Test interviews of two personnel evaluation techniques are available, the first requires a two-hour test interview while the second can be completed in less than an hour. The table below is the output of the regression analysis of the 15 individuals who took both tests:a.Using the method of least squares, the estimated regression will be?b.Suppose you must test the hypothesis at 5% significance level that versus using t-test. The value of J will be? Regression StatisticsMultiple R0.953935025R SquareMAdjusted R Square 0.903068342Standard Error3.134808415Observations15ANOVAdfssMSFSignificance F1291.5821291.582 131.4316573 3.60668E-08RegressionResidual13127.75139.827024Total141419.333CoefficientsStandard ErrorStatP-valueLower 95%Upper 95%Intercept11.665332785.2957132.202790.046260025 23.1060256-0.224639973Test 1 (X)0.7550167720.0658583.60668E-08 N

Test interviews of two personnel evaluation techniques are available, the first requires a two-hour test interview while the second can be completed in less than an hour. The table below is the output of the regression analysis of the 15 individuals who took both tests: a.Using the method of least squares, the estimated regression will be? b.Suppose you must test the hypothesis at 5% significance level that versus using t-test. The value of J will be?

Test interviews of two personnel evaluation techniques are available, the first requires a two-hour test interview while the second can be completed in less than an hour. The table below is the output of the regression analysis of the 15 individuals who took both tests: a.Using the method of least squares, the estimated regression will be? b.Suppose you must test the hypothesis at 5% significance level that versus using t-test. The value of J will be?

Functions and Change: A Modeling Approach to College Algebra (MindTap Course List)

6th Edition

ISBN:9781337111348

Author:Bruce Crauder, Benny Evans, Alan Noell

Publisher:Bruce Crauder, Benny Evans, Alan Noell

Chapter5: A Survey Of Other Common Functions

Section5.6: Higher-degree Polynomials And Rational Functions

Problem 5SBE

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Regression StatisticsMultiple R 0.890579188 Business Administration Program Final Assessment Semester Spring 2020Page 4R Square 0.793131289Adjusted R Square 0.7379663Standard Error 30.28395534Observations 20ANOVA df SS MS FRegression 4 52743.23074 13185.81 14.37743932Residual 15 13756.76926 917.1179509 Total 19 66500 Coefficients Standard Error t Stat P-valueIntercept 73.33291 62.25276 1.17799 0.25715X1 -0.13882 0.05353 -2.59326 0.02037X2 3.73984 0.95568 3.91328 0.00138X3 0.37644 0.16876 2.23061 0.04140X4 17.70752 15.57847 1.13667 0.27351 a. Write down the fitted multiple regression equation
Regression Statistics Multiple R 0.7980817 R Square 0.63693441 Adjusted R Square 0.63204134 Standard Error 198.511769 Observations 377 ANOVA df SS MS F Significance F Regression 5 25648149.7 5129629.95 130.170783 2.3368E-79 Residual 371 14619968.2 39406.9223 Total 376 40268117.9 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept -70.215668 83.5899819 -0.840001 0.40144881 -234.58524 94.1539002 -234.58524 94.1539002 LandArea 5.4726E-06 2.86E-05 0.19134566 0.84835946 -5.077E-05 6.1712E-05 -5.077E-05 6.1712E-05 Rooms -12.67723 10.5132648 -1.2058319 0.22865076 -33.350291 7.9958309 -33.350291 7.9958309 EquivArea 3.78736382 0.24640948 15.3702034 1.3343E-41 3.30282944 4.2718982 3.30282944 4.2718982 Condition 16.0812012 10.2954004 1.56197919…