McGraw-Hill OnlineMcGraw-Hill Higher EducationLearning Center
Student Center | Instructor Center | Information Center | Home
PageOut
Implementation tips
Feedback
Help Center


Kincaid: Research Projects in Statistic 1/e
Research Projects in Statistics
Joseph Kincaid, Blue Cross and Blue Shield of Kansas City

Data Analysis

Implementation tips

Help the students through the data analysis

In many of my courses, the objective was to help the students become intelligent consumers of statistics. In these courses, I asked the students to bring me the data on a floppy disk and I would carry out the analysis and talk them through the steps. Together we would check the assumptions for the data, discuss graphical and numerical summaries, perform the statistical analysis, and discuss its interpretation. This approach allowed the students to work through relatively interesting projects without worrying about the level of analysis required at the end.

In other courses, the objective was to help the students become producers of statistics. In these courses, the students were responsible for carrying out the analysis themselves, but they were free to ask me questions at any time. Many times, I didn’t see their analysis until their final presentations.

In both cases, the students were responsible for presenting the analysis and their conclusions in their oral and written presentations.

But make them do their own data entry

The title speaks for itself.

Grading data analysis

In course where the students are responsible for their own data analysis, I consider the final conclusion to be part of the analysis. I then assign a grade by evaluating the analysis on four criteria and the conclusion on three. If there was something wrong with the analysis or the conclusion, it usually fell into one of these criteria.

Criteria for the analysis:
  1. Was the analysis based in the research question?
  2. Was the analysis appropriate for the variables involved?
  3. Was the analysis done correctly?
  4. Was the analysis done completely?

Criteria for the conclusion:
  1. Were the conclusions answers to the research question?
  2. Were the conclusions based on the analysis?
  3. Were the conclusions properly stated?

This approach allowed me to grade the analysis, the oral presentation and the written presentation each on its own merits.

Points for the data analysis

In classes where the students are responsible for their own data analysis, I recommend assigning 5—10% of the points to documenting the data analysis.