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3.003.832.503.001.752.442.082.001.574.004.502.001.002.253.253.003.75Single regression uses one predictor (independent, x) variable to predict a single criterion (dependent, y) variable, while in multiple regression two or more preditor variables are used to predict the criterion variable.Using the Data Analysis Regession tool compute a multiple regression using all the variables orgto trto predictAfter the analysis is complete go to cell B337for further instructions.
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13.174.003.002.753.674.502.333.082.001.864.804.504.002.672.382.003.505.0013.504.003.331.004.003.752.443.081.502.574.204.001.502.002.002.503.203.7514.253.504.334.004.004.003.002.753.503.864.404.003.001.673.563.003.905.0012.924.003.504.004.332.502.672.833.503.294.604.504.002.672.312.752.905.0013.754.003.673.504.003.252.782.673.003.574.404.003.002.003.192.753.604.7513.503.503.173.504.003.502.672.671.502.144.404.002.001.672.943.503.704.7513.423.503.002.004.004.003.113.173.002.144.004.003.502.002.382.503.504.5014.424.004.174.254.003.754.003.833.004.004.404.004.003.004.314.004.305.0013.583.503.003.253.673.253.562.833.503.713.604.004.003.003.632.504.004.7513.914.503.333.254.004.252.892.502.503.574.805.003.004.333.633.754.115.0014.423.002.833.004.004.002.333.082.503.713.805.004.504.003.063.254.305.0012.252.502.002.503.003.253.222.752.002.002.801.503.504.002.752.252.102.5014.004.003.334.004.672.754.112.673.503.714.804.505.003.333.443.754.204.5013.754.004.003.254.004.253.333.002.504.004.203.003.504.332.194.003.605.0013.253.003.002.753.333.751.442.081.503.294.404.004.503.672.693.253.003.5013.924.503.172.004.334.002.892.754.003.434.804.003.503.003.504.253.505.0013.083.003.503.253.674.002.442.171.502.834.604.003.503.002.562.753.502.7513.334.003.673.753.333.253.502.754.002.574.804.502.003.333.473.003.603.2513.834.004.004.004.004.003.893.584.002.864.204.003.003.003.944.004.105.0013.832.002.503.252.673.501.331.251.502.435.004.001.003.002.311.253.405.0013.675.003.335.005.003.502.891.751.503.574.205.005.003.003.252.504.205.0013.753.503.833.004.003.253.222.672.003.574.204.002.502.333.313.503.504.0014.003.503.504.254.004.753.002.081.503.434.805.005.003.672.692.753.603.5013.174.002.673.003.674.253.782.753.003.004.403.505.002.333.063.003.605.0013.672.503.503.254.333.252.112.252.003.144.805.003.502.332.563.253.504.5014.423.503.673.004.334.003.893.004.003.713.805.003.503.673.503.754.105.0013.084.504.004.004.334.503.112.331.503.005.004.003.502.003.444.002.904.5013.673.003.833.503.674.002.562.422.003.434.202.003.003.332.003.753.004.5014.673.504.004.003.334.503.673.003.003.574.204.503.503.003.753.754.205.0014.334.004.333.504.003.502.673.084.003.433.604.003.502.003.692.754.303.5014.004.003.674.004.333.502.782.332.503.144.805.003.001.674.003.254.203.5013.923.002.672.753.503.502.292.903.002.334.604.004.502.332.773.253.904.7513.753.503.673.755.004.003.563.333.003.434.404.503.003.332.753.003.704.0024.704.004.002.255.004.503.783.383.003.675.005.003.004.003.713.254.865.0022.642.501.832.253.672.002.781.582.002.713.804.503.503.331.442.502.891.2524.673.504.504.004.004.253.443.924.003.714.204.504.003.674.193.504.505.0023.922.503.834.253.673.254.222.332.503.294.805.003.502.332.633.003.604.2523.834.004.173.754.004.003.562.673.504.004.404.002.502.673.634.003.705.0023.753.503.833.504.003.253.562.753.004.144.604.003.502.673.633.254.004.7523.833.504.174.003.673.503.502.582.504.004.204.004.003.674.062.753.804.5024.333.503.834.004.334.254.223.084.003.144.604.504.002.333.384.004.205.0022.582.502.831.753.331.251.561.501.501.864.603.003.002.002.133.002.703.2522.923.002.832.003.002.752.561.922.503.434.204.002.003.002.814.252.904.2523.424.003.003.334.003.503.112.423.003.004.604.503.504.002.503.753.505.0023.733.504.004.004.003.003.002.752.503.144.004.003.003.003.634.003.784.0024.253.003.833.754.334.002.892.923.503.004.004.003.002.333.693.003.904.5024.703.003.504.005.003.754.333.674.503.864.805.003.504.334.313.504.755.0023.674.003.674.004.003.503.783.274.502.714.204.504.003.333.813.503.905.0024.173.003.833.504.333.003.222.504.003.574.202.504.004.334.192.753.705.0023.583.503.831.752.674.001.892.251.502.433.804.501.503.672.693.753.201.7522.673.002.672.753.673.503.002.332.003.144.802.004.002.332.562.752.802.0024.094.003.505.003.674.252.673.082.003.294.603.502.502.673.062.504.002.7522.924.003.504.253.004.253.003.083.002.864.604.503.002.673.503.753.702.5023.642.503.503.504.003.002.783.084.003.144.004.502.002.333.002.753.895.0024.174.003.502.754.674.002.782.924.003.714.604.503.003.003.333.003.805.00sexGender: 1=Male; 2=FemaleorgThe OrganizationiniInformationindiDirectioninfFeedbackprweWork EnvironmentpreqEquipment & SuppliesprwdWork DisorganizationprwcWorking ConditionsprwcoWorking Conditions OutcomeicadAdvancementicimImpacticimoImpact OutcomeicpaPay AdministrationicpyPay & BenefitssuImmediate SupervisortrTrainingcptwCompelling Place to WorkitlIntention to Leave7Recompute the multiple regression using the independent variables with a p-value <= .05 in the full regression model.
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