THE SYLLABUS
- 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)
REFLECTION
From my point of view, I can say that I was given the ability to deeply understand the chapters taught in class while conducting the Project 2 case study on the World Happiness Report 2019. At first, our group was reluctant in choosing the data set as we had no idea on how to conduct the project. But after a few discussions, we finally chose the World Happiness Report 2019 dataset which records countless variables contributing to the 156 countries happiness level. Those variables includes the country's rank, happiness score, GDP per capita, freedom to make life choices, healthy life expectancy, perceptions of corruption, generosity and social support.
For project 2, I had specifically contributed in the data set description and also the correlation test. I had spent most of my days, revising and understanding the procedures in conducting the correlation test, mostly referring to lecture notes and recordings, explainer videos on YouTube and also by surfing the internet. Indirectly, I have made preparations and revisions on the correlation test for the upcoming Final Examination. I can now conclude that the correlation test is held to identify if there is a linear relationship between two variables. Besides that, when conducting this project, I was also given the opportunity to use R Studio. The software was used to generate a scatter plot, get the correlation coefficient and also generate the summary of the correlation test. I find this software extremely useful to convert plenty of data into a scatter plot. All I had to do was write some codes and the output will then be executed.
When doing the correlation test, I can conclude that there was a positive correlation relationship between the variable Happiness Score and Freedom to make life choices. I happen to reject the null hypothesis as the test statistics is larger than 1.976. Hence, it shows that there are sufficient evidence to prove that the linear relationship between the two variables does exist.
Furthermore, when documenting our findings, I was able to understand more about Hypothesis Testing, Regression test, Chi-Square Test of Independence and also ANOVA by going through the explanation stated by my groupmates. Overall, I really enjoyed doing assignments and projects with Sakinah, known as Kina, and Nurarissa Dayana, known as Yana, as they both are patient in guiding me with the task.