## Table of Contents

Links to all other posts in a structured way. Table of contents.

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# Blog

# Blog

## Table of Contents

## KNN imputation

## Recommendation systems

## Chi Square test of independence

## Chi-Square goodness of fit test

## Analysis of variance (Anova)

## Hypothesis test for population parameters

## All you ‘really’ need to know | Python Notebook | Advanced – Pandas

## Why are basics important?

## Time series EDA

and machine learning

Links to all other posts in a structured way. Table of contents.

Handling missing values in original mtcars data set by imputation using KNN algorithm.

Recommendation systems using associate mining rules

This post deals with Chi Square test of independence. Along with the R code, a contingency table, and mosaic plot are also presented.

A brief introduction to ChiSquare goodness of fit test using attendance data. Codes for Chi-sq plots along with post-hoc Cramers V are available.

Anova hypothesis test on unemployment data. Post hoc analysis and visualisations are presented.

Discussion on hypothesis testing. Introduction to z-test and t-test, Code for visualization of z-test and t-test.

It’s pretty obvious to summon the fact that you wouldn’t have clicked on this article if you have no understanding of the basics and intermediate level concepts of Python. You have? Then it is fair enough to go ahead with this article. You are confused with some basic stuffs, or perhaps forgot about it? IContinue reading All you ‘really’ need to know | Python Notebook | Advanced – Pandas

Explains why basics are important using a simple example.

Tutorial on Time Series EDA. Contains time plot, seasonal plots and correlogram plots (ACF) for in-time problem with reusable R code.