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Teaching Natural Sciences To Social Science Students?

timothy posted more than 2 years ago | from the use-lots-of-food-and-rent-analogies dept.

Education 265

An anonymous reader writes "As a calculus professor for a small undergraduate institution, I normally lecture students who are majoring in the natural (or 'hard') sciences, such as mathematics, physics, and computer science. In fact, I have done so for almost thirteen years. However, for the first time this fall semester, we have a shortage of professors on our hands. As a result of this, I have been asked to teach a general education statistics class. Such classes are a major requirement for the large psychology student body we have here. I have never lectured social science students in any mathematics-related classes. My question to the Slashdot community is as follows: What are your experiences with teaching natural science classes to social science students? How is the experience the same or different in comparison to natural science students who may be more adept to the nuances of mathematics and other similar fields?"

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They're just like other students. (4, Insightful)

Anonymous Coward | more than 2 years ago | (#40432571)

Some will be apt and mentally up to speed with whatever you through at them.

Some will be unable to comprehend every third word.

Some will be uninterested. Others will be interested, but incapable.

Re:They're just like other students. (2, Insightful)

Anonymous Coward | more than 2 years ago | (#40432655)

Some will be uninterested.

Most. And as a consequence, incapable. Or maybe it's the other way round.

Re:They're just like other students. (4, Interesting)

MagusSlurpy (592575) | more than 2 years ago | (#40432699)

I have to somewhat disagree with this. In teaching my inorganic chemistry and organic chemistry students, there is a huge difference between the chem majors and the biology majors (in genchem, they are still pretty much the same, as they haven't been "indoctrinated" yet). The chem majors know that do well, they need to practice, practice, practice. The biology students are all about memorization, flash cards, that kind of thing. Most catch on by the end, but for psych students, I strongly suggest that you drill into them from the very first day that the only way they will succeed in the class is by doing practice problems every day.

Re:They're just like other students. (-1, Offtopic)

Anonymous Coward | more than 2 years ago | (#40432747)

Speaking of indoctrination,

* Rape is not about sex, it's about power
* Race is just a social construct

Anyone stupid enough to believe these things is probably not going to learn any science at any more than than a superficial level, i.e. Galileo saw the phases of Venus, thus proving that that the sun is the center of the universe, however, the evil church people suppressed this knowledge because it offended their idea of God.

Re:They're just like other students. (0)

Anonymous Coward | more than 2 years ago | (#40433303)

Um, the sun isn't even the center of our solar system, much less the galaxy or universe!

Re:They're just like other students. (1, Insightful)

Anonymous Coward | more than 2 years ago | (#40433375)

Sure, buddy, sure.

But from what I've seen, #1 is mostly true. In case you didn't notice, there are a *lot* of power things in people's sexual desires. Unless you're suggesting BDSM is just about inserting tab A into slot B with a ridiculous amount of unnecessary formalities?

With #2, you don't know what they mean by race as a social construct. I, and another programmer, expressed that you could have medical problems which were noticeably affected by ancestry. So when we said "there are minor differences among races, almost entirely to do with distribution of medical problems, and any differences in important qualities (like intelligence) are almost certainly within the margin of error and should be treated as nurture-not-nature as a matter of practice", we were talking about genetic lineages, not physical appearance. When the professor protested, he was talking about race as a social construct, with all the PITA social baggage it brings in; about how people guess "race" based on appearance, use it to pre-judge, etc.

So frankly, I'm inclined to take the opinion of someone such as yourself, who wasn't perceptive enough to notice that, with a grain of salt.

Re:They're just like other students. (1, Insightful)

Anonymous Coward | more than 2 years ago | (#40433429)

Rape can be about power, otherwise people would never rape those of the same sex, or those who can't reproduce. Many aspects attributed to racial identify are social.

I think you've been a touch indoctrinated yourself.

Just a touch.

Re:They're just like other students. (0)

Anonymous Coward | more than 2 years ago | (#40433557)

I can attest to this.

The issue is firstly whether you teach facts or techniques. The second point is whether you adequately teach the links between the facts and an explanation of whence they came. Statistics is an unfortunate example because the real nuts and bolts don't become clear until you've taken undergraduate pure mathematics.

I'm a physics graduate; I suffered chemistry at high school and did appallingly. The reason was that everything was "it is, because it is" and I struggle to remember things without having a context or explanation. If mathematics is the byte code/assembly, physics is C, engineering is python and chemistry/biology is some higher level visual programming language. Point being that some people find things easier to accept than others, I could never do biology without understanding chemistry and I could never do chemistry without understanding physics. I've not yet got to a stage in physics where I care deeply whether I can really divide dy by dx, but that's just my personal limit.

Flash cards saved me in exams where there were significant marks for rote learning derivations or facts. However, powering through problems is essential for learning any sort of technique. Another programming analogy might be that I have, in my head, a good knowledge of programming paradigms. I know how to use OOP to my advantage or how to decompose a problem into loops and data structures. However, I always need a good reference book at my desk because I forget function names or how a particular language deals with data type X.

The best lecturing style we had this year was a guy who, at the start of every single lecture, would briefly gloss over the 'story so far' and explain the next problem that needed solving. He started out by giving a summary of the field (high energy astrophysics), that we see this distribution of cosmic rays, we know they're accelerated in supernovae shocks and other bits and pieces. He then taught with reference to that outline, gradually defined all the things he'd mentioned and showed how it all interrelated until we ended up back at the start. Not the best lecturer ever, but by far the best way to organise a course.

Re:They're just like other students. (0)

Anonymous Coward | more than 2 years ago | (#40432831)

mmm, ironing

Re:but it would be helpul if (0)

Anonymous Coward | more than 2 years ago | (#40432837)

Speaking not as a professor but as a student, I'd like to suggest that you keep in mind the nature of social versus hard sciences and find a way to emphasize the distinction, especially as regards the use of mathematics in the interpretation of 'data' where the soft sciences have such a 'hand wavy' approach to cause and effect.

To me, economics is a prime example. Forgive me if I'm off base in in my belief that economics is both sociological and soft(headed), but tyring to measure human behavior in the absence of an accounting for political corruption within this purely human realm and leaving the so-called black market beyond it's consideration leaves the inclusion of economics within the realm of 'science' suspect.

I would haved greatly appreciated any attempt by a professor to explain the difference between soft science and hard science, especially if it included an math based explanation of the nuance between these different domains.

Re:but it would be helpul if (5, Interesting)

stranger_to_himself (1132241) | more than 2 years ago | (#40433581)

...especially as regards the use of mathematics in the interpretation of 'data' where the soft sciences have such a 'hand wavy' approach to cause and effect.

To me, economics is a prime example. Forgive me if I'm off base in in my belief that economics is both sociological and soft(headed), but tyring to measure human behavior in the absence of an accounting for political corruption within this purely human realm and leaving the so-called black market beyond it's consideration leaves the inclusion of economics within the realm of 'science' suspect.

I would haved greatly appreciated any attempt by a professor to explain the difference between soft science and hard science, especially if it included an math based explanation of the nuance between these different domains.

Soft sciences are typically about trying to solve 'wicked' [] problems, which are those that are generally impossible to completely solve (end poverty or health inequality, understand crime, migration, or human behaviour in general etc). Hard scientists typically try to solve problems that are relatively much easier because they have a simple concrete goal (put a man on the moon, make a bomb, cure some disease)

Soft scientists need a much stronger theoretical framework to interpret their data, because of the absence of any really testable mechanisms for the effects they observe. This can come across as 'hand wavy' but it really isn't. Your economics example isn't entirely fair, some economic models will include corruption and black markets etc and others wont, just as some physics models include relativistic effects and others don't. A good scientist has to choose the right model to approah any problem, regardless of discipline.

I've been working in an inter-disciplinary group and have had the opportunity to see medics and economists try to work together. The two cultures are very different in their scientific approach, both consider the other to be unnecessarily picky about some aspects of the work while not being rigorous enough in others. Eg economists spend a huge amount of their time trying to prove causation in observational data, while medics will typically wave this away if they think the causal effect is likely enough. On the other hand economists tend not to contextualise their results well enough, while medics will see the bigger picture in terms of building on existing science.

Re:Soft sciences are about wicked problems (2)

TaoPhoenix (980487) | more than 2 years ago | (#40433653)

This might be the angle in for the original questioner's method.

Maybe he can reduce the raw theorems by 25%, and instead push harder on media and logical thinking issues.

Instead of too much push on the formal notation, what if he goes into a lot of "biased science" examples from the real media? Showing how slanted presentations produce emotional reactions, etc.

In a sense, "If I were in a position to hire", I'd rather have a smart thinker who's drilled cold on picking up sample bias than a book theoretician who can drill out 18 line proofs but folds the minute he/she gets into something about affordable housing studies and doesn't account for geo-social trends.

Re:but it would be helpul if (0)

Anonymous Coward | more than 2 years ago | (#40433833)

Hard scientists typically try to solve problems that are relatively much easier because they have a simple concrete goal

Yea, it's pretty hard to solve a problem if there is no definition of "solve", i.e. no concrete goal. A physics scientist wouldn't set out to completely understand all forces of nature, that's a wicked problem that he knows is impossible to solve; so he sets a concrete goal that is solvable.

Re:but it would be helpul if (5, Insightful)

Skippy_kangaroo (850507) | more than 2 years ago | (#40433839)

I will try to inform you a little about economics (speaking as the holder of both a BSc and PhD in Economics):

The key difference is that economics and social sciences are mostly non-experimental (people don't take kindly to you arbitrarily changing their parents, education, or wealth - which is the 'experimental' way of establishing cause and effect). This means that the statistical issues are orders of magnitude larger than those that exist in experimental sciences. In an experimental science you can go off and get new data where you have controlled for most everything except the effect you are interested in and a simple regression will generally be all you need. In a non-experimental science you are stuck with the data that nature has given you. As a result you need to be very careful to get meaningful results. But, in case you are doubting, you can get meaningful results if you are careful enough.

Thus, my second point: Economics is not soft headed. In fact, it is very hard headed because you need to be when you are dealing with data that are generally speaking - crap. There are so many ways you can be mislead by non-experimental data and you need to be very hard-headed to avoid this. I won't claim mistakes haven't been made, but those mistakes are the reason economics has gotten much better at dealing with this than many people might realise. But, there is only so much you can do when the data are the way they are.

So don't assume the difficulty of getting solid results in economics reflects the ability of the practitioners rather than the raw materials you are dealing with.

Re:They're just like other students. (0)

Anonymous Coward | more than 2 years ago | (#40432903)

Self-correct: Throw.

Some will be uninterested, even if capable.

statistics a soft science? (1, Insightful)

jehan60188 (2535020) | more than 2 years ago | (#40432629)

I'm sorry, am I misreading or are you saying statistics is a "soft science"? If you're that confused about things, then just go to the textbook, and teach one chapter a week.

Re:statistics a soft science? (0)

Anonymous Coward | more than 2 years ago | (#40432661)

correct, and computer science is a natural science.

Re:statistics a soft science? (1)

jehan60188 (2535020) | more than 2 years ago | (#40432815)

not sure if I'm being trolled, but I'll bite.
If you can show how Bayes' theorem is considered soft science, and machine learning is somehow considered hard science, then I will drop out of grad school

Re:statistics a soft science? (0)

Anonymous Coward | more than 2 years ago | (#40433311)

Whoosh x1.5

Re:statistics a soft science? (2)

englishknnigits (1568303) | more than 2 years ago | (#40433333)

Citing a specific example of hard science that is encompassed within a science does not prove the encompassing science itself is hard science. (notice I didn't say anything about statistics...just as the OP didn't say statistics was a soft science).

Re:statistics a soft science? (1, Insightful)

icebike (68054) | more than 2 years ago | (#40432855)

My thoughts exactly.
Statistics is just math.

If the OP thinks this is somehow different in social sciences vs the "hard" sciences, he is badly mistaken. In fact he might broaden his horizons a little to learn how to handle those experimental designs where you have no perfect control group since you can't just go out and give people cancer just to test in the real world, nor kill them just to autopsy them after the experiment has run its course.

He might end up losing some of his elitist attitude before the course is over. It would be better if lost the attitude ahead of time, and approached the experience like he was at least teaching the same species.

Re:statistics a soft science? (5, Interesting)

stranger_to_himself (1132241) | more than 2 years ago | (#40433457)

My thoughts exactly.

He might end up losing some of his elitist attitude before the course is over. It would be better if lost the attitude ahead of time, and approached the experience like he was at least teaching the same species.

Indeed. I teach statistics to mathematicians, biologists, psychologists and social scientists and I would say the social scientists 'get' the principles of statistics better than the 'hard' scientists do. The main reason is that soft scientists (which is a horrible term) can think about uncertainty and its consequences, whereas hard scientists (mathematicians included) are unhappy if they don't have a yes/no answer to a question. Obviously this is a generalisation but it may inform your approach to teaching.

Also, statistics is not 'just math'. I know this because I can do statistics but I can't do math(s) any more. :-)

Re:statistics a soft science? (2, Insightful)

PT_1 (2425848) | more than 2 years ago | (#40432877)

I'm sorry, am I misreading or are you saying statistics is a "soft science"? If you're that confused about things, then just go to the textbook, and teach one chapter a week.

I understood the summary to mean that the OP is teaching a statistics course to soft science students (those who are majoring in social science and phychology), and not that (s)he considers statistics to be a soft science.

Re:statistics a soft science? (5, Insightful)

bleedingsamurai (2539410) | more than 2 years ago | (#40432941)

Not to be rude, but reread the post.

The OP says he normally teaches hard sciences to students with a major in a hard science meaning that they are more likely prepared for the learning of hard sciences. Because of some staffing issues the OP now must teach his hard science classes to students with a major in soft sciences, thus previous classes may not have fully prepared them for a hard science class.
Because of this the OP is asking how to mold his teaching strategy to better target those soft science majors.

Keep it simple (2, Informative)

adoll (184191) | more than 2 years ago | (#40432703)

Avoid using overly abstract concepts, and try to put things in terms they can understand. Since you are teaching statistics, try to use a lot of gambling references (lotto, roulette, etc.) since nearly all the students will have some familiarity with those.

I've found I can teach engineering concepts to elementary school teachers as long as I avoid formulae (and avoid using Latin references, so use the term "formulas" :-) ).

Re:Keep it simple (4, Insightful)

grcumb (781340) | more than 2 years ago | (#40432909)

Avoid using overly abstract concepts, and try to put things in terms they can understand.

Arts major here, who's been working for about 20 years in IT. I'd offer a qualified agreement here. I found some science subjects innately easy, because I was able to visualise the forces at work. Vector equations in physics, geometry, etc. were dead easy, even when they became more advanced. But the moment the teacher began to fall back on jargon and symbolic shorthand, I'd get lost.

The reason is pretty straightforward. I am extremely good at certain kinds of pattern-identification, but quite poor at others. Among the ones I'm poor at are mathematical equations, which are not evaluated in the same way natural languages are. It's merely a left brain/right brain thing, and I can compensate by using different approaches. I thrived under teachers who understood this, and died under teachers who spent their entire time writing equations on the board without attempting to contextualise them.

Re:Keep it simple (3, Insightful)

Trepidity (597) | more than 2 years ago | (#40433041)

I think some of it is getting the big picture / motivation as well. A lot of students don't have the background many Slashdotters have in documentaries, natural-science museums, even sci-fi, which can lay the big-picture groundwork, with which you can then dive right into equations and methods in the courses. When it comes to physics, for example, a large number of students probably first need to be brought up to "read some Carl Sagan" levels of understanding, which would put them in a lot better position to learn more quantitative aspects.

100% agree (1)

gestalt_n_pepper (991155) | more than 2 years ago | (#40433717)

A great deal of math and science is conceptually trivial. What trips me up is symbolic notation. For some reason, it gives my brain fits. Give me the same problem with a decent verbal explanation and yeah, I'll have it coded up for you in a few minutes, thanks. Obviously math notation works for most people, but not for everyone.

Start simple.. (1)

Anonymous Coward | more than 2 years ago | (#40432733)

Tell them, everyday at the beginning of the lesson, the purpose of each topic you teach and how it is going to be useful for them when solving a problem.
Tell them again at the end.
Knowing why you are teaching them something like hypothesis testing is half the battle to get them to listen.

And examples, lots of examples.

Your question sounds contrived (0)

Anonymous Coward | more than 2 years ago | (#40432737)

Why are you asking about "teaching natural science classes to social science students," when mathematics is not a natural science?

If you were truly a math professor of any kind, surely you would know this, and you would also know that the syllabus of statistics 101 is so basic that it doesn't vary depending on the major of the students sitting for the class.

And finally, why would any legitimate professor of anything be asking for teaching advice on Slashdot?

distinct iterations within a subject (0)

Anonymous Coward | more than 2 years ago | (#40432741)

I have no experience, but I believe in adding detailed layers per (sub)-subject in distinct iterations. I am attending university at the age of 32. When I follow the lectures, the teachers exhale all the theory and statements in one breath. it annoys me the most that they somehow explain distinction within one subject, thus while processing the new material, you easily confuse or associate one formula expression with a general statement you can claim by using the formula.

oh yea, don't turn your back on them. Since they are the social kind, they probably want to see your face, even while writing the chalk board... (will you even have a chalk board?)

Re:distinct iterations within a subject (1)

defiant.challenged (1072712) | more than 2 years ago | (#40432765)

... it annoys me the most that they somehow explain distinction within one subject, ...

I ment to say: it annoys me the most that they DO NOT somehow explain distinction within one subject ....

somewhat off topic? (0)

Anonymous Coward | more than 2 years ago | (#40432755)

This isn't what you asked but ... ensure you use the terminology wrt statistics that social scientists use, not the terminology that those in other sciences use. Explanation: as a grad comp sci student years ago, I took a course (I think it was in finite difference methods) from the engineering department. Part way through I had an "aha!" moment when I realized the prof was talking about things I knew, but using a different vocabulary.

If you want to be brilliant, when you introduce terms, tell your students, "this is what it's called in, e.g, sociology, but this is what it's called in physics/engineering/etc.

No (2)

Bill Dimm (463823) | more than 2 years ago | (#40432757)

Betteridge's Law of Headlines [] . Did I do that right?

Re:No (1)

PPH (736903) | more than 2 years ago | (#40432921)

Is this [] a better link?

Re:No (1)

Bill Dimm (463823) | more than 2 years ago | (#40432981)

Oops. I didn't notice the apostrophe in the URL and it prematurely terminated my href='...'. Thanks for the correction.

Re:No (1)

c0lo (1497653) | more than 2 years ago | (#40432925)

Betteridge's Law of Headlines [] . Did I do that right?

Not a headline... but also no [] .

Re:No (1)

Xtifr (1323) | more than 2 years ago | (#40433389)

Leave it to slashdot to invalidate the law by using a question mark for something that's not even a question! :)

In any case, I think the law only applies to questions that have yes/no answers, and not, for example, to questions like "Who Stole the Mona Lisa?", "What is the Effect of Coffee on Sleeplessness?", "Where Will the Enema Bandit Strike Next?", "When Will the Bridge Re-Open?" or "Why Can't Johnny Read?"

Re:No (1)

Bill Dimm (463823) | more than 2 years ago | (#40433935)

The intended joke was that it could be answered with yes/no due to the weird way that it was phrased.

Grade point (-1)

Anonymous Coward | more than 2 years ago | (#40432813)

Psych students assume they'll get an A in every course they take. You'll be a bad guy if the class average is a C.

Er... (2)

fuzzyfuzzyfungus (1223518) | more than 2 years ago | (#40432823)

Isn't the use of statistics pretty much the only thing that distinguishes 'psychology' from 'talking about feelings'?

I realize that most psych majors don't actually go on to practice in psychology or psychiatry, and the ones that do generally have to do some flavor of graduate work; but I'm still rather alarmed by the implication of TFS that psych students might well be deeply uncomfortable with statistics...

Re:Er... (1)

slew (2918) | more than 2 years ago | (#40433445)

Ironically, I've found many computer science majors are not very versed in the ramification of statistics either. I think it has something to do with the binary world that they envisage or something like that.

The most common example is the "1-in-a-million" mentatlity many computer science majors have when talking about bugs or special-case code paths. You'd think they'd know better as they can often quote all sorts of statistical sort or database traversal, O(log n), big-o little-o, etc, but when you get them with a common sense thing about code performance issue, they appear to get some sort of temporary lobotomy.

it's comprehension, it's appreciation (4, Insightful)

holophrastic (221104) | more than 2 years ago | (#40432849)

As someone who's been on both of those academic sides (I started in hard, and moved into soft four years later), I never thought it was a lack of comprehension when fellow students have trouble with hard sciences. Instead, it's an appreciation for numerical conclusions.

Hard sciences basically tend to conclude three steps earlier than soft sciences -- because the math ends there. Hard sciences tend to describe a scenario, detail it numerically, hypothesize a numerical result, experiment numerically, solve for x, and x=n is the answer. The issue for soft science students is really that nobody ever cared about x. Hard sciences very quickly forget where x came from, because the entire scenario was translated into numbers. This affords hard sciences a certain level of abstraction, making problems faster to solve, easier to solve, and more widely relevant to re-apply.

Soft sciences tend to be industries where some aspect of the scenario can't be translated into numbers. It's usually a black-box scenario, and psychology is a good example. Such experiments don't attempt to describe certain behavioural anomalies numerically. Instead, 40% - 80% of a scenario is translated into numbers, leaving the remaining 20% - 60% as mysterious elements. Imagine a hard science equasion where six linear constants simply cannot be merged into a single constant -- for no seemingly good reason. As a direct result, after solving for x, the numerical abstraction must then be de-abstracted back into whatever the real-world scenario actually is. This procedure is not only an effort to grasp, but it's also a a major point of interpretation at the end of an experiment -- usually because x isn't the number of grams diluted; instead x is the likelihood that a person might turn left.

The nice part about de-abstracting at the end is that you wind up with a real-world answer, not a mystery number.

So my point is, that for a social science student used to walking in with a scenario, and walking out with a conclusion, you need to teach them how to appreciate the hard-science "datum result" without having a one-question-one-answer conclusion.

You can see this same effect in the business world. Big business corporate C.E.O.'s often make decisions from numbers in, to predict numbers out, without ever knowing where the numbers came from, nor how they'll be used on the way out. But if you've seen anyone go through "board of director" training, you know that the skills wind up applying to any business anywhere because they are all done at the hard-science executive level.

Constrast that to the entrepreneur of a small business, who needs to make all of the same decisions, but simply doesn't have the sample-size of data coming in to ever be able to make decisions numerically like the corporate guy -- which is one of the primary reasons that he has an advisory board instead of a board of directors. The decision-making process is very different, even though they are the same questions and the same answers. And each has a very difficult time in the other's business world.

Here's hoping someone else's response details a good way to actually teach that appreciation.

Translation (0)

Overzeetop (214511) | more than 2 years ago | (#40433501)

Expect that most of your students this semester will have avoided ever having to solve for x, and their entire academic arc is predicated on claiming that the answer for x does not really matter because they are being trained to solve problems subjectively which are too difficult or complex to represent as a closed for solution to an equation.

Short version: they will all guess at the answers on your test and none of them will be able to solve anything as complex as the quardratic equation.

You have to options: Fuck with their minds on stuff like the Let's Make A Deal and other hard-math probability scenarios and flunk them all, or keep to the straight and narrow path, giving them the simple version of everything that won't require much more than my 4th grader had to learn for her standardized tests, plus an introduction to the various distributions, pass them, and call it a year.

(Note: I've taken Stat at the undergrad and grad level, and watching the people squirm with the weird stuff is the best part. If you can avoid squirming yourself.)

It is easy teaching psychology students. (4, Funny)

140Mandak262Jamuna (970587) | more than 2 years ago | (#40432857)

First thing to do is to get emacs and get the doctor watson mode working. Then have some sessions with Watson and understand how to talk to psychology students. To my best understanding, it involves rephrasing their questions and asking them why they ask that question or what their feeling is. All you need to do is to wing it for 50 minutes and charge them one hour of tuition fees. They will get the hang of it and learn to speak to their clients for 50 minutes and bill them for an hour.

Re:It is easy teaching psychology students. (1)

Xtifr (1323) | more than 2 years ago | (#40433511)

First thing to do is to get emacs and get the doctor watson mode working.

Doctor mode (M-x doctor). I'm not sure what a "doctor watson" mode would be. Would it be like the old movie version? Follow you around and act dumb to try to make you seem smarter, and occasionally exclaim, "that's simply astounding!", and "I don't know how you do it"?

Re:It is easy teaching psychology students. (1)

140Mandak262Jamuna (970587) | more than 2 years ago | (#40433631)

I must have confused the M-x doctor mode of emacs with the Dr Watson error dialogs from Windows NT. Sorry for the mistake. I have not used a true emacs editor for a long time. (no, no I did not switch to vi, nor to MsDev editor. I am using Visual Slick Edit that supports all the key binding of Emacs).

easy to memorize (1)

malbosher (795323) | more than 2 years ago | (#40432863)

Math and Hard science are easy for me. Just memorization, some students do better and some won't. students who consistently want to know why, normally have a harder time with math.

Social 'science' is a sham, more like scientism (-1)

Anonymous Coward | more than 2 years ago | (#40432881)

Nothing but an attempt to mix biology and statistics. And even the study of statistics is a bit on the flaky side.


Anonymous Coward | more than 2 years ago | (#40432891)

Toss 'em (him/her) in the river. If 'em drowns, 'ems a witch. If not, well, we's can't always be right !! It's not just the law, it's God's law, natural and science !!

Textbooks (0)

Anonymous Coward | more than 2 years ago | (#40432901)

First, you came to Slashdot for advice on this topic? Really? Could you not have considered browsing the curriculum at other institutions taking note of the number of statistics courses expected from these students as well as the recommended texts.

Let me suggest that you request copies of Moore & McCabe and maybe Howell, just as starters. I'm sure others will suggest other titles. If you're also required to teach a regression class, then here too you'll have to located a textbook. Oh, and read the textbooks.

Re:Textbooks (0)

Anonymous Coward | more than 2 years ago | (#40433045)

BTW, based on your pre-existing bias and inability to solve this question on your own (poor judgement), I'll suggest that you're ill-equipped to teach statistics and experimental design to this group of students. You will compromise their future - at least those who plan to complete an honours project and perhaps head to grad school. I also suggestion Keppel's book(s) on experimental design (you'll find similar from the biological sciences).

Reality is consistent (0)

Anonymous Coward | more than 2 years ago | (#40432961)

The laws of this universe do not differ in nature between those fields of knowledge where the prerequisites for the correct use of the natural scientific method are met and where those prerequisites are not. Both sets of knowledge are objective. Just because the natural sciences permit the constraint of most variables and permit experimental repeatability does not mean the social sciences are not equally rigorous. So long as the epistemological arguments are understood as to what methods are suited for fields of study in these non-empirical fields, both are valid means of investigating the world.

So long as you understand that, and treat your students with the same respect and demand for scientific thoroughness, you will do well.

It's not Special Ed (5, Insightful)

AK Marc (707885) | more than 2 years ago | (#40432973)

You make it sound like you are teaching physics to special ed classes.

They are as smart as everyone you've had so far. You may see some differences in their backgrounds, but that's easy enough if you make allowances to give more basics or point them to appropriate resources. I'd give an example, but I have no idea what "natural science" is to you. Geology and oceanography are natural sciences, same as physics, but they share little in common.

One thing you may notice is that arts students in hard classes may want more "why" than "how" answers. So be prepared for more philosophical discussions, or correct, if silly, comments (i.e., the "why" for valence electrons is that the stable ones are like a comforable couch, and the unstable ones are hard benches. You want the better seat, but you don't really want to get up, and the worse the chair, the sooner you'd move) or something like that. The "why" as an expression of potential energy in MeV won't get the point across as well as a discussion of musical couches, and they'll remember it better, isn't that the goal, over the goal of the hard science students where accuracy is above all.

Re:It's not Special Ed (4, Insightful)

muridae (966931) | more than 2 years ago | (#40433189)

I wanted to mod you up, but I'd rather add this: Psych students need to know statistics. Statistical analysis is 90% if their later term research; my sister spends paper writing time compiling data on people, analyzing how patterns stack up into behavior predictions. Yes, you can look at a group of people and predict what the chance is that one will have a mental illness, or who is suicidal, etc. It's not soft science, it's actuarial math. Combining individual research into meta-analysis to see how certain medications affect both groups and individuals. Seeing how changes in groups affect individual members. Even at the undergrad intern level, that was what her last two years of psychology classes were.

My advice to the poster is simple. They aren't idiots, and they need to know how stats work. Don't start classes with intense set-theory notation unless they have that as a pre-req. Don't pull a Taylor series out to explain something if the school doesn't require a course with that as a pre-req. Use lots of people examples, instead of abstract "X is a part of set S"; and as someone else suggested gambling stats are also good. And for their sake, don't talk down to them unless you want them to fail. Or if you have tenure. These are psych students, they can manipulate the hell out of you if you seem to be annoyed with them.

Note: if you pace from one side of the lecture hall/room to the other a lot, watch for them to drop papers and pencils when you do. Classic psych prank to get a teach to stop pacing. They can have you trained by the end of a semester if they want.

Re:It's not Special Ed (1)

Anonymous Coward | more than 2 years ago | (#40433563)

Yeah, I was surprised about the question. I don't know the Ask Slashdotter's institution but at my alma mater, the first two introductory stats courses for psych students were at least as difficult as the first two introductory stats courses for math, stats, science and engineering majors. The courses were slightly different (psych got their own two, math/stats/science got their own two, and engineering their own, AFAIK) but they were more or less comparable.

Arts, humanities and business students got a different pair of stats courses, and these were not considered equivalent to the aforementioned three.

In fact, the psych stats courses may have been the most challenging. I can't be sure as I did not do them. Because of university limitations, the psychology department was limited in how it could restrict student admittence, so they used a loophole... Students with highest GPAs got to register first so the two psych stats courses were mandatory for all later psych courses and had limited enrollment and number of class offerings. Some students with quite solid academic backgrounds couldn't get into the courses because they were already filled by students with even higher GPAs. And the department then used those two stats courses to set the bar where they wanted it.

But at the very least, psychology students should be at the expected science major level.

Re:It's not Special Ed (3, Informative)

Anonymous Coward | more than 2 years ago | (#40433655)

Step one when teaching a class like this: ask the department that they are in what these students will need to know and why it is a required class.

When I was forced to teach introductory logic to mathematics majors, that is what I did. Not only did it make my examples something they were more familiar with, but it also caused me to change my curricula that I offered by skipping certain things they didn't need (e.g. square of opposition) and focusing more on what they do need (e.g. WFFs and formal systems).

So, don't ask slashdot, ask the psychology department.

Yes, they use stats, but... (3, Interesting)

jensend (71114) | more than 2 years ago | (#40433847)

If I had a dollar for every paper published in a peer-reviewed social sciences journal which totally abused statistics, I'd retire and use my extra cash to fund organizations directed at basic logic and math education, trying to help with the situation.

Most social studies students I knew had little understanding of the statistics they were using. It was basically a magic incantation for giving them results and making their conclusions sound more credible to other people who likewise didn't understand statistics. The result is bad statistics and bad science. Yes, these people aren't idiots, but they've become used to being rewarded without having to think rigorously.

The impression I get is that the pattern persists even among those few who make it into the field. There are some psychologists etc who are really trying to do real science- a difficult task since the basic concepts are even more up in the air than the basic concepts of chemistry were in the days of the alchemists. As far as I can tell, however, quite a lot are quite happy to be able to find ways of running a study so it will inevitably vindicate their preexisting biases and will fudge the statistics to match.

For the OP: You're right to be concerned. Students for the GE stats class are usually woefully underprepared. Rather than giving them the rigorous preparation in logic, multivariate calculus, etc they really need to understand statistics, the GE stats class does the equivalent of the Wizard's favor to the Scarecrow.

"I can't give you a brain, so I'll give you a passing grade! Now you understand statistics! Go back to your department now, please. (Phew, they're gone at last. That kind of work may pay the bills here in the Stats dept. but it doesn't do wonders for my sense of academic integrity as an educator.)"

I'd recomend showing how it's relevant. (4, Informative)

Karmashock (2415832) | more than 2 years ago | (#40432985)

A major problem with these sorts of courses is that they're often not taught in a way that emphasizes their utility to the student. If you're thinking about being a psychologist for example why is calculus important? I'm not saying it isn't. I can think of several different ways it could be very important especially as it regards understanding statistics.

But you might want to create some test questions that relate to their majors.

In business calculus they focus on it's relationship to various economic calculations. So you might want to look at drug trial statistics or anthropological/demographic statistics.

And for the love of God... please tell them that correlation is not causation. You'd be doing everyone a huge favor. These guys are going going write stupid papers or write blogs or something similar that will pop up in the media. And everyone here at slashdot will be facepalming over another dumb paper that didn't acknowledge that simple fact.

Just saying.

Umm... you did say "statistics," right? (0)

Anonymous Coward | more than 2 years ago | (#40432987)

So you are going to be teaching a general statistics course, right? So what's the problem? If they gaduated high school, they should be able to plug and chug. I wouldn't bother showing them how to use calculus to derive the formulas. Just give 'em the formulas and put 'em to work

Here's what a business school stats prof did. (0)

Anonymous Coward | more than 2 years ago | (#40432991)

Assign homework.

At the beginning of every class, he went around and checked off if you did it or not.

Doing your homework was part of your grade - 10% I think.

He was a real ball buster from Trinidad. After I was done, it was the first time -ever - in my school career that I did really well in math. I remember him fondly - guy with a beard of (black) African decent and his old red baseball cap. I wish I could remember his name. If he saw you in the cafeteria studying, he would make a bee line over to see if you had any questions and to shoot the shit.

No one ever taught me how to succeed in Math before that.. It was drilled early on in my mind - by teachers and my parents - that you had a talent in it or you didn't. It wasn't something that could be cultivated by work - I am definitely NOT saying kids should go all Asian and work themselves to death there are some limits to hard work.

Re:Here's what a business school stats prof did. (4, Funny)

turkeyfeathers (843622) | more than 2 years ago | (#40433193)

I think that professor was me. I am from Trinidad but my parents were from Nigeria where I am living now. I would love to get back in touch and have a beer with you. If you could please send me a small advance for travel along with your SSN and a passport photo I can begin to make arrangements.

Not to land on you, but... (1)

cbrew (628146) | more than 2 years ago | (#40433065)

You really shouldn't generalize about what psychology majors are going to be like. In the department I did my Ph.D in, psychology was closely allied to biology and ecology, and there was another department across campus that did social psychology. Some of the psychologists were pretty darn quantitative. But they were being quantitative about the mind, which is (my bias) maybe more interesting than the examples you used last time you taught calculus. Also, while the majority of students may be psych majors, some will be from other majors. What do you want future lawyers, school principals and politicians to know about statistics? This is your chance to teach them. Sooo, they might have good math skills, or not. But you can't assume that they know calculus, obviously, so you probably want to use a textbook that treats stats as a tool for understanding patterns in data, and goes easy on the theory behind maximum likelihood estimates and so on. I like Perry Hinton's Statistics Explained, but it really depends what you are trying to teach the students to do. [] If the psychology majors are any good, they may be more used to thinking clearly about surveys and tricky experiments than you are. Perhaps you can structure the course so that learning goes both ways.

Simple Before Moving On (0)

Anonymous Coward | more than 2 years ago | (#40433071)

Make sure to beat the simple topics to death, because those are the only pieces that will stick in anyone's head.
If you aren't doing stats all the time, then you just refer to someone who is..

On the other hand if you don't know how to setup your
experiment to be statistically analyzed then your wasting everyone's time.

Abandon all hope (0)

solidraven (1633185) | more than 2 years ago | (#40433079)

Run to the hills and don't look back! I've tried on several occasions to explain basic statistics to social science students, it's a hopeless effort. Very few of them seem to have a feeling for it. And those that do will act like they don't cause it's "cool" to suck at statistics.

Categories (3, Insightful)

paleo2002 (1079697) | more than 2 years ago | (#40433095)

Always interesting to see the categories different parts of academia place each other in. The post's author is calling math, physics and comp-sci "natural sciences" and apparently considers statistics to be "social science". I'm a geology professor and, as far as I'm aware, my colleagues and I tend to consider Earth, environmental, and biological sciences to be the "natural sciences"; physics, chemistry, engineering, and any math to be "physical science"; and psychology, sociology, (cultural) anthropology, etc. to be "social sciences". Everything else is art and/or humanities.

I wonder how other groups categorize one another? Right off the bat I'd suspect that mathematicians don't always consider themselves scientists. Perhaps ditto for engineers. People tend to form and place each other in groups of varying degrees of subjectivity. How you place others probably says something about the standards and values of one's own group.

This sounds like it'd make a great piece of social-psych research! They love this kind of fluff, right? (j/k)

Re:Categories (1)

gringer (252588) | more than 2 years ago | (#40433259)

The post's author is calling math, physics and comp-sci "natural sciences" and apparently considers statistics to be "social science". I'm a geology professor and, as far as I'm aware, my colleagues and I tend to consider Earth, environmental, and biological sciences to be the "natural sciences"; physics, chemistry, engineering, and any math to be "physical science"; and psychology, sociology, (cultural) anthropology, etc. to be "social sciences".

My mental image of natural science also includes biology, geology and ecology in the "natural sciences". I'd consider maths and comp-sci to be too abstract to be a natural science (something like the study of patterns and algorithms rather than the observation of patterns and algorithms).

Re:Categories (0)

Anonymous Coward | more than 2 years ago | (#40433277)

Mathematicians call ourselves scientists if and only if we are trying to explain to other people why it is worth paying us.

Re:Categories (1)

Tooke (1961582) | more than 2 years ago | (#40433433)

The post's author ... apparently considers statistics to be "social science".

No, he/she said statistics is a requirement for the psychology students, of which they have a lot.

In response to the rest of your post, I don't really think of CS being in the same category as math, physics, etc. It just doesn't seem as "science-y" to me.... Though I'm just a student barely starting his CS degree, so what do I know eh.

Re:Categories (1)

Xtifr (1323) | more than 2 years ago | (#40433645)

Always interesting to see the categories different parts of academia place each other in. The post's author is calling math, physics and comp-sci "natural sciences" and apparently considers statistics to be "social science".

I think you misread. He's not calling statistics a social science. He's asking how to teach "hard" math (statistics) to students whose background is in "soft" social sciences.

My Experience (1)

Javagator (679604) | more than 2 years ago | (#40433129)

I don’t mean for this to sound arrogant, but it probably will. I was a physics major who took a statistics course that was taught in the Psychology Department and meant for psychology students. A lot of science and math majors took the course as a way to pad their GPA’s. I could see from the books the other students brought to class that about one forth of the students were science or math majors. I think I made about a 96 on the first test and was embarrassed at the thing I missed. The class average was 48 or something. The grad student teaching the course said that maybe the test was too hard, but “there were a lot of very good grades”. I have a feeling that not many of the good grades were made by the psych majors.

If I were teaching the course, I would probably emphasize the purpose of the various statistical techniques for behavioral evaluation, and not make the math portion too detailed or rigorous.

Re:My Experience (0)

Anonymous Coward | more than 2 years ago | (#40433179)

It appears that you didn't learn anything about data, and error in judgement. I'm being serious.

Re:My Experience (0)

Anonymous Coward | more than 2 years ago | (#40433215)

Let me re-phrase. It appears that you did not learn anything about data, hypothesis testing, and knowing which question(s) to ask. You chose to construct the model to fit your perception. And, it is clear you did not identify the error that initiated the cascade to your conclusion. Perhaps you'll be good enough to propose several alternative hypotheses as well as identify that first mistake (that will likely remain with you for life).

Re:My Experience (1)

tomhath (637240) | more than 2 years ago | (#40433509)

I don't see any mistake in his observation. I had a similar experience in a Logic course that was cross listed in Philosophy and Comp Sci.; the semester I took it the course was taught by an engineering professor who stated that, as in all engineering courses, the average grade for the class would be a C+. About 1/3 of the students immediately got up and walked out.

As someone who just took my first statistics class (0)

Anonymous Coward | more than 2 years ago | (#40433307)

I'd have to say prepare for the unexpected. I'm in an MBA program, and was not looking forwards to our statistics course. Something quite interesting happened, though. A student in my team, who had never gone to college (is a screenwriter) was terrified of the course, blew everyone away. Even compared to those who majored in a 'hard' science where left in his tracks. So, try and toss your expectations of who will do well in the class aside. Since you're teaching psychology students, and statistics are very relevant to their field (especially misinterpreting them) it should be easy for you to emphasize the relevance to their major.

On a practical note, if you are going to use Excel for the course, be sure and tell people using Mac's to put Windows and Office 2010 on their machine (using VMware Fusion is the simplest way to go). In standard Microsoft crappy fashion, they didn't put the all the statistics functions in Office 2011 (to try and force people to install Windows). And tell them to turn Windows update off! Installing the OS takes 25 minutes, but Windows updates take 5 hours!!! Obviously you should never let Windows connect to the internet, so disable that, and then they can trash Windows when they are done with the course. If they haven't spent much time with Windows 7 yet, they will be blown away by what a piece of garbage that OS is. Jesus. If they are going to do serious statistics, then they'll be using a real program like SPSS which runs native on OSX.

Statistics vs Calculus (1)

MountainLogic (92466) | more than 2 years ago | (#40433353)

There is an interesting talk by Arther Benjamin [] arguing that for most students stats are for more valuable than calculus as an end point as they are more relevant to everyday life.

Re:Statistics vs Calculus (1)

goodmanj (234846) | more than 2 years ago | (#40433599)

I'm a physics professor -- aka, The Reason You Take Calculus -- and I totally agree. I think all high schools should teach statistics as a mandatory 12th grade math class. Students who intend to go into technical fields (physics, chemistry, carpentry, metalworking) should take trigonometry, and nobody should take pre-calculus or calculus until college.

Seeing as this is a new class... (1)

Genda (560240) | more than 2 years ago | (#40433361)

You might want to try this in a new way? Have your students use the Khan Academy to look at topic lectures. Take the short tests after each section to see who's having problems and with what sections. This allow you to provide the interesting stuff, make you lectures about the relevance of what they're learning to the process of understanding the flow and function of populations and how statistics are a powerful tool to let us begin to extract patterns of form and function inside what would would otherwise look like turbulent and unpredictable systems. They even let us predict outcomes in nonlinear systems. Also, you can get tutors through the Khan Academy, so anybody who is having a little difficulty can actually work with someone who already understands the concepts. The point is you can do the cool stuff, watch your students perform, support the stragglers, and get the feedback you need to have everyone complete the course informed, knowing the material, and enjoying the process that got them there. A win/win.

The one down side is that they Statistics series isn't quite complete yet, but its getting there, and there's more than enough there to get your kids started.

Try (1)

JustOK (667959) | more than 2 years ago | (#40433383)

At my univ, "stats" was a very core part of post-grad psychology. Unfortunately, many students only cared about stats with respect to surveys/questionnaires, and they had problems with that :(

BUT multivariate stats was still seen as important and was required, along with experimental design. At the undergrad level the psycho-stats included the basics, including null-hypothesis, which stats to use depending on the experimental design etc.

Grab some real psychology (not couch psychology) studies, and look at the experimental design and what statistical methods were used in them. Take a look at the texts used in the good psych schools.

For the sociology students, pat them on the head and tell them that things will be ok.

Teach modelling and show examples (1)

ACluk90 (2618091) | more than 2 years ago | (#40433401)

My advice to you are the following two points: 1. Teach mathematical modelling. In my experience many students, also those in technical sciences, have problems creating reasonable mathematical models. Once you teach them to do that, they will see by themselves how math can actually simplify their lives. 2. Work with examples from their (!) field. I have heard a lot how for example med students complain about their physics courses being completely unrelated to their studies. But as soon as you point out that Bernoulli's principle applies to blood flow and you give them some time to think about what this means in case of Arteriosclerosis they are fully interested again. This becomes even more important towards the end of the term when exams come closer and students might start skipping classes "not relevant for their further studies".

Been tutoring stats to buiness majors. (1)

Bork (115412) | more than 2 years ago | (#40433411)

You’re going up against the left brain / right brain situation. The hard sciences are more of logic, analysis, detail oriented thinking, where the liberal art side are the intuitive, creative thinkers that are more in tune of the shape of things. The social science side tends to attract those with the right brain dominate way of thinking of things; they will try and process numbers as a shape/color/texture instead of a symbolic/fact/defining.

Draw a Venn diagram and they will be right with you talking about it but write it out in logic notations( P(A)+P(A’)=1 ), you will have a sea of blank faces looking at you. Numbers and symbols are very difficult for them to process and will need a lot more pictures and drawings that help them relate the two together.

To switch places, try taking a very good math student and ask him to paint a picture; color, shapes, patterns do not translate well for them.

science and science (0)

Anonymous Coward | more than 2 years ago | (#40433443)

Try looking at voting or decision theory. The topics are of interest to social scientists and lend themselves to mathematical modeling to pose questions and answer them.

The distinction between natural and social science is not crystal clear, as some others have pointed out. Look at Karl Popper, who looks at generalizing and historical sciences in"physical"/"natural" science.

Don't overemphasize the mathematics. Models and explanations should be judged by their explanatory power rather than the abstractness or sophistication of the models.

Some experience here (1)

DiegoBravo (324012) | more than 2 years ago | (#40433461)

First, on any engineering courses the students take for granted the need for math/science. That's not your case, so take some time every class to explain why and how this could be useful for your students beyond passing the grade

Second, they usually had a very hard time with school math, so take it easy and by all means try to avoid showing how smart you are when dealing with the abstractions and the logic, instead focusing on how little is needed to cover most of your material.

Third, they don't enjoy the solution of very difficult problems or challenging exercises (like a science/engineering student does.) They really enjoy the simple fact of grasping the concepts and making something useful with that

Fourth, check your students' background. Be prepared to provide several high/elementary school sessions.

fifth, your students are very good for reading, so give them some literature partially related to math (for example a biography of Descartes showing some of his math discoveries.) That's a pretty good way to generate interest. If they're political interested, then talk about Marx's math manuscripts, etc.

Pedagogy & Positivity (2)

ancarett (221103) | more than 2 years ago | (#40433487)

If you're not familiar with it, I recommend you read Ken Bain's What the Best College Teachers Do (2004) [] which provides a wide range of insights and approaches that can help you out in any classroom. Speaking as a former science major who went on to a Ph.D. in history, the number one difference I notice between the streams is that many of the social science and humanities students believe they're bad at math and statistics. Problems in high school convinced them that they can't cut it - a high proportion will claim they're incapable in the fields. The secret to your success is convincing them that they can and want to master these skills.

I know - I teach a stats module as part of my sophomore course for majors. They learn how to read, interpret and critique statistics in articles in their field of study. Did you know that most of them don't know how to read and interpret statistics? The number of students at the start of the course who tell me they don't stop to read the charts because "they'll never understand them" is staggering. Statistical literacy should be the bedrock skill you inculcate. Show them good and bad uses of statistics. Teach them to figure out when someone's playing fast and loose with figures, hoping to fool readers. That will build their confidence and their thirst for knowledge.

My students go on to create their own time series and other statistical outputs from a dataset that they all find fascinating. (I use the Old Bailey Online [] for this, a website with material in statistically manipulable format for almost 200,000 trials at London's major criminal court: almost everyone finds the history of crime at least a little bit intriguing and so they will persevere a bit more when they run up against problems or road blocks.) Don't waste a lot of the time throwing new theories at them - make sure that every new concept you introduce is tied to something they'll want to and be able to explore.

Sure, some won't want to try. They'll find the work too hard or uninteresting no matter what you do. But others will be able to master this if you make it clear both why they need to learn certain techniques and how while giving them some clear and jargon-free walk-throughs. Exercises they can tackle tied into the fields they already find interesting are a great way to keep them motivated.

Look at some of the textbooks that are out there for stats that are directed to your U's social science fields - see what elements they emphasize as important for the field of psych, poli sci, etc., and then decide how you want to incorporate those key elements into your own teaching. Avoid getting too tied into teaching a particular software package - make sure they understand how to generalize their application.

Good luck - you're tackling what many consider a thankless course but one which can help to change students from math-phobic and fearful to at least statistically literate and confident that they can understand and apply some basic skills in the field as they go on in life.

heterogeneity and probability (1)

cretog8 (144589) | more than 2 years ago | (#40433513)

First, it might not be important, but the title bugs me: statistics isn't a natural science.

I teach economics, and the biggest thing I note about my students is the heterogeneity in mathematical capabilities. I always need to keep on my toes about who I'm boring because they can handle that math in their sleep and who I'm leaving in the dust so that they're not even close to learning what I'm talking about. In a hard science program, there will presumably be some of that, but a bit more pressure on the low end which will make the students more homogeneous.

What to teach depends partly on whether you imagine this is a terminal class for a lot of the students. If so, teach general ideas which they'll be able to dredge up 6 years from now when the ideas are relevant, because they'll forget the details. If it's not a terminal class, try to teach some of the example applications which they might see in future classes.

Behavioral economics is pretty hip these days. Pulling examples from that literature (such as the popular stuff by Dan Ariely) is likely to interest a lot of students and be directly applicable for psychology students (since lots of behavioral economics is more about psychology than economics).

I have a strong bias about how statistics should be taught these days, though I've never tried it and could be proven wrong. I think that statistics should be taught as (1) probability theory, followed by (2) monte carlo methods, and then follow that up with more classical statistics and nonparametric tests. Monte carlo testing gets at the core concepts of what rejecting a null hypothesis means, what confidence is all about, etc and it's straightforward to do these days. Once the ideas are clear, then you could move on to the standard t-tests and so forth. But if you start with monte carlo, the students will grok the notion without knowing calculus as opposed to spending all their time trying to memorize formulas.

Make it as hard as possible (0)

Anonymous Coward | more than 2 years ago | (#40433547)

Let them suffer.

Change nothing (2)

brillow (917507) | more than 2 years ago | (#40433551)

You do it exactly the same. Psychologists take stats pretty seriously.

From a fellow professor (1)

goodmanj (234846) | more than 2 years ago | (#40433555)

I'm a physics professor who teaches some similar classes, including a course on climate change for nonmajors. I also deal with a lot of students who take stats. Statistics is probably the most uniformly loathed class in every university. Neither its students nor its professors want to be there.

Your first job is to convince students that they need to know this material, not just because it's a requirement but because it's vital. Start your class off with some statistical disasters. Drugs that were approved without proper testing, which turned out to be useless or harmful; innocent people sent to jail via the prosecutor's fallacy; major ideas in the social sciences which turned out to be based on baloney statistics.

Your second job is to forget you're a mathematician. You've been trained to formally prove everything you say. Don't. These students will take "because I said so" as a legitimate explanation, and will never need to prove things on their own the way your other students will. Give them useful definitions, rules, and formulas, without the backstory. Tell them that common random events often have a bell-curve distribution, but do not prove the central limit theorem. Show them how and why to do a t-test, but don't show the PDF for a t-distribution or the equation for it.

Finally, be very careful with your attitude. It's easy for a specialist to conclude that because these students are untrained, they're stupid. But if you motivate them enough, you'll find that many are just as smart as the physics majors in your calc class. Some, you'll find, are not, but don't let the bad ones shape your impression of the class, or you'll lose the respect of the good ones.

what to cover (1)

hedrick (701605) | more than 2 years ago | (#40433591)

I taught stat to a business school audience, too many years ago to think about. One thing you have to figure out is what to cover and from what viewpoint. Math students might be interested in the math behind some of the statistical methods. Social science students probably aren't. To be honest, they're just going to use canned packages, so details of the math are not the most important thing to teach them. What you really have to teach them is what all the math means. What assumptions are the methods based on? What do they do? When do you use them?. How do you formulate problems? What are the most important ways that people can unintentionally (or intentionally for that matter) get completely meaningless results out of statistics? E.g. what does it mean when you try 20 different models, and one of them is statistically significant at the .05 level? Answer: it means nothing at all. But those kinds of results get reported all the time. Have then read some of the articles on why so many drug studies are turning out not to be meaningful.

You may find it hopless (1)

Streetlight (1102081) | more than 2 years ago | (#40433601)

As a college chemistry professor, I had a chem major who took a one semester statistics course taught by a Psych Prof at our school. I'm not sure why she didn't take the statistics course taught by the math department. Maybe it was because she could get general education credit from this course. Anyway, the course never got to the standard deviation because the prof required the students to do the calculations by hand. The students couldn't do long division so they couldn't calculate the requisite ratios. Square roots? They never got a chance. I guess they spent many weeks calculating means, medians, deviations from the mean and medians and their sums, squares, etc. What a waste. They certainly didn't get into the subtleties of the meaning of SDs, significance of differences between means, t tests, etc., etc., etc.

Try to Put Yourself in Their Situation (0)

Anonymous Coward | more than 2 years ago | (#40433697)

I teach astronomy to non-science major students at a large public university. I'll try to give you a few of my best suggestions, as I have been relatively successful.

Try to remember where these students are in their educational careers: they may not have had very much of a math and/or science background. The process of the scientific method and thinking in equations is probably not their forte. Many of them may resent taking such a math class, or have a math "phobia". My suggestions pretty much follow from this.

I should make it clear that I do NOT think that non-science students are all stupid or incompetent. Most of them CAN understand the concepts, but they are unfamiliar with the mindset and often intimidated where math is involved.

1. Think very carefully through your lectures/presentations and look hard at the language: what jargon are you using? There are a lot of terms that I bet you use that you don't realize the general public does not use in the same way. Phil Plait had a good example of some of these in a Bad Astronomy blog entry: Think about your language and simplify things where you need to - don't introduce jargon unless you feel it's crucial. After all, you want the students to learn and understand the concepts - you don't want to end up testing their vocabulary. You will also be more accessible if you don't sound like you're trying to be uber-scientific.

2. Presumably your students are supposed to have achieved some basic math level. Don't assume that they are all at that level, and even those that are may be uncomfortable with it. Many of them have difficultly with the basic abstract concept of algebra, that a symbol represents a quantity, and that there can be a lot of power in manipulating an equation AS symbols, before plugging in numbers. You will need to work with them to enable them to be comfortable with the equations and realizing how they can be used for proportionalities, inverse proportions, etc. I forget where I read it at, but a science educator commented that for many non-science/math students an equal sign in an equation does not denote that the stuff on the left and right of the sign is equivalent, but that an equal sign is an indication to start calculating (i.e., plugging in numbers and doing work). I try to help my students understand WHY equations make sense, such as, "It makes sense that if you throw a bowling ball the same way as a baseball, the bowling ball will hit with more force" for F = ma.

3. You need to make special effort to get them to understand the meaning of their results. Most of them will be happy when they plug in numbers and get a numerical answer. They will have no conception of giving their answers a common-sense check (i.e., my velocity is faster than the speed of light - maybe I made a mistake!). If you want them to have this kind of understanding, you need to teach them how to think about it and use it. This is a good place to put in a lot of relevant examples, as other posters have suggested. If you can show that they can make sense of their answer in some real-life way (i.e., my answer says that I should win at roulette 110% of the time), then it will be more accessible and intuitive for them.

Statistics is very non-intuitive, so that presents an extra challenge. I hope you're planning on doing a lot of demos with coin-flipping, drawing unseen objects, etc. Whenever possible, I suggest doing these in small groups (rather than the whole class) to get the maximum impact.

Good luck!

natural my ass (1)

Shavano (2541114) | more than 2 years ago | (#40433725)

Math and computer science are not natural sciences.

Prepare for some remediality (1)

rknop (240417) | more than 2 years ago | (#40433751)

The main thing you need to be aware of is that there are students in college -- decent numbers of them -- who cannot comprehend 7th grade math.

Not all social science majors are like this by any means. But there are some. They tend not to end up in the hard sciences, because they just won't survive there. But they can survive in other fields. What's more, they have the idea that it's OK not to understand math, and that it's "unfair" to demand that they have any kind of grasp of 7th grade math. I suspect that this latter attitude comes from the fact that there is a non trivial population of college *professors* who can't do 7th grade math.

What's most frustrating about the whole thing is that if you try to teach the remedial stuff to the ones who need it, you will bore the living daylights out of the ones who don't need it. They will rightfully wonder why they need to sit through so much review of very early high-school mathematical concepts such as basic algebra.

good advice (0)

Anonymous Coward | more than 2 years ago | (#40433761)

I am a researcher in higher education learning and teaching, my focus is interdiscilinarity and disciplinary languages, and I have in the past worked in all three of the knowledge domains (humanities, social sciences, natural sciences) First, Slashdot is the last place you should be looking for advice on a matter like this, you will not get information which comes from experience or research into the questions you are asking, this can only come from the academic community (there may be a few others from there here, but you're best asking within academia first.

You need to talk to the other lecturers in the social sciences in the school you are teaching in to see what the expected level of student understanding of and interest/engagement with mathematics in general and statistics specifically is. You should also talk to lecturers in social science statistics at other universites, that should give you your best insights. I know, for example, that there are several major textbooks on Introduction to Statistics for Social Scientists. You should look at these as well, they should give you a good outline of the typical course structure, amount of material to cover, and starting point for explaination, as well as probably some good examples of concpets put into social sciences terms which you can use until you get comforatable. also, if there was a course before, shouldn't there already be a course guide and lesson plan outline, possibly some powerpoints as well?

Been there (1)

Egg Sniper (647211) | more than 2 years ago | (#40433763)

I've got an engineering background and have taught computer aided design and programming in the past. I've taught statistics to classes largely composed of psychology students a few times as well.

Know what they are expected to know: the prerequisites for the course I've taught are very minimal so I can fully expect some students to struggle with basic algebra. While the majority do seem to be able to 'plug and chug' reasonably well, their ability to actually understand what the equations they're using mean conceptually is severely lacking.

Focus on what the math is saying: the first couple times I was able to cram a lot of different statistical analyses into a semester, and the students were largely able to keep up with the math and work out the solutions correctly. Unfortunately some of the really basic concepts still sounded foreign to them because they had spent all their time doing math problems.

Think small: If you start with probability and normal distributions it's a stretch to even progress through Z and t tests into the analysis of variance (if that's the sort of route you're taking) in a single semester. I think it's better that students more fully understand a couple, extremely basic types of statistical analysis instead of quickly being 'exposed to' several in the course of a semester. If one fully understands the logic and mathematical relationships behind a simple Z test on a sample mean they should be able to fairly quickly understand the more complex analyses.

If it is germane to the course, focusing on the non-math concepts like experimental design is also important, and generally more useful for students heading toward graduate school.

Show them the "hard science" in *their* discipline (0)

Anonymous Coward | more than 2 years ago | (#40433773)

I was trained in the "hard sciences" (and still view myself as a researcher in that area, neuroscience) and I've been teaching statistics to psychology majors at a tier-1 university for over ten years. Don't let the students think that statistics is something other than their field of study. Doing statistics *is* the bulk of doing psychological research (or biological research, or sociological research, etc etc etc.). My advice:
1) Find a handful of journal articles that demonstrate really interesting results in what you think is the home discipline of your audience
2) Teach them *why* (and *how*, on a conceptual level) the studies were conducted in that way, with specific reference to the statistical analyses
3) For 1st adn 2nd year stats, they should understand that the p value is not the probability that the null hypothesis is wrong, but the probability that is is true given the data.
If they understand *why* statistics are done the way they are in their discipline, then they understand that their discipline is just as "hard science" as any other. And that should leave them plroperly educated.

Re:Show them the "hard science" in *their* discipl (0)

Anonymous Coward | more than 2 years ago | (#40433799)

p = The probability of getting data with an effect as big as their theirs, or bigger, if the null hypothesis is true.

Doing exactly this right now (1)

siwelwerd (869956) | more than 2 years ago | (#40433823)

Lots of bad advice in this thread. As a fellow mathematician who has taught intro stats before, and am currently teaching it (at a large research university) again this summer, here is my take: 1) Be prepared for the fact that many will not have taken a math class in many years, some 5 or more. They will recall little from their previous math classes other than intuition. Their arithmetic skills are poor. Be sure you are evaluating them on their understanding of the stats material, and be forgiving of arithmetic errors 2) They will be heterogeneous. Some will prefer abstract formulae, others will want to see things in words. Give both. Some will like to read the book, others will like lectures. I am linking to relevant Khan Academy videos on my website along with the date of the lecture they go along with. Anything you can do to come at things from various angles will increase the proportion of the class that understands it. 3) Try and explain the big picture. I am often motivating things with social science "experiments", or medical experiments. Find out what kinds of examples click with your students, and use those. While their arithmetic skills are often abysmal, they generally grasp quite readily the major ideas, how one should apply them, and when. They just get lost a bit in details. 4) Don't get bogged down teaching too much probability. It's an easy trap to fall in to. 5) Have fun. I've found teaching this course to be more work, but rewarding. A lot of these students have a near phobia of anything math, it's nice to see things clicking for them and them grasping the big ideas, if not the specific computations. Okay, back to writing tomorrow's lecture... P.S. Neither math nor statistics are "natural science", much less any kind of science.

It will be like this (2)

germansausage (682057) | more than 2 years ago | (#40433827)

True Story: -Engineers at my school had to take 15 units of Arts courses as part of their studies, and Economics 100 was one of the popular choices. We had an Econ 100 class that matched a hole in the 3rd year mech and EE schedule, as a result we had about 2/3 engineers and 1/3 Arts students.

One day the prof, a very smart man with a subtle sense of humor, drew a graph of some function on the board. He drew the x and y axes, a straight line with a 45 degree slope and labelled the x intercept "a" and the y intercept "b". One of the girls from Arts puts up her hand and says "I don't think it should be that steep". The prof erases the line, redraws it half as steep and labels the x intercept "a" and the y intercept "b". "How's that" he says."Much better" says Arts girl.

Every engineer in the place falls over laughing. We laugh even harder as we see the confused look on Arts girl's face as she tries to figure out what's so damned funny. The prof never cracks a smile.

You're teaching them stats. (1)

Dcnjoe60 (682885) | more than 2 years ago | (#40433951)

You are teaching them stats, not calculus, so you shouldn't approach it like it is calculus. Social Science majors know they need statistical analysis. So do business majors.

For the record, my son had a major in psychology and a minor in math. Soft sciences and hard sciences are mutually exclusive and people don't go into the soft sciences because they can't do hard science. People go into soft sciences for the same reason as people go into hard sciences -- because they are interested in the subject matter.

Teach the subject at the appropriate grade level and quit looking down your nose at non-math and physics majors. Teaching statistics might be below the level of a calculus professor, but maybe both student and teacher will learn something from this.

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