Review Sheet for Exam Four

• You will be asked to complete aspects of the major types of computations that you have completed on the quizzes and in class. You may be asked to do the following:
  1. Regression
     • calculations:  calculating sum of squares for x, y, and xy from raw data; calculating slope & intercept from sum of squares values; writing out the regression equation and finding predicted values for specific values of x; calculating the SSE, s (the standard error of the regression model), and the standard error of the slope; calculating the confidence interval for the slope; calculating the test statistic for a formal hypothesis test of the slope value
     • conceptual work:  you may be asked to interpret slope, intercept, SSE, and s (standard error of the regressiom model) values and the CI of the slope; you also may be asked to carry out each of the formal hypothesis testing steps (as we have done in class) to test hypotheses about the slope, as well as to write about p-values and Type I/II errors. 
  2. Correlation
     • calculations:  calculating sum of squares for x, y, and xy from raw data; calculating slope & intercept from sum of squares values; writing out the regression equation and finding predicted values for specific values of x; calculating the SSE, s (the standard error of the regression model), and the standard error of the slope; calculating the confidence interval for the slope; calculating the test statistic for a formal hypothesis test of the slope value
     • conceptual work:  you may be asked to interpret values of the correlation coefficient and the coefficient of determination (r-squared); you also may be asked to carry out each of the formal hypothesis testing steps (as we have done in class) to test hypotheses about the correlation, as well as to write about p-values and Type I/II errors; know the conceptual caveats to a correlational analysis; know the links between regression and correlation
  3. Non-Parametrics
     • calculations: you may be asked to do the calculations for a Chi-Square and/or Spearman Rank-Order test
     • conceptual work: know the general distinctions between parametric and non-parametric stats (when you use each, what the advantages and disadvantages to each are, etc.); know when to use which particular parametric and non-parametric stats; be prepared to do formal hypothesis testing for any of the two non-parametric tests we covered in class (although, as in class, you will not be required to complete all aspects of the hypothesis testing framework for all tests; some of the steps will be done for you); know what observed and expected frequencies are & conceptual material about the chi-square and Spearman rank-order correlation covered in class