Regression is a statistical approach used for predicting real values like age, weight, salary, for example. In regression, we have a dependent variable which we want to predict using some independent variables. The goal of regression […]
Continue readingMore TagIntroduction: Ordinary Least Squares(OLS) is a commonly used technique for linear regression analysis. OLS makes certain assumptions about the data like linearity, no multicollinearity, no autocorrelation, homoscedasticity, normal distribution of errors. Violating these assumptions may reduce […]
Continue readingMore TagIn the previous part of the Introduction to Linear Regression, we discussed simple linear regression. Simple linear regression is a basic model with just two variables an independent variable x, and a dependent variable y based […]
Continue readingMore TagOnce we build our regression model, how can we measure the goodness of fit? We have various regression evaluation metrics to measure how well our model fits the data. In this article, we will see some […]
Continue readingMore TagBefore we venture into linear regression, let’s first try to understand what regression analysis is? What is Regression? Regression is a statistical approach used for predicting real values like the age, weight, salary, for example. In […]
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