OLS Assumptions

Ordinary Least Square, Assumptions about Regression analysis, OLS assumptions, heteroscedasticity, multicollinearity, autocorrelation

Homoscedasticity: Constant Variance of a Random Variable (2020)

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The term “Homoscedasticity” is the assumption about the random variable $u$ (error term) that its probability distribution remains the same for all observations of $X$ and in particular that the variance of each $u$ is the same for all values of the explanatory variables, i.e the variance of errors is …

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Checking Normality of Error Term

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Normality of Error Term In multiple linear regression models, the sum of squared residuals (SSR) is divided by $n-p$ (degrees of freedom, where $n$ is the total number of observations, and $p$ is the number of the parameter in the model) is a good estimate of the error variance. In …

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Regression Model Assumptions

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Linear Regression Model Assumptions The linear regression model (LRM) is based on certain statistical assumptions, some of which are related to the distribution of a random variable (error term) $u_i$, some are about the relationship between error term $u_i$ and the explanatory variables (Independent variables, $X$‘s) and some are related …

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