Consider the following data on production volume (x) and total cost (y) for a manufacturing operation. Excel File: data14-29.xlsx Production Volume (units) Total Cost ($) 400 450 4000 5000 5400 550 600 5900 700 6400 750 7000 The estimated regression equation is ŷ = 1246.67 + 7.6x. Use a = 0.05 to test whether the production volume is significantly related to the total Complete the ANOVA table. Enter all values with nearest whole number, except the F test statistic (to 2 decimals) and the p-value (to 4 decimals). Use Table 1 of Appendix B. Source of Degrees of Sum Mean p-value Variation Freedom of Squares Square Regression 400 160000 4000 Error Total

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Consider the following data on production volume (x) and total cost (y) for a manufacturing operation.
Excel File: data14-29.xlsx
Production Volume (units)
Total Cost ($)
400
450
4000
5000
5400
550
600
5900
700
6400
750
7000
The estimated regression equation is ŷ = 1246.67 + 7.6x.
Use a = 0.05 to test whether the production volume is significantly related to the total
Complete the ANOVA table. Enter all values with nearest whole number, except the F test statistic (to 2 decimals) and the p-value (to 4 decimals).
Use Table 1 of Appendix B.
Source of
Degrees of
Sum
Mean
p-value
Variation
Freedom
of Squares
Square
Regression
400
160000
4000
Error
Total
Transcribed Image Text:Consider the following data on production volume (x) and total cost (y) for a manufacturing operation. Excel File: data14-29.xlsx Production Volume (units) Total Cost ($) 400 450 4000 5000 5400 550 600 5900 700 6400 750 7000 The estimated regression equation is ŷ = 1246.67 + 7.6x. Use a = 0.05 to test whether the production volume is significantly related to the total Complete the ANOVA table. Enter all values with nearest whole number, except the F test statistic (to 2 decimals) and the p-value (to 4 decimals). Use Table 1 of Appendix B. Source of Degrees of Sum Mean p-value Variation Freedom of Squares Square Regression 400 160000 4000 Error Total
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