## Variable Manipulation and Reliability Check using Stata

In this session, we are going to learn how to manipulate, compute, and check the reliability of our variables. Variable manipulation and reliability check is an essential step of data analysis. In this article we will also learn how to…

## Data Cleaning and Editing using Stata

We’ll be learning about data cleaning and editing in this session. Data cleaning is a process that checks to see if your variables’ values are valid. We do data coding in order to make data (participants’ responses) more manageable, in…

## Multiple Regression Analysis Using Stata

We’re learning how to perform multiple regression analysis using stata this session. Regression is a prominent statistical technique for predicting a single outcome variable (continuous variable) from a set of independent factors (continuous as well as binary variables). For example,…

## How to Analyse Data using Stata: An Introduction

Data utilization has become a day-to-day business essential in today’s digital world, whether in public or private enterprises. Whatever sector or field you work in, you will always come across data, either indirectly as someone who relies on data-driven decisions…

## MANOVA(Multivariate Analysis of Variance) using R

What is MANOVA (Multivariate Analysis of Variance)? MANOVA is an extension to univariate ANOVA that includes at least two dependent variables to analyze differences between multiple groups in the independent variable. In contrast to ANOVA, where we compare individual group means, MANOVA compares the vectors…

## Analysis of Covariance (ANCOVA) using R

A general linear model (GLM) with at least one continuous and one categorical independent variable is known as ANCOVA (treatments). When the effect of treatments is essential and there is an additional continuous variable in the study, ANCOVA is effective.…

## Statistical Test of Significance

In experiment or observation data, the test of significance is used to account for sample variability. It’s usual to compare a group’s feature to a specified value or to compare two or more groups on the same characteristic (such as…

## One Sample T-test in R

A one-sample t-test is used to see if the mean of a population from which a sample was taken differs statistically from a hypothesised value. The null hypothesis in a t-test is that the population mean is equal to the…

## Pearson correlation in R

The Pearson correlation coefficient, sometimes known as Pearson’s r, is a statistic that determines how closely two variables are related. Its value ranges from -1 to +1, with 0 denoting no linear correlation, -1 denoting a perfect negative linear correlation,…

## Chi-Square test using R

A chi-square test is used to analyze nominal (sometimes known as categorical) data. It is pronounced kai and is frequently written as a χ2 test. It’s used to compare the observed frequencies in each sample’s response categories. The null hypothesis…