# Panel Data

## 05 FebBeyond Linear Modeling using R (part-2)

Non-linear relationships are equally important to linear ones and in this post we will showcase an another basic approach in modeling exponential relationships between a predictor variable and a response variable. ...

## 03 FebBeyond Linear Modeling using R (part-1)

Non-linear relationships are equally important to linear ones and in this post we will showcase a basic approach in case of exponential relationship between a predictor variable and a response variable. ...

## 20 JanLinear Regression Modeling with R

Having discussed about the mathematical formulation and assumptions of the linear regression, its time to do some modeling using some specialised functions in R....

## 17 JanLinear Regression Summary Statistics

Summary statistics returned by the lm() object in R, highlight some important measurements used to decide the overall fitting performance of the linear model to our dataset....

## 06 DecHow to Draw Basic Descriptive Plots in R with ggplot2

Depending on the complexity of your task, the easiest way is to construct the panel dataset in Excel; and then transfer the data into an econometric software like Stata...

## 01 DecHow to Draw Basic Descriptive Plots in R

Depending on the complexity of your task, the easiest way is to construct the panel dataset in Excel; and then transfer the data into an econometric software like Stata...

## 02 NovHow to create a panel dataset

Depending on the complexity of your task, the easiest way is to construct the panel dataset in Excel; and then transfer the data into an econometric software like Stata...

## 04 OctPanel data analysis: fixed effects or random effects?

Use fixed-effects models, if you are only interested in analysing the impact of variables that change over time and not over entities, whereas use random-effects models when the variation across entities is assumed to be random and uncorrelated with the independent variable...