One of the most frequent used techniques in statistics is linear regression where we investigate the potential relationship between a variable of interest (often called the response variable but there are many other names in use) and a set of one of more variables (known as the independent variables or …

Why Python Python is a general purpose language that is easy and intuitive. This gives it a relatively flat learning curve, and it increases the speed at which you can write a program. In short, you need less time to code and you have more time to play around with …

So today, I will tell you about ANOVA(ANalysis Of VAriance ). ANOVA: is a parametric method appropriate for comparing the means for 2 or more independent or dependent groups. There are 3 types of ANOVA:

import numpy as num # Importing numpy import scipy as sci # Importing scipy

In this section we learn about control structures loops used in R. Control structures in R contains conditionals, loop statements like any other programming languages. Loops are very important and forms backbone to any programming languages.Before we get into the control structures in R, just type as below in Rstudio: …

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 …

Analyzing Twitter data Extract tweets and followers from the Twitter website with R and the twitteR package 1. With the tm package, clean text by removing punctuation, 2. numbers, hyperlinks and stop words, followed by stemming and stem completion 3. Build a term-document matrix 4. Analyse topics with the topicmodels package 5. …

Introduction Variable selection is an important aspect of model building which every analyst must learn. After all, it helps in building predictive models free from correlated variables, biases and unwanted noise. A lot of novice analysts assume that keeping all (or more) variables will result in the best model as …