Assumptions of Classical Linear Regression Model

SAS Analytics Linear Regression
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Transcript

In this video we will be discussing about the assumptions of classical linear regression model. So, the first assumption of classical linear regression model is the relationship between the dependent and independent variables is linear. So, there should be a linear relationship between the dependent and independent variables okay the second assumption is the errors are uncorrelated with the independent variables. So, the errors should not be correlated with in their terms should not be related to the independent variables the expected value of the residual terms should be zero this is the third assumption next the variance of their atoms should be constant this phenomena is called homoscedasticity. When we say the variance of their atoms are constant or the variance of the relative should be constant the phenomena is called the phenomena of homoscedasticity. Next, the lesser terms are Random or uncorrelated with respect to time that is the error term should not be correlated with respect to time that is error terms that a time period should not be correlated to their terms of t minus one and t minus one factor that is E t should not be correlated to t minus one should not be correlated to et minus two and so on.

And this concept is called the concept of non autocorrelation the error term should be normally distributed, this is another assumption and then the independent variables should be independent that is the independent variables should be less influenced by each other there should be minimum multicollinearity for the independent variables that is the independent variables should not get influenced by by other independent variables there should be less influence of the independent variables by other independent variables. So, there should be minimal multicollinearity for the independent variables Next, the independent variables should be non stochastic in nature non stochastic in nature means the independent variables should not follow any distributions So, we'll be ending this video over here in Our next video we will be discussing about the concept of multicollinearity and auto correlation for now. We'll end this video over here. See you all for the next video.

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