STAT641 Class Project (Regression Analysis, Fall, 2019) Project Timeline: Final draft of report is due 5pm, Thursday, December 5, 2019 Each student is expected to do a project. You can work in a group of 2 if you wish. The project should be something pertaining to the materials we cover in the course. Each student (or group) will take some data and apply the techniques from class. The data analysis and results will be described in a written technical report. Choose a Topic First you must choose a topic to investigate. You must have one quantitative response variable and at least two *quantitative* predictor variables. Data a. Decide on the response and predictor variables. Determine the appropriate model and necessary assumptions. b. Write a protocol for your study. How will you get your data (online research data e.g.) Data Analysis Using SAS (or R, Minitab, Python…), a. Describe your data. Compute summary statistics (mean, median, standard deviation, etc.) Produce appropriate graphs (scatterplots, histograms, boxplots…). b. Perform a statistical analysis. Test for overall significance of your model. Make individual inferences about each parameter in the model. Obtain simultaneous confidence intervals and/or prediction intervals where appropriate. c. Check the validity of your model. If possible, test for lack of fit. Obtain residual plots and tests to verify your assumptions. Check for multicollinearity, outliers, and influential observations. Take appropriate remedial measures. Report Your report must be of professional quality and contain the following: I. Explanation of Research Topic What are you studying? Explain what you intend to show/discover with your analysis. II. Data Collection/Data Source Include the protocol for your study. Describe your data set and data actual collection III. Method of Analysis Explain the theory (model, parameters, assumptions, hypotheses, equations). Describe how to check the validity of the model and assumptions. IV. Results Provide descriptive statistics and graphs. Give the results of your hypothesis tests. Explain the significance of your findings. Was there anything usual? Did you meet the assumptions? Were any remedial measures necessary? V. Conclusions Explain conclusions and interpretations in layman’s terms. VI. References List all books, articles and web pages used. VII. Appendices Data set. SAS (R or Minitab, Python…) programs and output.
