Posted: October 9th, 2017
Is group comparison the best approach to analyze the available data? Why or why not?
- Suppose that you have collected data throughout a semester from a large elementary school regarding the number of days per week each math teacher spends in a collaborative teaching community. The average ranges from 0 to 7 days per week. You have also obtained the pre-test and post-test scores in math administered in those same classrooms in the beginning and end of the semester, and you have calculated a score that shows learning during the semester by subtracting the pre-test score from the post-test score for each student.
You are interested in examining any potential differences in student learning (i.e., post-test minus pre-test) that may be due to the number of days of teacher participation in a collaborative community. Is group comparison the best approach to analyze the available data? Why or why not?
- Assume that you are interested in the relationship between Graduate Record Examinations (GRE) scores (the total of all subtests) and graduate school grade point averages (GPAs) at the end of their graduate programs. Conveniently, you have access to the GRE scores and GPAs of a large number of graduate students who have graduated from the electrical engineering master’s program in an Ivy League university between 2000 and 2013. The Pearson correlation coefficient did not reach significance. What can you conclude from the data analysis? Can the result be generalized to all graduate students in electrical engineering master’s programs across the United States? Why or why not?