Question

When we are computing a simple linear regression line, there are certain conditions that must be met for this model to be valid. One of these conditions is the linearity condition.

Which of these answers best explains how we check to make sure that this condition is met?
a) See if there is a positive relationship between x and y.
b) See if there is a straight linear relationship between x and y.
c) See if there is a negative relationship between x and y.
d) See if we have at least 5 cases.

Answer 1

The linearity condition in simple linear regression is checked by observing if there is a straight linear relationship between the independent and dependent variables.

Step-by-step explanation:

The linearity condition in simple linear regression is checked by observing if there is a straight linear relationship between the independent variable (x) and the dependent variable (y). This means that the relationship between x and y can be represented by a straight line. To check for linearity, you can create a scatter plot of the data and examine if the points approximate a straight line. If they do, then the linearity condition is met.

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