Here are links for Psychology 302, Winter 2003
Instructions for final paper/project
STUDY QUESTIONS FOR FINAL in Psychology 302
Quizzes have been focused on two or three chapters at a time. The final exam (20% of final grade) is different. Although part of it is concerned with text chapter 11, the rest is cumulative, and more of an exercise in developing an integrated understanding of the material in the course. It puts more of an emphasis on an understanding of concepts used in the course, especially in terms of how they relate to one another. The cumulative part of the final exam will be focused on (though not limited to) the following nine questions. These topic areas may be reflected in exam items that call for an open-ended response in a similar form to how questions are worded below. Or, they may be reflected in multiple choice or fill-in items or in problems, of the kind that have been seen on the quizzes and you are already familiar with. About 25% of the final will be focused on Chapter 11, and the best way to prepare for this is to read the chapter, study up on the key concepts at the end of the chapter, and look over notes and homework problems.
1. Suppose someone tells you about a finding that there is an average difference between two groups of people. (For example, that the average man and the average woman differs in how many colors [e.g., blue, red, beige, mauve] they can name/identify. The average woman can name/identify more colors.) In order to draw appropriate inferences about this difference, why would it be important to know the standard deviation or variance?
2. What's the difference between the two terms in each of the following pairs of concepts:
A large effect/A significant effect
Phi coefficient/Correlation coefficient
Z test/t test
Cross product/Correlation
Histogram/scatter diagram
Positive correlation/negative correlation
p<.05 / p< .01
Point estimate/Population parameter
Type I error/Type II error
S2between / S2within
Statistical significance/statistical power
Sdifference / SM
Correlation coefficient/regression coefficient
SD2 / S2
3. What do SD, Spooled , and Swithin have in common?
4. How are normal, t, F, and chi-square distributions similar, and how are they different?
5. How will you decide which statistic (among the following) to use, in order to test a hypothesis?
(Z, t for single sample, t for dependent means, t for independent means, F [one-way
ANOVA], factorial ANOVA, chi-square, correlation coefficient)
6. Explain how increasing the sample size affects each of the following: power, effect size, type I error, type II error, the likelihood of "significant" results, estimates of the population mean and variance, and confidence intervals.
7. What are some of the reasons why a research hypothesis can turn out to be "not statistically significant"? (including but not limited to "because the research hypothesis is actually false")
8. How could you compute a Z, t, or F value, once you know the sample mean(s), and the standard deviation and standard error [standard deviation of the distribution of means, or comparison distribution] for the sample(s)?
9. How does one test a hypothesis using the correlation coefficient? (re-read pages 71-73)