Info about PSDA Section
Name: LIM SHI KAI
Matric Number: A21EC0196
Section: 09
Lecture's Name: Dr. Rozilawati Binti Dollah @ Md. Zain
Welcome to my PSDA Page. You can get the info and reflection about my Project 2, which produce together with following friends:
1. Ng Keng Keat
2. Phang Seng Soon
3. Tan Chun Ming
Introduction to Project 2
We are getting the data from Kaggle as our dataset in this project. This dataset belongs to Eleanor Xu, an analyst from Coursera in San Francisco, California, the U.S. As we can see that this dataset is secondary data, it means that the data has been collected before. We get it online and use it again in our project.
This dataset talks about car specifications such as fuel type used, aspiration, number of doors and more. The total number of samples is 205 from multiple manufacturers in this world. So, we are choosing some specifications for testing purposes such as 2-sample hypothesis testing, correlation analysis, regression analysis, the goodness of fit test and chi-square test of independence.
Presentation Slide
R-Script File
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Download Project 2 R programming (1).R
Project 2 R programming (1).R Details
- Wednesday, 29 June 2022 [3.5KB]
Project Report
Dataset
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Download car_data.csv
car_data.csv Details
- Thursday, 30 June 2022 [22.1KB]
Presentation Video by 4 of a kind
My Reflection towards Project 2
RSS
Along with this long, long progress to complete this project, I gain a lot of knowledge about the vital part of this course, which is how to test the statistical value. I calculated the test statistics value via the data given and compared it with the value from the table.
Besides that, I also learned how to use RStudio to debug, run and show the output for the RScript file, which is a part of Project 2. The RStudio is helping me to get the correct data value based on the dataset. If the manual calculation and computer calculation are different, I will consider computer calculation as my answer because manually calculation sometimes will occur some humankind mistakes.
Then, I would like to thank my beloved teammates because they always present on time for the physical meeting at UTM Skudai Campus. Also, they always submit the task on time, which is done nicely. In addition, I also would like to thank my lecturer, yang cantik, for her guidance and advice for the whole project and the clear teaching of the entire relevant lesson.
I am happy I can do this project on time and with a wonderful report. Thanks again