In econometric models, some variables can play a very important role in the explanation of an economic phenomenon. For instance, gender can play a crucial role in determining salary levels. However, quantifying gender isn’t straightforward because gender lacks a numerical nature. This tutorial aims to explain methods for incorporating such information into econometric models, employing […]

The data visualization is the important and powerful tool of R software. Using ggplot2 package, one can create multiple kind of bar charts, line and scatter plots etc. to display the world of data in certain figures. Previously, we have discussed basics of ggplot and creating a scatter plot in R using ggplot2, however this

Data visualization is one of the important and interesting aspect of any software. In the landscape of data analysis and interpretation, effective visualization is key to unlocking insights and communicating findings. Like other softwares, R can also visualize data in form of bar charts, Line Plots and other graphs etc. However, data visualization in R

What are outliers? Outliers are data points in a dataset that are different from the rest of the data. They can have immensely high or low values and can skew statistical analysis and models. Outliers can rise for various causes, including measurement errors, inaccurate data entry, or true abnormal events in the data. Finding and

When working with linear regression models, it’s essential to assess the model’s assumptions and diagnostic tests. These diagnostics help us in ensuring the reliability of our regression analysis. In simple terms, they ensure that the results are correct and unbiased. In this tutorial, we will only focus on three crucial diagnostic tests: normality of residuals,