Question

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),

Answer 1

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.