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# On the right is the summary of relevant statistics

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Unformatted text preview: redicted (y), the linear regression line. On the right is the summary of relevant statistics extracted and reformatted from the Excel report. Regression Statistics Labour Hours Std Error Labour Hours and Overhead Cost Regression Line \$120,000 \$100,000 \$80,000 \$60,000 \$40,000 t-Stat R Square 0.7322 Observations 12.0 df 11.0 Intercept a \$ 31,886.03 9,098.884 Slope b \$ 9.45 1.8076 Confidence 95.0% Critical Value df = 11 2.202 3.5044 0.0057 5.2290 0.0004 95.0% 2.202 P-value Y Predicted Y \$20,000 \$0 - 2. 2,000 4,000 6,000 X = Labour Hours 8,000 The RSquare (r2) indicated that a change in labour hours will explain approximately 73% of a change in the total overhead cost pool. This is higher than the benchmark of 30% explanatory power. The t‐Stat indicates whether or not the intercept a value is random or not and in this case 3.5044 > 2.202 at df = 11 and confidence level of 95%. The value of 2.202 is read from Exhibit 10‐6 in the list of critical values in Appendix. Bob can be confident 95/100 times that the unexplained portion...
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