Question

# Regression: First, choose any metric variable as the dependent variable and then choose any three other...

1. Regression: First, choose any metric variable as the dependent variable and then choose any three other metric variables as independent variables. HOWEVER, this process must be repeated until you find a model that produces a significant F-calc (p-value (sig) <.05). Thus, you may have to sort through several combinations of dependent and independent variables before finding a combination that produces a significant F-calc. This is actually quite easy to do in SPSS using the drop down menus as shown in the powerpoint slides. Once you get a significant F-calc, then interpret the rest of the model (r2, adjusted r2, t-calcs, confidence intervals) and type out the model in the form of y = b0 + b1x1 + b2x2 + b3x3 putting in the actual estimates and names of the variables used. Use alpha = .05 for both the F-calc and t-calcs.   As a helpful starting hint, you may want to use the variables listed early in the data set to explain related variables listed later in the data set. You only need to report the significant model and not all of those you had to sort through to find it.
2.  Variables Entered/Removeda Model Variables Entered Variables Removed Method 1 DesiredListens, DesiredConvenience, DesiredFriendlyb . Enter a. Dependent Variable: ActualConvenience b. All requested variables entered.
 Model Summary Model R R Square Adjusted R Square Std. Error of the Estimate 1 .225a .051 .040 1.602 a. Predictors: (Constant), DesiredListens, DesiredConvenience, DesiredFriendly
 ANOVAa Model Sum of Squares df Mean Square F Sig. 1 Regression 36.887 3 12.296 4.789 .003b Residual 690.696 269 2.568 Total 727.582 272 a. Dependent Variable: ActualConvenience b. Predictors: (Constant), DesiredListens, DesiredConvenience, DesiredFriendly
 Coefficientsa Model Unstandardized Coefficients Standardized Coefficients t Sig. 95.0% Confidence Interval for B B Std. Error Beta Lower Bound Upper Bound 1 (Constant) 2.112 .726 2.909 .004 .682 3.542 DesiredConvenience .219 .104 .158 2.108 .036 .014 .424 DesiredFriendly .061 .125 .041 .492 .623 -.184 .307 DesiredListens .106 .150 .059 .703 .483 -.190 .402 a. Dependent Variable: ActualConvenience

REPORT: Your report will consist of one multiple regression output using three metric variables with interpretation (Part A),

There are three independent variables, which are DesiredConvenience, DesiredFriendly and DesiredListens.

Overall F score for the test is 4.789 with a p value of 0.003, which is significant at 0.05 level of significance. So, ANOVA result is significant

t scores corresponding to each independent variable DesiredConvenience, DesiredFriendly and DesiredListens are 2.108, 0.492 and 0.703 with respective p values 0.036, 0.623 and 0.483.

Only DesiredConvenience is a significant predictor of dependent variable based on the p value because its p value is less than 0.05 significance level.

Final model is

ActualConvenience = 2.112 + 0.219*(DesiredConvenience) + 0.061*(DesiredFriendly) + 0.106*(DesiredListens)

R square or coefficient of determination is 0.051 or 5.1%, which means that only 5.1% of variation in the dependent variable can be explained by the model.

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