I need the 3 exercises below to be completed By 2 PM pacific time Monday Feb 1 st: The attached file is to be used to complete Excercise 3. i will upload 2 more files to complete exercise 4 and 5.

**Exercise 3: Single predictor regression (residual analysis)**

For this exercise you will use the same data set used for exercise 2. Fit the simple regression analysis for the same dependent Y = Number of refereed journal publications since Ph.D. (PUBS) and independent variables X = Years since Ph.D. (TIME). Now conduct a residual analysis. The rubrics specified above (Exercise scoring guide) will apply for grading. Provide an interpretation of your residual analysis highlighting major issues if found.

Using the data from Exercise 2, show or calculate with matrix algebra (Proc IML)the following matrices and vectors: X, Y, X`X, (X`X)-1, det(X’X), X`Y, b, Yhat, e, SSR, SSE, SST

Construct the ANOVA summary table by hand.

OR

Residual Analysis (2 pts EC)

Provide examples using graphs (hand drawn, web or SPSS/SAS generated) where homogeneity of variances, normality in the distribution of errors and non-linearity are NOT satisfied. Explain how each assumption maybe violated.

**Exercise 4: MR (intro)**

We have added annual salary (9 month) for use as a new Y-variable to the data from Exercise 2. There is an excelfile in e leaning named “publisperishdata_salary.xlsx”. Import it to SAS or SPSS and then .conduct a two variable multiple regression with X1 = Years since Ph.D. (TIME), X2 = Number of refereed journal publications (PUBS) and Y = Salary earned per year (SALARY). In your write-up include a statement regarding the significance of the overall model and each parameter along with your interpretation of the parameters.

MR Extra Credit (1 pt)

The EC is due with Exercise 4; please use a separate attachment for it in the eLearing drop box.

Write a paragraph to review (APA format with a complete APA citation) of a primary source that utilized multiple linear regression. Be sure to answer the following questions in your summary: (a) What is the general problem under study, (b) specifically what research question/hypothesis are the researchers testing within the specified analysis (i.e., multiple regression), (c) what are the criterion and predictor variables, (d) does the analysis relate to the general problem the researchers are investigating (e.g., from your answer to part (a)) and (e) what were the findings of the specific analysis?

**Exercise 5: MR – Model Fit**

SAS users Download the BODY2.DAT and the SAS (ex05start.sas)/SPSS (ex05start.sps) start program eLearning. Predict weight (kg) from only the girth measurements (12 predictors). Write up your analysis and findings.

Determine the “best model,” a model with the maximum R2 or Adj R2 with minimum multicollinearity and extraneous variables for predicting weight from the 12 girth measures. Do residual analysis. Write up your analysis and findings.

Model Evaluation Extra Credit (1 pt)

The EC is due with Exercise 6; please use a separate attachment for it in the eLearing drop box.

Write a paragraph to review (APA format with a complete APA citation) of a primary source that presents a comprehensive analysis of the model fit (multicollinearity and/or outlier analysis) in a multiple linear regression analysis. Be sure to answer the following questions in your summary: (a) What is the general problem under study, (b) specifically what research question/hypothesis are the researchers testing within the specified analysis (i.e., multiple regression), (c) what are the criterion and predictor variables, (d) how id the authors present the analysis for multicollinearity and/or outliers and (e) what were the findings of the specific analysis?

Subject | Mathematics |

Due By (Pacific Time) | 02/01/2016 02:00 pm |

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