- The data is collected from a class of 25 students who have reported their usage of social media apps for seven weeks.
- The data has 15 columns and 175 rows in total.
- The data is not cumulated for each student. Instead, we have considered each row as an individual data entry for better analysis.
- Student - Name of the Student
- Week - Week start and end date
- Whatsapp - Time spent on Whatsapp per week(hrs)
- Instagram - Time spent on Instagram per week(hrs)
- Snapchat - Time spent on Snapchat per week(hrs)
- Telegram - Time spent on Telegram per week(hrs)
- Facebook/Messenger - Time spent on Facebook/Messenger per week(hrs)
- BeReal - Time spent on BeReal per week(hrs)
- TikTok - Time spent on Tiktok per week(hrs)
- Wechat - Time spent on WeChat per week(hrs)
- Twitter - Time spent on Twitter per week(hrs)
- Linkedin - Time spent on LinkedIn per week(hrs)
- Messages - Time spent on Messages per week(hrs)
- Total Social Media Screen Time - Total time spent on social media per week(hrs)
- Social Media Addiction Level - Is the person addicted to social media?
Considering the 24-hour slots in a day, how many hour slots did the user open social media apps? This is for one day.
- As we have many outliers, we can analyse the data in two methods and check for any differences.
- We can consider two approaches - One considering all the Data, One considering only the columns WhatsApp, Instagram, Snapchat, LinkedIn, Total Social Media hours, and Addiction.
- Based on the given variables, can we classify if the student is addicted to Social Media or not?
- Based on the given variables, can we predict if the student is addicted to Social Media or not?
- We can predict if the student is addicted to social media based on the time they have spent on the individual social media apps.
- MVA_Class_Project_aa2569_Report.pdf file gives the brief report of the questions answered and the hypothesis results.
- Class_Survey.csv is the dataset considered for the analysis.
- The Class_Survey_aa2569.Rmd file contains the R code for the complete analysis performed, the flow of thought process, and inferences mentioned after each step.
- The Class_Survey_aa2569.html file gives the output of the Rmd file which includes the outputs of the file with visuals and inferences.