For this project, my groupmate and I were tasked to collect and analyze a dataset. The analysis involves descriptive and inference statistics analysis. The topic we are working on is "Sleep and Its Relation with Academic Performance". The sample dataset is collected among the students from the School of Computing University Teknologi Malaysia. The dataset that we have collected involved is as below.
|
Variable |
Type of Variable |
Level of Measurement |
|
Age |
Quantitative |
Nominal |
|
Gendre |
Qualitative |
Nominal |
|
CGPA |
Quantitative |
Interval |
|
Nap Duration (During Weekdays) |
Quantitative |
Ratio |
|
Total Sleep Time (During Weekdays) |
Quantitative |
Ratio |
|
Nap Duration (During Weekends) |
Quantitative |
Ratio |
|
Total Sleep Time (During Weekends) |
Quantitative |
Ratio |
|
Sleep Satisfaction |
Qualitative |
Ordinal |
|
Sleep Consistency |
Qualitative |
Ordinal |
|
Caffeine Intake |
Quantitative |
Ratio |
|
Stimulant Pill Intake |
Quantitative |
Ratio |
|
Reason to Stay Up |
Qualitative |
Nominal |
|
Total Study Time per Day |
Quantitative |
Ratio |
Figure 1. Table of Data Collection
For the first part of the project (which involves descriptive analysis), we are looking at the pattern of the dataset. Referring to the data that was collected, it is clear that sleep and academic performance are related. In order to get a better grade in academics, we need to get enough sleep to make sure our brain can function to its maximum potential. From the data we collected, we can see that on average, students with good academic performance mostly have a total sleep time of 7.5, and most of them have a sleep time of 12.30 a.m. This total sleep time also includes the time taken for their nap throughout the day where they have 2.5 hours of nap time during the weekdays and the weekend.
For the second part of the project (which involves inference analysis), we are using a different dataset given by our lecturer. This dataset is also related to the students' academic performance. However, the variable involved is as below.
|
Name |
Variable |
Data type |
|
Gender |
Gender |
Nominal |
|
Race/Ethnic |
Race |
Nominal |
|
Parental Level of Education |
Parental Level of Education |
Ordinal |
|
Lunch Aid |
Lunch Aid |
Nominal |
|
Test Preparation Course |
Test Preparation Course |
Nominal |
|
Math Score |
Math Score |
Ratio |
|
Reading Score |
Reading Score |
Ratio |
|
Writing Score |
Writing Score |
Ratio |
Table 2: Variables in the data
From the analysis, it can be said that financial stability will not guarantee the students' academic performance, there is a strong positive linear relationship between reading and writing which shows that the performance of a certain subject might influence the performance of other subjects, and test preparation course are able to help the students to perform in their math test.
From both parts of the project, I'm able to gain a better understanding of the subject. Especially, in terms of implementation. It teaches me how to analyze the pattern of a dataset, and how to prove a claim on certain things. I realize that we can't make a claim or statement without a proper study of the topics where it can lead to a wrong statement and can result in a negative impact if someone uses the wrong statement especially to make a decision.
Last but not least, I would like to deliver my thanks to my groupmate for doing this project with me. Also to be forgotten our lecturer, Dr. Aryati Bakri. Thank you so much for the knowledge, and guidance you have given to us.