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Simple Regression Modeling Steps Open the Excel worksheet containing your Team Project Data. As you learned in Module 2, run a simple linear regression model
Simple Regression Modeling Steps
- Open the Excel worksheet containing your Team Project Data.
- As you learned in Module 2, run a simple linear regression model using the independent numerical variable whose Excel worksheet column is highlighted in DARK ORANGE as the predictor ofYthe YELLOW Excel column.
- Cut and paste into your report the scatter plot and the Excel Regression Output for this simple linear regression model.
- Write the sample regression equation.
- Interpret the meaning of the Y-intercept and slope for your fitted model.
- Interpret the meaning of the coefficient of determinationr2.
- Interpret the meaning of the standard error of the estimate SYX.
- Obtain the residual plots and cut and paste them into the report. Briefly comment on the appropriateness of your fitted model.
- (1) If the assumptions are met and the fitted model is appropriate,continueto Step 2G.
- (2) If any of the linearity, normality, or equality of variance assumptions are problematic state this but continue to Step 2G. Note -- you do not need to check the assumption of independence in your project. (That assumption is automatically met because your project is not time-dependent).
- Comment on the statistical significance of your fitted model
- Comment on the 95% confidence interval estimate on the average impact on the response variable for each unit increase in the predictor variable.
- Select a value for your independent variable in its relevant range:
- Predict
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