Chapter 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)
Course overview
This course is designed to introduce some statistical techniques as tools to analyze the data. In the beginning the students will be exposed with various forms of data. The data represented by the different types of variables are derived from different sources; daily and industrial activities. The analysis begins with the data representation visually. The course will also explore some methods of parameter estimation from different distributions. Further data analysis is conducted by introducing the hypothesis testing. Some models are employed to fit groups of data. At the end of course the students should be able to apply some statistical models in analyzing data using available software.
Lecturer: Dr. Sharin Hazlin Huspi
Reflection
In this course, I learned a lot about statistical techniques as a tool for analyzing data. There are several methods that are useful for managing datasets, as well as testing datasets. R programming is one of the applications used to process datasets. I learned several tests used to test statistical data, namely hypothesis testing, chi-square test, correlation test, regression test and ANOVA test. I did the test with my project 2 team. Thanks to Dr. Sharin for guiding us in this course