HW 5 regression.xlsx - WC premium in thousands 7 7.3 7.8 8.2 8.5 9.2 9.9 10.6 11.4 12.2 12.9 13.5 14.5 15.6 16.8 17.3 18.2 19.8 20.5 21.5 23 24.1

HW 5 regression.xlsx - WC premium in thousands 7 7.3 7.8...

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Manufacturing Metropolitan Note: 7 380 0 0 WC premiu 7.3 410 0 0 Payroll in th 7.8 443 0 1 8.2 480 0 0 8.5 520 0 1 9.2 566 0 0 9.9 616 1 0 10.6 672 0 0 11.4 733 1 1 12.2 802 0 1 12.9 878 1 0 13.5 963 0 1 14.5 1057 1 1 15.6 1161 1 0 16.8 1277 1 1 17.3 1405 1 0 18.2 1548 1 0 19.8 1706 1 1 20.5 1882 1 1 21.5 2077 1 0 23 2293 1 1 24.1 2534 1 1 WC premium in thousands Payroll in thousands
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um in thousands: For example, WC premium for company A is $7,000 and for company B is $7,300. housands: For examaple, total payroll for company A is $380,000 and for company B is $410,000.
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(a) Interpret the relationship between the independent variable and the dependent variable in terms o Show Summary Output Below SUMMARY OUTPUT Regression Statistics Multiple R 0.987962726 R Square 0.976070348 Adjusted R Square 0.974873865 Standard Error 0.856603844 Observations 22 ANOVA df SS MS F Significance F Regression 1 598.597324377 598.5973 815.7832 1.0968295E-17 Residual 20 14.6754028955 0.73377 Total 21 613.272727273 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Intercept 4.976433162 0.36740057338 13.54498 1.55E-11 4.21004899575 5.74281733 X Variable 1 0.008209203 0.00028741779 28.56192 1.1E-17 0.0076096602 0.00880875 1. Run a simple regression using payroll in thousands to predict workers compensation premiums For every additional 100 in payroll you can expect a .8 increase in WC premium in thousands.
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