Bring in your answers to questions 5 and 7 of the take home exam and any other questions you did not hand in, plus extra credit. We'll continue to work on the Sampling chapter and on Group designs. See you in our Library classroom
Hints for the Ch. 14 & 15 Quiz on statistics
  1. What is the major characteristic of the data that affects your choice of the appropriate statistic?
  2. When coding categories are said to be exhaustive and exclusive, what does this mean? Is this a good thing?
  3. What is the function/purpose of descriptive statistics?
  4. What is the function/purpose of inferential statistics?
  5. Interval/ratio data that are heavily skewed call for the median. Yes or No
  6. What does dispersion mean?
  7. With contingency tables, the independent variable is shown across the top of the table, for example male and female, so the differences between males and females with regard to STD fear would be shown in the columns. Yes or No ?
  8. By looking at differences in percentages, you can get a rough idea about the strength of a relationship. Y or N?
  9. Pearson's r is one specific measure of association. When comparing r values, which of the following is a higher correlation: -.8 or +.5 ?
  10. Which measure of association is used for nominal data in a 2 X 2 table? Check pg. 18 of your handout.
  11. PRE stands for the proportional reduction in error. This is the amount of error that is reduced when you know the independent variable and you're trying to predict the dependent variable. Usually you take the r value and square it. So if the r value is .5 and you square it, you'd get .25. In the class example, where we looked at the relationship between number of years of volunteer experience and the salary one would accept upon graduation; if r = .5, then r x r = .25-- this means that you would make 25% fewer errors predicting the dependent variable, acceptable salary, by knowing the independent variable, # of years of volunteer experience. Another way of wording it is to say that 25% of the variation in the acceptable salary one indicates can be explained by knowing the number of years of volunteer experience.
  12. What is a scattergram or scatterplot?
  13. What are Type I and Type II errors?
  14. What doers it mean when we say that a result was statistically significant?
  15. When do researchers use the multiple regression procedure? Look at pg. 18 in statistics handout