In project 2, we in the group of 4 were required to conduct an inference analysis by using a dataset. For our group, we chose student performance dataset to analysis whether the gender or test preparation course is affecting the performance of students in different education level.
First of all, I would like to thank our lecturer, Dr Sharin Hazlin Binti Huspi for giving us a chance to improve our analysis skills by exploring another tool which is R programming instead of Excel that we used in project 1. We really appreciate her effort in helping us to complete this project successfully. Besides, I also would like to thank my group members for their contributions and assistance in completing the project.
It is quite difficult for me to learn R programming because I haven't studied before and I need to spend extra time to study the slides and videos. But after I got some clues and idea about R code, I think it's worth learning to use R programming in our analysis. I learned the method to import the dataset, the technique to write the accurate code for different test such as hypothesis test, correlation test, regression test and chi-square test. We could obtain the result faster through R programming once we used to it. I will improve my skills and technique in R programming because it will be useful in the future.
Moreover, I think that team work is really importance throughout the completion of this project because without their assistance, I might not be able to accomplish the task. We always discuss and share our ideas together so that we could finished the project and submitted on time.
From our analysis, we learned that the students' performance are influenced by different aspects regardless of gender and test preparation course. I think the factors that affect the students' performance are their usual hard work, self-discipline, learning environment and the list go on.
Lastly, I hope that all of us could gain a brilliant performance in this course.