# Blog

This category will display all the post that i want to share under the blog navigation. This category will further have different categories based on different research or analysis software or different areas of research.

## Top 10 Books on Statistics

Exploring the realm of data and its interpretation has always been a fascinating journey. In an age, increasingly defined by exponential influx of data, it is not merely about collecting facts anymore. The underlying patterns and implications of data need to be understood. That is where Statistics swoop in, playing the role of truth-seekers and […]

## 10 Best Statistics Books for Data Science Enthusiasts

Data science books often serve as a vital repository of information for anyone working in the field of data science. Statistics, a fundamental component of these books, provide us with the ability to collect, define, evaluate, display, and eventually draw useful insights from data. A strong cognition of statistics is essential for a data scientist.

## Panel Data Analysis For Beginners

Researchers and analysts consistently endeavour to derive significant insights to inform decision-making and policy development in an era of abundant data. Panel data analysis is a robust methodology that offers insights into longitudinal patterns and reveals valuable information within intricate datasets. This article explores panel data analysis, explaining its fundamental nature and various applications. Definition

## Between, First Difference and Within Estimation

In the previous 3 articles, we discussed the theoretical and practical implications of the Pooled OLS, Fixed Effect, and Random Effects Models and the significance of dummy variables such as time or industry dummies. This article will look into other techniques that come under panel data analysis. The techniques are listed below: Download Example File

## Reshape data in R using Tidyverse and Reshape2

Reshape in R is when data is transformed from one form to another. The data can take a long form or wide form. In the wide form, each row represents a unique entity and each variable is spread across multiple columns. For example, consider a data set of a company, having stock prices for different