I have finished the “Correlation Analysis “and “Linear Regression “(I copied all the charts, tables, and figures in the memo, and you need to answer questions based on these data and delete the extra ones that are not helpful to the problem.), you only need to answer the questions by using these data in the red text of the file. And I also upload the Dax 4 memo?which is compared with Dax 5?, I have completed all the parts that need to be analyzed by SAS. You just need to answer the memo’s questions with the tables and figures in my file.
In this exercise the students will compare a model that only contains position 1 to the regression model from DAX 4. They will then use this new model to test if the company discriminates by height. The students may refer to previous instructions for more details on how to run the analysis in SAS. A video is attached that demonstrates how to compare similar results. The conclusions will likely be the same as in the video, but the numbers will likely differ slightly. YOU MUST HAVE THE CORRECT CORRESPONDING NUMBERS TO YOUR DATA TO RECEIVE CREDIT.
Instructions
- Use your labor data set to create a data set that contains only position 1.
- Use this data set to run all analysis to test assumptions (summary descriptive statistics with max min, mean, etc, Regression Analysis Results Table that shows F, Pr, and R-square you produced in your analysis, correlation analysis ,and scatter plots of continuous variables (height, years of employment, and performance)
- Note: An Example of Regression Analysis Results Table is in following link below (Example Only – Not DAX 5 results) that must be submitted along with all the other tables and figures created for DAX 5 to prove that a Regression Analysis was conducted: Example Regression Results Tables-2.pdf
- Run a linear regression of $/hr in SAS using Location as a classification variable and with performance and years of employment as continuous variables.
- Run a linear regression of $/hr in SAS using Location as a classification variable and with height, performance, and years of employment as continuous variables.
- Use the outputs to complete the memo. NOTE THE ASSUMPTION TESTS CAN BE LIMITED TO THE MODEL WITH HEIGHT
- Paragraph 3 summarizes the results discussing whether the model is significant, states which parameter estimates are significant and interprets them, discusses the root MSE, R-Squared, and if the results are meaningful. Tables and graphs should be referenced. Comparisons should be made between the DAX 4 and DAX 5 model and between a Model with and without height.
- Paragraph 4 is a summary Paragraph with a conclusion, a recommendation, and the impact of the recommendation.The conclusion is the plain language answer to the research question. It should also provide a recommendation to include position 2 in the model or not and for what action to take against a potential lawsuit for height discrimination.
