Chapters List
Chapter 1: Introduction to Statistics
Chapter 2: Data Description
Chapter 3: Descriptive Statistics
Chapter 4: Probability, Random Variables and Probability Distributions
Chapter 5: Hypothesis Testing
Chapter 6: Chi-Square Test and Contingency Analysis
Chapter 7: Correlation and Regression
Chapter 8: Analysis of Variance (ANOVA)
Overview
Statistical data analysis is a procedure of performing various statistical operations. It is a kind of quantitative research that seeks to quantify the data, and typically, it applies some form of statistical analysis. Quantitative data basically involves descriptive data, such as survey data and observational data. This course introduced me to how to use statistical techniques as tools to analyze data, There are several useful methods for organizing data, starting from graphs or tables, a few more such as bar graphs, line charts, pie charts, and histogram charts to display data in the form. In this course, and finally in the end students should be able to apply some statistical models in analyzing data using R studio.
Course Reflection
This course taught me a lot about the importance and many of the methods for data organizing. Starting from graphs, tables, line charts, histogram charts, and pie charts. and at the end of the course, we have learned the coding language R using RStudio, a programming language for statistical computing and graphics. It is available in two formats: RStudio Desktop is a regular desktop application while RStudio Server runs on a remote server and allows accessing RStudio using a web browser.
We did 2 projects along the course. In our first project, we collected the data of UTM students, specifically computing students by conducting a survey that consists of the student's information, entertainment platforms used, how to subscribe, spend time, and opinion choices. Finally, the question of ever watching piracy.
In the second project, I feel it's a little more complex because here we learned several tests used to test statistical data, namely hypothesis testing, chi-square test, correlation test, regression test, and ANOVA test.