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State the four conditions required for making regression inferences.

Short Answer

Expert verified

1. Independent observations

2. Equal standard deviations

3. Normal populations

4. Population regression line.

Step by step solution

01

Given information

The four conditions required for making regression inferences

02

Explanation

The following are the requirements for making regression inferences:

1. Independent observations: The responses to variable observations are unrelated to one another.

2. Equal standard deviations: The conditional standard deviations of the response variable are the same for all values of the predictor variable.

3. Normal populations: For each value of the predictor variable, the conditional distribution of the responder variable is a normal distribution.

4. Population regression line: There are constants β0and β1such that the conditional mean of the response variables is β0+β1xfor each value of x for the predictor variable.

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Most popular questions from this chapter

In Exexcises 14.98-14.108, use the technology of your choice to do the following tasks.
a. Decide whether your can reasonably apply the conditional mean and predicted value t-interval procedures to the data. If so, then also do parts (b) - (h).
b. Determine and interpret a point estimate for the conditional mean of the response variable corresponding to the specified value of the predictor variable.
c. Find and interpret a 95% confidence interval for the conditional mean of the response variable corresponding to the specified value of the predictor variable.
d. Determine and interpret the predicted value of the response variable corresponding to the specified value of the predictor variable.
e. Find and interpret a 95%prediction interval for the value of the response variable corresponding to the specified value of the predictor variable.
f. Compare and discuss the differences between the confidence interval that you obtained in part (c) and the prediction interval that you obfained in part (e).
14.102 Home Size and Value. The data from Exercise 14.38 for home size (in square feet) and assessed value (in thousands of dollars) for the same homes as in Exercise 14.101 are on the WeissStats site. Specified value of the predictor variable: 3000 sq. ft.

Explain why the predictor variable is useless as a predictor of the response variable if the slope of the population regression line is 0.

In Exercises 14.12-14.21, we repeat the data and provide the sample regression equations for Exercises 4.48 -4.57.

a. Determine the standand error of the estimate.

b. Construct a residual plot.

c. Construct a normal probability plot of the residuals.

we repeat the data and provide the sample regression equations for Exercises a.Determine the standard error of the estimate.

b. Construct a residual plot.

c. Construct a normal probability plot of the residuals.

Home Size and Value. The data from Exercise 14.38 for home size (in square feet) and assessed value (in thousands of dollars) for the same homes as in Exercise 14.73 are on the WeissStats site.

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