Some Exam Study Tips

Here are some suggestions for how you may improve your strategy for preparing for exams. These are all based on research findings, but we won't bother you with those details.

1. You should consider spreading your review of the material across the term, rather than saving it for the few days prior to the exam, as much as possible. For example, review the contents of a lecture shortly afterwards, while it's fresh in your mind. As the course makes new lectures applicable, review them in the same way, and also review earlier ones, but spending somewhat less time on the ones you've reviewed before. Maybe you do this already, but you should review things in 30 minute chunks, rather than powering through lots of material in a long session - the mind gets tired and confused, the more time it spends doing a task. These suggestions are based on the finding that spaced studying (distributed over time) and expanding series (Session 1: study one thing extensively; Session 2: study a new thing extensively and review more briefly the thing you studied in Session 1; Session 3: study a new thing and study briefly things from Session 1 and 2; and so on...) are the best methods for learning something well.

2. Study material actively - anything at all you can do that goes beyond what is written in the text or notes will be by far more valuable for your learning than just reading over the lecture slides and the textbook chapters. Think actively about how each concept relates to other things that you know or things that have happened in your experience. Think about how the material across lectures (or even within the same lecture) might relate to each other. Think of ways to organize different facts in your mind - sometimes a timeline is good, sometimes a hierarchy works, sometimes facts can be related in the form of a story (e.g., so first they thought this, then that proved to be problematic because of this, then they came up with this new idea, and so on).

3. Be aggressive at evaluating your own learning - if you've really learned something, you should be able to explain it to someone else - you can try to explain concepts to people that aren't taking the class (even if they didn't ask for your fascinating descriptions of psychological concepts). Generate possible multiple-choice questions without looking at your notes.

4. One thing you shouldn't do is try to memorize and get hung up on precise wording. Concepts appear on tests in words and phrases that might differ somewhat from how they are describe in the textbook or in the recorded lectures, yet the underlying meaning will stay the same. We do that on purpose. Our goal in constructing tests is to measure the extent that people really understand the information highlighted in lectures and the textbook at the level of meaning, rather than at the level of specific words. As a result, you’ll need to understand the concepts more deeply than by memorizing them word-for-word from the textbook or from the lecture slides or from the lectures. Strategies 2 and 3 should help with this because you are structuring the material for yourself, rather than relying on the specific way things are described in lectures or in the textbook.

We hope these suggestions are helpful!

A Note on the Standard Deviation

This issue comes up every year, so we may as well deal with it. In our lectures on calculating the Standard Deviation, we report that the denominator is: n – 1. That is, after adding up the deviations of observations from the mean of those observations, you must divide by the denominator of the number of observations minus 1. Many students enrolled in first-year math and/or stats classes like to point out this denominator as an error because it conflicts with information they receive in those courses. It seems that the equation for Standard Deviation that they often encounter in those courses reports the denominator as N, instead of n – 1. In actuality, both equations are correct and the contradiction can be easily resolved by pointing out that the Standard Deviation has different equations, depending on whether it is the Standard Deviation of a POPULATION of observations that is being computed versus a SAMPLE of observations drawn from a larger POPULATION. Imagine that we had all of the high school GPAs of every student beginning their studies at the U of M. We could calculate the Standard Deviation from that Population of scores by using N (the # of GPA scores we have) as the denominator in the equation. However, if we didn’t have the entire population of scores, we could obtain a smaller number of scores drawn from that population (say, 100 scores out of the much larger number of first-year students). In that case, we must compute the Standard Deviation using n – 1 as the denominator. The reason is that our goal is to estimate how much scores vary in the population, based on the information we have from a much smaller sample. Because we are using a sample, rather than the entire population of first-year student GPAs, we can only get an accurate estimate by computing the Standard Deviation with n – 1 as the denominator. You’ll just need to trust us in this one: using n – 1 in the denominator means that the Standard Deviation we compute will come as close as possible to the Standard Deviation of the Population of scores, even though the denominator for computing Standard Deviation for a population of scores is N, rather than n – 1. We report the equation for computing the Standard Deviation of a Sample of scores, instead of a Population of scores, because psychological studies most typically rely on observations obtained from a SAMPLE, and it is really quite rare for such studies to involve scores obtained from an entire POPULATION. It is simply too difficult to get observations from every single member of a POPULATION and it is usually much more trouble than it’s worth. We hope that clarifies things. 

Drugs and Addiction

Some students are surprised at some of our comments about drug use and addiction. Mainly, that's because the goal of a War on Drugs is to make extreme statements that terrify people into not doing them. As with any war, there is very little concern as to the truthfulness of the statements, since the goal of war is to win, not to be completely truthful. For example, people might be used to hearing that one or a handful of times using a hard drug, like heroin or cocaine, will more or less automatically turn a person into an addict. It isn't that simple. It is not uncommon for people to use these types of drugs a few times and then not use them again or use them occasionally without becoming chronic users. There are plenty of studies that have investigated this more rational perspective on drug use and addiction. Here is one web address to support our comments about this, for those who are interested:

http://www.drugscope.org.uk/resources/mediaguide/heroinmyths


Here's another link from a Parliament of Canada Senate Committee presentation by an expert on drug addiction from Simon Fraser University regarding the myth of drug-induced addiction:

http://www.parl.gc.ca/Content/SEN/Committee/371/ille/presentation/alexender-e.htm