The adjusted r-squared is helpful for multiple regression and corrects for erroneous regression, giving you a more accurate ...

In this short course we will cover how to analyze simple and multiple linear regression models. You will learn concepts in linear regression such as: 1) How to use the F-test to determine if your ...

Now that you've got a good sense of how to "speak" R, let's use it with linear regression to make distinctive predictions. The R system has three components: a scripting language, an interactive ...

Logistic regression is a powerful statistical method that is used to model the probability that a set of explanatory (independent or predictor) variables predict data in an outcome (dependent or ...

Multinomial logit (also termed multi-logit) models permit the analysis of the statistical relation between a categorical response variable and a set of explicative variables (called covahates or ...

Taken from Introduction to Econometrics from Stock and Watson, 2003, p. 215: Y=B0 + B1*ln(X) + u ~ A 1% change in X is associated with a change in Y of 0.01*B1 ln(Y)=B0 + B1*X + u ~ A change in X by ...

Have you ever found yourself staring at a spreadsheet, trying to make sense of all those numbers? Many face the challenge of transforming raw data into actionable insights, especially when it comes to ...

Proposals for multivariate analysis with ordinal variables based on analogies with product-moment formulae are criticized on the grounds that such analogies do not provide a basis for interpreting the ...