QUANT homework
Applied Learning Research Project Phase II (due August 21)
Project Part 2 : Reference all prior notes and readings for the course as support for completing this assignment. Ensure that ALL prior instructor requested corrections to your approaches to formatting, etc … taken when completing your HW assignments, are understood and that you have addressed any misconceptions you had prior to submitting your Project Part 2 assignment
Part 2: Simple Regression Pre-Analysis
- Select 1 response and 1 explanatory variable from the Project 1 dataset (list your choices). Please do not choose variable combinations that were assigned in HW previously
- Perform a Simple Regression assumption check. That is, check all 4 Simple Regression assumptions. In 4 separate subheadings (Linearity, Normality, Independence, Equal Variances) write up your results. Include all supporting evidence (tables, charts etc …). Appropriate formatting and use of complete sentences is expected.
If you were justified in running the simple regression (that is all assumptions for running a simple regression analysis were met) please report your regression output tables from Excel . Also, please run the analysis and interpret your output tables relative to the significance of the regression model, the coefficient of the regression explanatory variable, and the regression numerical summaries (Multiple R and R squared). Write up your significant/ not significant simple regression analysis results as follows:
A simple regression was run to predict (response variable) from (Explanatory variable). Results show that the explanatory variables does / does not statistically significantly predict (response variable). F(df regression, df residual) = Significant F, p< , =, or > .05. The explanatory variable does/ does not contributes significantly to the prediction with p < .05.
Finally, write your simple regression equation. Be sure to name the explanatory and response variable when writing the equation.
If you were NOT justified in running the simple regression (that is assumptions for running a simple regression analysis were met) , please provide an explanation why not and support your conclusion using statistical details revealed during your investigation.
Write up your results as follows:
A simple regression was run to predict (response variable) from (Explanatory variable). Results show that the explanatory variables does not statistically significantly predict (response variable). F(df regression, df residual) = Significant F, p< , =, or > .05. The explanatory variable does/ does not contributes significantly to the prediction with p <, =, or > .05.
