In previous article of this series we learned how to calculate values of coefficients, test of slope coefficients and Hypothesis.

You must have heard about Regression models many times but you might have not heard about the techniques of solving or making a regression model step-wise.

Why Logistic Regression? The linear Regression model assumes that the response variable Y is quantitative. But in many situations, the response variable is instead qualitative. For example eye colour is qualitative taking on values blue, brown or green. Often qualitative variables are referred to as categorical. Here we study approaches …

What is Logistic Regression ? Logistic Regression is a classification algorithm. It is used to predict a binary outcome (1 / 0, Yes / No, True / False) given a set of independent variables. To represent binary / categorical outcome, we use dummy variables. You can also think of logistic …

Hello guys, we have learnt about Linear Regression model in my previous article. Today, in this article we will get to learn the basics of Logistic Regression and some tricks to find the relation between the variables. Do you know what type of variable is used in logistic regression… Don’t …

R FUNCTIONS FOR REGRESSION ANALYSIS Here are some helpful R functions for regression analysis grouped by their goal. The name of package is in parentheses. Linear model Anova: Anova Tables for Linear and Generalized Linear Models (car) anova: Compute an analysis of variance table for one or more linear …