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# Statistics

## Design Of Experiment: Completely Randomized Design

Introduction: In Design Of Experiment, experimentation and making inference are twin essential features of general scientific methodology. After setting up a statistical problem, we perform experiments for collecting information on the…

## Naive Bayes Classifier and Its Application Using R

Naive Bayes or Naive Bayes Classifier has its foundation pillar from the concept of Bayes theorem explained by the theory of probability. Probability is the chance of an event occurring. Probability can be related to our regular life and it…

## What Is Heteroscedasticity in Regression Analysis

We have some assumptions in our linear regression analysis. Some of them are really important. I am going to state them below at first. The regression model is linear in parameters. The mean of residuals is zero. Homoscedasticity of…

## Beginner to Advance level – Steps to Make Regression Model

Part 2 In this article, we will learn the steps to make the Regression Model. In the previous article of this series, we learned how to calculate the values of coefficients, a test of slope coefficients and Hypothesis. (more…)

## Beginner to Advance level: Steps to Make Regression Model

Part 1 You must have heard about Regression Models many times but you might not have heard about the techniques of solving or making a regression model step-wise. (more…)

## K Means Clustering In R

K Means Clustering is used when the input data is unlabeled and we have to find hidden patterns or clusters in the data set unsupervised learning comes into the picture. In clustering what we do is given a data set we look for similarities…

## Point Estimation

Point Estimation: So far we know that when the constants of a population (the parameters) are unknown, we estimate them by finding estimates based on the samples drawn from the same population. This method is called “estimation”. Now, since…

## How to Use Probability Distribution to Understand Your Data Critically

Is there any basis why probability distribution has to be talked about? What are its uses in understanding data? Can it show a sense of relevance according to one's needs? These are some of the questions that one has to ask in studying…

## Dispersion

Dispersion Dispersion means the variability, spread in the data. Average gives a single representative of the data however reliability of average is more if dispersion is less. Consider the following example, suppose there are three…

## Testing of Hypothesis and its application using R

Hypothesis Testing The primary objective of any statistical analysis is to gather information about some characteristics of the population. But usually only a part of the population (i.e. sample) can be accessed and hence one needs to make…