34. In a manufacturing process a random sample of 9 bolts manufactured has a mean length of 3 inches with a variance of 0.09. What is the 90% confidence interval for the true mean length of the bolt?
A) 2.8355 to 3.1645 inches
B) 2.5065 to 3.4935 inches
C) 2.4420 to 3.5580 inches
D) 2.8140 to 3.8160 inches
E) 2.9442 to 3.0558 inches

Use the following to answer questions 7 - 9:

The following results were obtained from a simple regression analysis:

= 37.2895 - (1.2024)X
r2 = 0.6744 sb = 0.2934

7. For each unit change in X (independent variable), the estimated change in Y (dependent variable) is equal to:
A) -1.2024
B) 0.6774
C) 37.2895
D) 0.2934

8. When X (independent variable) is equal to zero, the estimated value of Y (dependent variable) is equal to:
A) -1.2024
B) 0.6774
C) 37.2895
D) 0.2934

9. ____________ is the proportion of the variation explained by the simple linear regression model:
A) -1.2024
B) 0.6774
C) 37.2895
D) 0.2934

Solution Summary

The solution contains explanation to certain multiple choice questions from Regression analysis

From a management policy perspective, which regression result is the most useful?
a regressionequation that passes the F-test.
a regressionequation whose explanatory variables all passed the t-test.
a regressionequation that has the highest R2.
a regressionequation that has the least n

When is a regressionequation used? What terms describe the fit of a regressionequation to the data? What is the importance of the coefficient of determination (r2)?
What are outliers? How do you identify outliers in your data? How do outliers impact your regressionequation?

Regression analysis was used to estimate the following linear trend equation:
St = 10.5 + 0.25t
Use this equation to forecast the value of the dependent variable (St) in time period of 10.
10.75
13
35.5
2.5

Find the equation of the regression line for the given data. Then construct a scatter plot of the data and draw the regression line. (The pair of variables have a significant correlation.) Then use the regressionequation to predict the value of y for each of the given x-values, if meaningful. The table below shows the heigh

I need to figure out the regressionequation, the value of Y when X is 7, the slope of the regressionequation, the Y-intercept of the regressionequation, the coefficient of correlation, and the coefficient of determination.

1. x= 1, 1, 5, 5
y= 1, 3, 2, 4
The regressionequation is y = 1.75 + 0.25x
2. What can you say about SSE, SSR, and the utility of the regressionequation for making predictions if
a. r^2 = 1
b. r ^2 = 0?