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),

Homework Answers

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.

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