Annually, Forbes Magazine presents a summary of the ...
Psy 230 Lab Assignment 10Name ________________________Please use the attached output to answer the questions below. Please hand in one sheet with your answers (either hand written or typed) on the due date (next week in lab). You may print this one sheet and handwrite your answers on it or you may number and answer the questions on a separate page. 1. We want to assess whether net worth is associated with age.Specify:H0:H1:2. Use a few sentences to describe the relationship depicted by the scatter plot. Be sure to describe the form and direction of the relationship.3. Find the correlation coefficient to determine whether the relationship is significant (2-tailed test, alpha = .05). Indicate your decision (Retain or Reject Ho).4. Find the Regression Coefficients matrix and write the regression equation. Please note that the constant (a) is the y-intercept and Age (b) is the slope.5. Calculate (by hand) the estimated net worth of a wealthy 60-year-old (x).6. On the scatter plot “R Squared Linear = 0.524” is displayed. What does this mean specifically? (Hint: Remember we have discussed r2 as a measure of effect size. See G&W p. 523-525).7. I want to use this data to predict net worth of a 30-year old. What would your advice be? (See G&W p. 565)Annually, Forbes Magazine presents a summary of the richest Americans. Included is information on net worth of the individuals as well as their ages. We would like to determine whether net worth and age form a linear relationship. In addition, if these variables are significantly correlated, we would like to estimate the net worth of wealthy Americans (y), based on their age (x).Age and Net Worth of 36 of the Richest AmericansAgeNet Worth (in millions)81.001400.0075.00925.0076.001250.0066.00865.0077.00700.0058.00320.0059.00660.0048.00460.0064.00860.0076.00800.0057.00300.0072.00490.0064.00300.0062.00438.0081.00876.0075.00560.0076.001100.0071.00750.0066.00800.0043.00345.0061.00690.0073.001300.0045.00400.0050.00550.0047.00425.0057.00466.0082.00850.0052.00530.0052.00330.0064.00460.0066.00600.0066.00345.0050.00290.0054.00400.0046.00320.0056.00530.00Correlations[DataSet1] E:\regression data.savCorrelationsageNet Worth (in millions)agePearson Correlation1.724**Sig. (2-tailed).000N3636Net Worth (in millions)Pearson Correlation.724**1Sig. (2-tailed).000N3636GraphRegressionVariables Entered/RemovedbModelVariables EnteredVariables RemovedMethod1agea.Entera. All requested variables entered.b. Dependent Variable: Net Worth (in millions)Model SummaryModelRR SquareAdjusted R SquareStd. Error of the Estimate1.724a.524.510209.346a. Predictors: (Constant), ageCoefficientsaModelUnstandardized CoefficientsStandardized CoefficientstSig.BStd. ErrorBeta1Constant (a)-559.338197.438-2.833.008Age (b)18.8813.085.7246.121.000a. Dependent Variable: Net Worth (in millions) ................
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