Question 1: Why might a data set suffer from missing data? Explain the techniques researchers may use to handle missing data during data analysis.
Question 2: What are the four rules that guide the coding and categorization of a data set? Explain why each one is important for researchers.
Question 3: If a researcher must use a non-probability sample because a list is not available, should convenience sampling or judgment sampling be used? Explain
Question 4: What is the difference between a probability sample and a non-probability sample? Which one is preferred by researchers? Explain
Question 5: What is the difference between a Type I error and a Type II error? How are the two errors related?
Question 6: Define the null and alternative hypotheses. Discuss the relationship between the two hypotheses.
Question 7: What advantages do stem-and-leaf displays provide over histograms?
Question 8: What can a researcher determine through the use of cross-tabulations?
Question 9: Provide some advice for a person writing a short research report
Question 10: Define the null and alternative hypotheses. Discuss the relationship between the two hypotheses.
Question 11: What are the assumptions made by the regression model in estimating the parameters and in significance testing?
Question 12: What can a researcher determine through the use of cross-tabulations?