How many students are in each group? Summarize the data relating to both test scor by the student group (separately). Use appropriate numerical and/or graphical summaries. (3 points) Do the test scores vary by student group? Perform a one way ANOVA using the aov o function in R to assess. Summarize the results using the 5 step procedure. If the res overall model are significant, perform the appropriate pairwise comparisons using Tul procedure to adjust for multiple comparisons and summarize these results. (7 points Create an appropriate number of dummy variables for student group and re-run the c ANOVA using the Im function with the newly created dummy variables. Set chemistry students as the reference group. Confirm if the results are the same. What is the int of the beta estimates from the regression model? (4 points) Re-do the one-way ANOVA adjusting for age. Focus on the output relating to the co of test score by student type. Explain how this analysis differs from the analysis in ste (not the results but how does this analysis differ in terms of the questions it answers to the one above). Did you obtain different results? Summarize briefly (no need to go the 5-step procedure here). (6 points)