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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 tStat 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 Pvalue 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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This note was uploaded on 01/23/2014 for the course TELFER adm3346 taught by Professor Collier during the Winter '12 term at University of Ottawa.
 Winter '12
 collier

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