1) Is/are there Independent Variable/s that can predict the Dependent Variable? Explain the result of the Regression Analysis (refer th the attach photos)2) Where there IVs found that are not predictors of the DV? What could be the reason? Base your answer on the p-value and Adjusted R Square. Predicted ValueStd. Predicted ValueStandard Error of Predicted ValueAdjusted Predicted ValueResidualResiduals StatisticsªMinimum Maximum Mean Std. Deviation N114.8627 249.3678 1.8923E233.26412 261.000 263.653 26Regression Standardized PredictedValue-2.2361.808.0007.23819.886 11.474114.8193 260.1165 1.8851E2-7.92405E1 61.01555Std. ResidualStud. ResidualDeleted ResidualStud. Deleted ResidualMahal. DistanceCook's DistanceCentered Leverage Valuea. Dependent Variable: Production Output1.7242.002-8.27001E1 82.291712.1556.933466277-2.239-2.288-2.546084.000003ScatterplotODependent Variable: Production OutputO00.00000.000010@.72087015Regression Standardized Residual1.923055077O34.23423 2633.94235 26959 261.029 2639.25609 261.083 261.879 26105 26075 26 Model Variables Entered Variables RemovedNumber of Staff12Idle Hoursa. Dependent Variable: Production OutputModel12a. Predictors: (Constant), Number of Staffb. Predictors: (Constant), Number of Staff, Idle Hoursc. Dependent Variable: Production OutputModel1ANOVACSum of Squares df Mean Square F Sig.20667.398 120667.398 13.856 | .001 a1491.55135797.217 2456464.615 2527662.543 22 RegressionResidual28802.073 23Total56464.615 25a. Predictors: (Constant), Number of Staffb. Predictors: (Constant), Number of Staff, Idle Hoursc. Dependent Variable: Production OutputModel1 (Constant)R R Square.605a.366.700⁰.490RegressionResidualTotal1-272.3821.424-330.6751.765Idle Hours-.139a. Dependent Variable: Production Output2 (Constant)Number of StaffModel1Number of Staff2Model SummaryAdjusted R Square Std. Error of the Estimate Durbin-Watson38.62060.340.44635.387341Beta In123Variables Entered/RemovedaMethodStepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100).Stepwise (Criteria: Probability-of-F-to-enter <= .050, Probability-of-F-to-remove >= .100).124.240.383116.480.379.059CoefficientsaUnstandardized Coefficients Standardized CoefficientsBStd. Error1.998.0022.932.066.002a. Dependent Variable: Production OutputIdle HoursMachine HoursLabor Hours-.381ª-.290a.116a-.221b-2.363 .027-1.873 .074.588.562-1.481 .1532 Machine HoursLabor Hours.167b.930 .363Number of Staffa. Predictors in the Model: (Constant),b. Predictors in the Model: (Constant), Number of Staff, Idle Hoursc. Dependent Variable: Production OutputCollinearity DiagnosticsaModel Dimension Eigenvalue Condition Index13831.2711252.2641.00032.7761.0006.64041.66811.045.000bBetaExcluded VariablesSig. Partial Correlation.001.00.00.01.99Correlations Collinearity Statisticst Sig. Zero-order Partial Part Tolerance VIF-2.192.038|.605 3.722.001-2.839.009.750 4.656.000-.381 -2.363.027-.442-.364.1221.787-.301.194Variance Proportions(Constant) Number of Staff Idle Hours.001.00.00.01.99.605 .605 .605Collinearity StatisticsTolerance VIF Minimum Tolerance.855 1.169.995 1.005.698 1.433.943 1.060.688 1.453.01.90.09.605 .697 .693-.095 -.442-.352.855.995.698.811.6471.000 1.000.855 1.169.855 1.169

Regression Analysis is a process of estimating the association between the dependent variable (or…

1) Is/are there Independent Variable/s that can predict the Dependent Variable? Explain the result of the Regression Analysis (refer th the attach photos) 2) Where there IVs found that are not predictors of the DV? What could be the reason? Base your answer on the p-value and Adjusted R Square.

1) Is/are there Independent Variable/s that can predict the Dependent Variable? Explain the result of the Regression Analysis (refer th the attach photos) 2) Where there IVs found that are not predictors of the DV? What could be the reason? Base your answer on the p-value and Adjusted R Square.

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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