In this project, I have explored individual variables' effect on survival rate. This, of course, is not something that extracts the maximum information from the dataset but shows how different R functions can be used to extract valuable information. I have extensively used dplyr and ggplot2 which was the main goal of this project.

Visualization of the correlation matrix.

This project aims at showing various attributes of registered general members of the `Programming Club, Dept. of Statistics, CU” in 2023. I have used ggplot2 for the visualizations.

Some methodologies for missing values imputation and R code

Discover various clustering techniques, such as hierarchical clustering, k-means clustering, as you delve into the process of grouping similar observations together to uncover patterns and structures in the data.

These are used to compute and draw a function as a continuous curve.

Only basic code on performing PCA in R.

Discussion on centroid, variance-covariance matrix, correlation matrix.

Discussed various applications of the t.test() function in R.

I've discussed on constructing a data frame using vectors, matrix to data frame conversion, selecting/sub-setting, re-leveling factorized values in data frame, joining two data frames in different manners.

Github repo - https://github.com/AhsanHimel/RepData_PeerAssessment1

I have discussed on different functions of the popular dplyr package for data manipulation in R.

I have discussed about for loop, while loop, loop using apply and repeat loop.

I have discussed about if, else, else if, switch, break and next.

I have discussed about the functions print(), nonquote(), cat(), paste(), format() and sprintf().

This is my first project on Statistical Inference. This is done after finishing the course from Coursera taught by Mine Çetinkaya-Rundel of Duke University. My research question here is, "Is political view of an individual USA citizen related to opinion towards the government expenses on improving education?"

This is my solution to the 3rd weeks lab exercise of the course - "Inferential Statistics by Mine Çetinkaya-Rundel" in Coursera.