Consider the simple linear regression model: HARD1 = β0 + β1*SCORE + є, where є ~...
Consider the simple linear regression model: HARD1 =
β0 + β1*SCORE + є, where
є ~ N(0, σ).
Note: HARD1 is the Rockwell hardness of
1% copper alloys and SCORE is the abrasion loss
score.
Assume all regression model assumptions hold. The following
incomplete output was obtained from Excel. Consider also that the
mean of x is 81.467 and SXX is
81.733.
| SUMMARY OUTPUT | |||||
| Regression Statistics | |||||
| Multiple R | |||||
| R Square | |||||
| Adjusted R Square | 0.450969 | ||||
| Standard Error | |||||
| Observations | 15 | ||||
| ANOVA | |||||
| df | SS | MS | F | P-value | |
| Regression | 75.203 | 15.975 | 1.5E-03 | ||
| Residual | |||||
| Total | |||||
| Coefficients | Std Error | t Stat | P-value | ||
| Intercept | 166.656 | 19.559 | 8.521 | ||
| SCORE | 0.959 | ||||
What is a 90% confidence interval for the population slope?
Homework Answers
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Consider the simple linear regression model: HARD1 =
β0 + β1*SCORE + є, where
є ~...
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