Aa Aa E 4. Regression model assumptions In simple linear regression analysis, yo

Question

Aa Aa E 4. Regression model assumptions In simple linear regression analysis, you make the assumption that the straight ne y S Bo B1x is the basis for the relationship between the variables x and y. The coefficient of determination r2 is a measure of how well the model fits the data. But even when the independent variable does a good job of explaining the variability of the dependent variable, the error terms in the regression model must satisfy certain assumptions. When the assumptions about E are seriously violated, the model is not useful for making inferences. The assumptions about the error term are: 1. The random errors E have a mean of zero. 2. The random errors Ei have the same variance. 3. The random errors Ei are independent. 4. The random errors are normally distributed. The following graph shows the probability distributions of E1 and E2, the error terms for x1 and x2, and two values of the independent variable x. 0.5 0.4 0.3 0.2 0.1 0.0 El, E2

Explanation / Answer

Based on graph assumptions 2 and 4 violated

Because random error has no same variance it is clear from graph

Shape of graph is rectangular not bell shape hence random error not normally distributed

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