In Chapter 3, we examined data on the body weights and backpack weights of a group of eight randomly selected ninth-grade students at the Webb Schools. Some Minitab output from least-squares regression analysis for these data is shown

1. What conditions must be met for regression inference to be appropriate?

Short Answer

Expert verified

There are five conditions that must be met for the regression inferences to be appropriate.

Step by step solution

01

Given Information

Need to find the conditions that must be met for regression inference to be appropriate.

02

Explanation

There are five conditions that must be met for the regression inferences to be appropriate, that are:

Linear, independent, normal, equal variance, and random conditions.

Thus, we have to check the linearity of the relationship between variables, and then we have to check whether the variables are independent samples or not. Then, we have to check the normality of the residual whether they follow the normal distribution, and also check if they have equal variance. Also the sample we must have taken must be a random sample so that it represents the whole of the population.

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