R

I developed this dashboard as as part of my studies at MIT Emerging Talent

In this post, I explore visualizing continuous variables by combining a histogram (showing the frequency of values within specific intervals) and a density plot (illustrating probability distribution)

In this post you will learn how to analyze multiple response questions in R.

In this post I explore different ways of reading data from multiple Excel sheets and converting them into individual data frames in R using lapply() and purrr::map() funciton.

This dashboard visualizes the economy & growth related indicators from the World Bank (WB)

In this post you will learn how to build a linear regression, interpret the result, test its assumptions, and use the regression equation for predictions.

In R working with survey weight is made possible using the `survey` package.

When dealing with numerical data, the most common way to graphically explore the patterns and relationships between variables and draw conclusion about how varaibles relate to one another is by plotting the data points using a scatterplot. A scatterplot uses dots/markers to represent values for two numeric variables where the position of each dot indicates values for an individual data point in the (x,y) coordinates.

In this post, I provide an overview of duplicated( ) function from base R and the distinct( ) function from dplyr package to detect and remove duplicates.

In this post, I try to cover the most common methods of transforming a skewed distribution into a normal distribution, and the foundational step that you must consider prior deciding which method to apply.