calculate multiple linear regression equation

#CALCULATE MULTIPLE LINEAR REGRESSION EQUATION SOFTWARE#

So if there are m Dummy variables then m-1 variables are used in the model. The solution of the Dummy Variable Trap is to drop one of the categorical variables. In the simple term, we can say that one variable can be predicted from the prediction of the other. The Dummy Variable Trap is a condition in which two or more are Highly Correlated. These variables consist of values such as 0 or 1 representing the presence and absence of categorical values. In the regression model, these values can be represented by Dummy Variables. Categorical Data refers to data values that represent categories-data values with the fixed and unordered number of values, for instance, gender(male/female). Using Categorical Data is a good method to include non-numeric data into the respective Regression Model. Lack of Multicollinearity: It is assumed that there is little or no multicollinearity in the data.Īs we know in the Multiple Regression Model we use a lot of categorical data.Multivariate normality: Multiple Regression assumes that the residuals are normally distributed.

Homoscedasticity: Constant variance of the errors should be maintained.Linearity: The relationship between dependent and independent variables should be linear.

#CALCULATE MULTIPLE LINEAR REGRESSION EQUATION SOFTWARE#

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Calculate multiple linear regression equation