R Final Project
Overview
The Student Social Media & Relationships dataset contains anonymized records of students’ social‐media behaviors and related life outcomes. It spans multiple countries and academic levels, focusing on key dimensions such as usage intensity, platform preferences, and relationship dynamics. Each row represents one student’s survey response, offering a cross‐sectional snapshot suitable for statistical analysis and machine‐learning applications.
Scope & Coverage
Population: Students aged 18–24 enrolled in high school, undergraduate, or graduate programs.
Geography: Multi‐country coverage (e.g., Bangladesh, India, USA, UK, Canada, Australia, Germany, Brazil, Japan, South Korea).
Column Descriptions
Student_ID A unique integer identifier assigned to each survey respondent to enable de-duplication and track individual records without revealing personal information.
Age The student’s age in completed years at the time of the survey, used to segment analysis by age group and control for developmental differences.
Gender The student’s self-reported gender, recorded as “Male” or “Female” to allow for demographic breakdowns in usage and outcome measures.
Academic_Level The highest level of education the respondent is currently enrolled in, with categories: “High School,” “Undergraduate,” or “Graduate,” facilitating stratified analyses by academic stage.
Country The country of residence where the student completed the survey, enabling cross-country comparisons of social media behaviors and impacts.
Avg_Daily_Usage_Hours The average number of hours per day the student spends on social media platforms, calculated from self-reported weekday and weekend usage estimates.
Most_Used_Platform The social media platform on which the student spends the most time (e.g., Instagram, Facebook, TikTok), used to examine platform-specific effects.
Affects_Academic_Performance A binary indicator (“Yes”/“No”) reflecting whether the student perceives their social media use as having a negative impact on their academic performance.
Sleep_Hours_Per_Night The respondent’s average nightly sleep duration in hours, provided to investigate correlations between screen time and sleep quality/quantity.
Mental_Health_Score A self-rated integer from 1 (poor) to 10 (excellent) indicating overall mental well-being, allowing assessment of potential associations with social media habits.
Relationship_Status The student’s current romantic relationship status, categorized as “Single,” “In Relationship,” or “Complicated,” to explore social media’s impact on interpersonal dynamics.
Conflicts_Over_Social_Media The number of arguments or disagreements the student reports having had with family, friends, or partners due to their social media use, serving as a proxy for social friction.
Addicted_Score A composite score from 1 (low addiction) to 10 (high addiction) based on a standardized survey scale (e.g., Bergen Social Media Addiction Scale), quantifying the degree of problematic usage.
library(tidyverse)## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.4 ✔ readr 2.1.5
## ✔ forcats 1.0.0 ✔ stringr 1.5.1
## ✔ ggplot2 3.5.2 ✔ tibble 3.2.1
## ✔ lubridate 1.9.4 ✔ tidyr 1.3.1
## ✔ purrr 1.0.4
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorsstudents <- read.csv("C:/Users/asroka/OneDrive - Adobe/Desktop/Anna/MTech/R/Final Project/Students Social Media Addiction.csv")head(students)## Student_ID Age Gender Academic_Level Country Avg_Daily_Usage_Hours
## 1 1 19 Female Undergraduate Bangladesh 5.2
## 2 2 22 Male Graduate India 2.1
## 3 3 20 Female Undergraduate USA 6.0
## 4 4 18 Male High School UK 3.0
## 5 5 21 Male Graduate Canada 4.5
## 6 6 19 Female Undergraduate Australia 7.2
## Most_Used_Platform Affects_Academic_Performance Sleep_Hours_Per_Night
## 1 Instagram Yes 6.5
## 2 Twitter No 7.5
## 3 TikTok Yes 5.0
## 4 YouTube No 7.0
## 5 Facebook Yes 6.0
## 6 Instagram Yes 4.5
## Mental_Health_Score Relationship_Status Conflicts_Over_Social_Media
## 1 6 In Relationship 3
## 2 8 Single 0
## 3 5 Complicated 4
## 4 7 Single 1
## 5 6 In Relationship 2
## 6 4 Complicated 5
## Addicted_Score perc_daily_usage perc_sleep
## 1 8 22% 27%
## 2 3 9% 31%
## 3 9 25% 21%
## 4 4 13% 29%
## 5 7 19% 25%
## 6 9 30% 19%ANALYSIS
Data Cleaning
Checking for missing values:
colSums(is.na(students))## Student_ID Age
## 0 0
## Gender Academic_Level
## 0 0
## Country Avg_Daily_Usage_Hours
## 0 0
## Most_Used_Platform Affects_Academic_Performance
## 0 0
## Sleep_Hours_Per_Night Mental_Health_Score
## 0 0
## Relationship_Status Conflicts_Over_Social_Media
## 0 0
## Addicted_Score perc_daily_usage
## 0 0
## perc_sleep
## 0We have no missing values in our dataset. Next step is checking the data types.
str(students)## 'data.frame': 705 obs. of 15 variables:
## $ Student_ID : int 1 2 3 4 5 6 7 8 9 10 ...
## $ Age : int 19 22 20 18 21 19 23 20 18 21 ...
## $ Gender : chr "Female" "Male" "Female" "Male" ...
## $ Academic_Level : chr "Undergraduate" "Graduate" "Undergraduate" "High School" ...
## $ Country : chr "Bangladesh" "India" "USA" "UK" ...
## $ Avg_Daily_Usage_Hours : num 5.2 2.1 6 3 4.5 7.2 1.5 5.8 4 3.3 ...
## $ Most_Used_Platform : chr "Instagram" "Twitter" "TikTok" "YouTube" ...
## $ Affects_Academic_Performance: chr "Yes" "No" "Yes" "No" ...
## $ Sleep_Hours_Per_Night : num 6.5 7.5 5 7 6 4.5 8 6 6.5 7 ...
## $ Mental_Health_Score : int 6 8 5 7 6 4 9 6 7 7 ...
## $ Relationship_Status : chr "In Relationship" "Single" "Complicated" "Single" ...
## $ Conflicts_Over_Social_Media : int 3 0 4 1 2 5 0 2 1 1 ...
## $ Addicted_Score : int 8 3 9 4 7 9 2 8 5 4 ...
## $ perc_daily_usage : chr "22%" "9%" "25%" "13%" ...
## $ perc_sleep : chr "27%" "31%" "21%" "29%" ...Let’s see if we have any duplications.
sum(duplicated(students))## [1] 0Our dataset does not have duplicated values.
Data manipulation
Let’s apply some filters to check how many males and females from the USA spend more than 6 hours a day on social media. 6 hours represents 25% of the whole day.
filter(students, Gender == "Male", Country == "USA", Avg_Daily_Usage_Hours >= 6)## [1] Student_ID Age
## [3] Gender Academic_Level
## [5] Country Avg_Daily_Usage_Hours
## [7] Most_Used_Platform Affects_Academic_Performance
## [9] Sleep_Hours_Per_Night Mental_Health_Score
## [11] Relationship_Status Conflicts_Over_Social_Media
## [13] Addicted_Score perc_daily_usage
## [15] perc_sleep
## <0 rows> (or 0-length row.names)Now, we will apply the same criteria for females.
filter(students, Gender == "Female", Country == "USA", Avg_Daily_Usage_Hours >= 6)## Student_ID Age Gender Academic_Level Country Avg_Daily_Usage_Hours
## 1 3 20 Female Undergraduate USA 6.0
## 2 221 19 Female Undergraduate USA 6.5
## 3 229 19 Female Undergraduate USA 7.0
## 4 237 19 Female Undergraduate USA 6.8
## 5 245 19 Female Undergraduate USA 6.9
## 6 253 19 Female Undergraduate USA 6.7
## 7 261 19 Female Undergraduate USA 6.6
## 8 269 19 Female Undergraduate USA 6.4
## 9 277 19 Female Undergraduate USA 6.6
## 10 285 19 Female Undergraduate USA 6.7
## 11 293 19 Female Undergraduate USA 6.8
## 12 301 19 Female Undergraduate USA 6.9
## 13 309 19 Female Undergraduate USA 7.0
## 14 317 19 Female Undergraduate USA 7.1
## 15 327 20 Female Undergraduate USA 6.8
## 16 337 19 Female Undergraduate USA 6.9
## 17 347 20 Female Undergraduate USA 7.0
## 18 357 19 Female Undergraduate USA 7.1
## 19 367 20 Female Undergraduate USA 7.2
## 20 377 19 Female Undergraduate USA 7.3
## 21 387 20 Female Undergraduate USA 7.4
## 22 397 19 Female Undergraduate USA 7.5
## 23 407 20 Female Undergraduate USA 7.6
## 24 417 19 Female Undergraduate USA 7.7
## 25 427 20 Female Undergraduate USA 7.8
## 26 437 19 Female Undergraduate USA 7.9
## 27 447 20 Female Undergraduate USA 8.0
## 28 457 19 Female Undergraduate USA 8.1
## 29 467 20 Female Undergraduate USA 8.2
## 30 477 19 Female Undergraduate USA 8.3
## 31 487 20 Female Undergraduate USA 8.4
## 32 497 19 Female Undergraduate USA 8.5
## Most_Used_Platform Affects_Academic_Performance Sleep_Hours_Per_Night
## 1 TikTok Yes 5.0
## 2 Instagram Yes 6.0
## 3 TikTok Yes 5.8
## 4 Instagram Yes 5.9
## 5 TikTok Yes 5.7
## 6 Instagram Yes 5.8
## 7 TikTok Yes 5.6
## 8 Instagram Yes 5.7
## 9 TikTok Yes 5.5
## 10 Instagram Yes 5.4
## 11 TikTok Yes 5.3
## 12 Instagram Yes 5.2
## 13 TikTok Yes 5.1
## 14 Instagram Yes 5.0
## 15 TikTok Yes 5.5
## 16 Instagram Yes 5.4
## 17 TikTok Yes 5.3
## 18 Instagram Yes 5.2
## 19 TikTok Yes 5.1
## 20 Instagram Yes 5.0
## 21 TikTok Yes 4.9
## 22 Instagram Yes 4.8
## 23 TikTok Yes 4.7
## 24 Instagram Yes 4.6
## 25 TikTok Yes 4.5
## 26 Instagram Yes 4.4
## 27 TikTok Yes 4.3
## 28 Instagram Yes 4.2
## 29 TikTok Yes 4.1
## 30 Instagram Yes 4.0
## 31 TikTok Yes 3.9
## 32 Instagram Yes 3.8
## Mental_Health_Score Relationship_Status Conflicts_Over_Social_Media
## 1 5 Complicated 4
## 2 5 Single 4
## 3 4 In Relationship 4
## 4 4 Single 4
## 5 4 In Relationship 4
## 6 4 Single 4
## 7 4 In Relationship 4
## 8 4 Single 4
## 9 4 In Relationship 4
## 10 4 Single 4
## 11 4 In Relationship 4
## 12 4 Single 4
## 13 4 In Relationship 4
## 14 4 Single 4
## 15 5 In Relationship 4
## 16 5 In Relationship 4
## 17 5 In Relationship 4
## 18 5 In Relationship 4
## 19 5 In Relationship 4
## 20 5 In Relationship 4
## 21 5 In Relationship 4
## 22 5 In Relationship 4
## 23 5 In Relationship 4
## 24 5 In Relationship 4
## 25 5 In Relationship 4
## 26 5 In Relationship 4
## 27 5 In Relationship 4
## 28 5 In Relationship 4
## 29 5 In Relationship 4
## 30 5 In Relationship 4
## 31 5 In Relationship 4
## 32 5 In Relationship 4
## Addicted_Score perc_daily_usage perc_sleep
## 1 9 25% 21%
## 2 9 27% 25%
## 3 9 29% 24%
## 4 9 28% 25%
## 5 9 29% 24%
## 6 9 28% 24%
## 7 9 28% 23%
## 8 9 27% 24%
## 9 9 28% 23%
## 10 9 28% 23%
## 11 9 28% 22%
## 12 9 29% 22%
## 13 9 29% 21%
## 14 9 30% 21%
## 15 9 28% 23%
## 16 9 29% 23%
## 17 9 29% 22%
## 18 9 30% 22%
## 19 9 30% 21%
## 20 9 30% 21%
## 21 9 31% 20%
## 22 9 31% 20%
## 23 9 32% 20%
## 24 9 32% 19%
## 25 9 33% 19%
## 26 9 33% 18%
## 27 9 33% 18%
## 28 9 34% 18%
## 29 9 34% 17%
## 30 9 35% 17%
## 31 9 35% 16%
## 32 9 35% 16%We have 32 females from the USA that spend more than 6 hours on their social media, whereas none of males. This is an interesting result and we will dive deeper into analysis later on.
We will now calculate percentage of average daily usage and percentage of sleep at night. To do so, we will use mutate function.
mutate(students, perc_daily_usage = round(Avg_Daily_Usage_Hours / 24*100,0), perc_sleep = round(Sleep_Hours_Per_Night / 24 *100,0)
)## Student_ID Age Gender Academic_Level Country Avg_Daily_Usage_Hours
## 1 1 19 Female Undergraduate Bangladesh 5.2
## 2 2 22 Male Graduate India 2.1
## 3 3 20 Female Undergraduate USA 6.0
## 4 4 18 Male High School UK 3.0
## 5 5 21 Male Graduate Canada 4.5
## 6 6 19 Female Undergraduate Australia 7.2
## 7 7 23 Male Graduate Germany 1.5
## 8 8 20 Female Undergraduate Brazil 5.8
## 9 9 18 Male High School Japan 4.0
## 10 10 21 Female Graduate South Korea 3.3
## 11 11 19 Male Undergraduate France 4.8
## 12 12 20 Female Undergraduate Spain 5.5
## 13 13 22 Male Graduate Italy 2.8
## 14 14 18 Female High School Mexico 6.5
## 15 15 21 Male Undergraduate Russia 3.7
## 16 16 20 Female Undergraduate China 4.2
## 17 17 24 Male Graduate Sweden 2.0
## 18 18 19 Female High School Norway 5.0
## 19 19 21 Male Undergraduate Denmark 3.5
## 20 20 20 Female Undergraduate Netherlands 4.7
## 21 21 18 Male High School Belgium 5.3
## 22 22 23 Female Graduate Switzerland 2.5
## 23 23 19 Male Undergraduate Austria 4.9
## 24 24 20 Female Undergraduate Portugal 5.7
## 25 25 22 Male Graduate Greece 3.2
## 26 26 19 Female High School Ireland 6.1
## 27 27 21 Male Undergraduate New Zealand 3.8
## 28 28 20 Female Undergraduate Singapore 4.4
## 29 29 24 Male Graduate Malaysia 2.2
## 30 30 19 Female High School Thailand 5.9
## 31 31 21 Male Undergraduate Vietnam 3.6
## 32 32 20 Female Undergraduate Philippines 4.8
## 33 33 18 Male High School Indonesia 5.4
## 34 34 23 Female Graduate Taiwan 2.6
## 35 35 19 Male Undergraduate Hong Kong 4.7
## 36 36 20 Female Undergraduate Turkey 5.6
## 37 37 22 Male Graduate Israel 3.1
## 38 38 19 Female High School UAE 6.2
## 39 39 21 Male Undergraduate Egypt 3.9
## 40 40 20 Female Undergraduate Morocco 4.5
## 41 41 24 Male Graduate South Africa 2.3
## 42 42 19 Female High School Nigeria 5.8
## 43 43 21 Male Undergraduate Kenya 3.7
## 44 44 20 Female Undergraduate Ghana 4.6
## 45 45 18 Male High School Argentina 5.5
## 46 46 23 Female Graduate Chile 2.7
## 47 47 19 Male Undergraduate Colombia 4.8
## 48 48 20 Female Undergraduate Peru 5.5
## 49 49 22 Male Graduate Venezuela 3.3
## 50 50 19 Female High School Ecuador 6.3
## 51 51 21 Male Undergraduate Uruguay 3.8
## 52 52 20 Female Undergraduate Paraguay 4.7
## 53 53 24 Male Graduate Bolivia 2.4
## 54 54 19 Female High School Costa Rica 5.7
## 55 55 21 Male Undergraduate Panama 3.6
## 56 56 20 Female Undergraduate Jamaica 4.9
## 57 57 18 Male High School Trinidad 5.6
## 58 58 23 Female Graduate Bahamas 2.8
## 59 59 19 Male Undergraduate Iceland 4.6
## 60 60 20 Female Undergraduate Finland 5.4
## 61 61 22 Male Graduate Poland 3.1
## 62 62 19 Female Undergraduate Romania 5.6
## 63 63 20 Male Undergraduate Hungary 4.2
## 64 64 18 Female High School Czech Republic 6.1
## 65 65 23 Male Graduate Slovakia 2.3
## 66 66 21 Female Undergraduate Croatia 4.8
## 67 67 20 Male Undergraduate Serbia 3.9
## 68 68 19 Female High School Slovenia 5.7
## 69 69 22 Male Graduate Bulgaria 2.8
## 70 70 20 Female Undergraduate Estonia 4.5
## 71 71 18 Male High School Latvia 5.4
## 72 72 21 Female Graduate Lithuania 3.2
## 73 73 19 Male Undergraduate Ukraine 4.9
## 74 74 20 Female Undergraduate Moldova 5.8
## 75 75 23 Male Graduate Belarus 2.5
## 76 76 21 Female Undergraduate Kazakhstan 4.6
## 77 77 19 Male High School Uzbekistan 5.5
## 78 78 22 Female Graduate Kyrgyzstan 2.9
## 79 79 20 Male Undergraduate Tajikistan 4.7
## 80 80 18 Female High School Armenia 5.9
## 81 81 21 Male Graduate Georgia 3.0
## 82 82 19 Female Undergraduate Azerbaijan 4.8
## 83 83 20 Male Undergraduate Cyprus 3.8
## 84 84 22 Female Graduate Malta 2.7
## 85 85 18 Male High School Luxembourg 5.6
## 86 86 21 Female Undergraduate Monaco 4.5
## 87 87 19 Male High School Andorra 5.3
## 88 88 23 Female Graduate San Marino 2.6
## 89 89 20 Male Undergraduate Vatican City 4.4
## 90 90 18 Female High School Liechtenstein 5.8
## 91 91 22 Male Graduate Montenegro 2.9
## 92 92 19 Female Undergraduate Albania 4.7
## 93 93 21 Male Undergraduate North Macedonia 3.7
## 94 94 20 Female High School Kosovo 5.5
## 95 95 23 Male Graduate Bosnia 2.4
## 96 96 19 Female Undergraduate Qatar 4.9
## 97 97 18 Male High School Kuwait 5.7
## 98 98 22 Female Graduate Bahrain 2.8
## 99 99 20 Male Undergraduate Oman 4.6
## 100 100 21 Female Undergraduate Jordan 5.4
## 101 101 19 Male High School Lebanon 5.8
## 102 102 23 Female Graduate Iraq 2.5
## 103 103 20 Male Undergraduate Yemen 4.7
## 104 104 18 Female High School Syria 5.6
## 105 105 22 Male Graduate Afghanistan 2.9
## 106 106 19 Female Undergraduate Pakistan 4.8
## 107 107 21 Male Undergraduate Nepal 3.8
## 108 108 20 Female High School Bhutan 5.5
## 109 109 23 Male Graduate Sri Lanka 2.6
## 110 110 19 Female Undergraduate Maldives 4.9
## 111 111 20 Male Undergraduate Bangladesh 6.1
## 112 112 21 Female Undergraduate India 5.8
## 113 113 19 Male Undergraduate Nepal 4.9
## 114 114 22 Female Graduate Pakistan 5.5
## 115 115 20 Male Undergraduate Sri Lanka 5.2
## 116 116 19 Female Undergraduate Maldives 4.8
## 117 117 21 Male Graduate Bangladesh 6.0
## 118 118 20 Female Undergraduate India 5.7
## 119 119 22 Male Graduate Nepal 4.7
## 120 120 19 Female Undergraduate Pakistan 5.4
## 121 121 20 Male Undergraduate Sri Lanka 5.9
## 122 122 21 Female Graduate Maldives 4.6
## 123 123 19 Male Undergraduate Bangladesh 5.3
## 124 124 22 Female Graduate India 5.8
## 125 125 20 Male Undergraduate Nepal 4.5
## 126 126 21 Female Graduate Pakistan 5.2
## 127 127 19 Male Undergraduate Sri Lanka 5.7
## 128 128 20 Female Undergraduate Maldives 4.4
## 129 129 22 Male Graduate Bangladesh 5.1
## 130 130 21 Female Graduate India 5.6
## 131 131 19 Male Undergraduate Nepal 4.3
## 132 132 20 Female Undergraduate Pakistan 5.0
## 133 133 22 Male Graduate Sri Lanka 5.5
## 134 134 21 Female Graduate Maldives 4.2
## 135 135 19 Male Undergraduate Bangladesh 4.9
## 136 136 20 Female Undergraduate India 5.4
## 137 137 22 Male Graduate Nepal 4.1
## 138 138 21 Female Graduate Pakistan 4.8
## 139 139 19 Male Undergraduate Sri Lanka 5.3
## 140 140 20 Female Undergraduate Maldives 4.0
## 141 141 22 Male Graduate Bangladesh 4.7
## 142 142 21 Female Graduate India 5.2
## 143 143 19 Male Undergraduate Nepal 3.9
## 144 144 20 Female Undergraduate Pakistan 4.6
## 145 145 22 Male Graduate Sri Lanka 5.1
## 146 146 21 Female Graduate Maldives 3.8
## 147 147 19 Male Undergraduate Bangladesh 4.5
## 148 148 20 Female Undergraduate India 5.0
## 149 149 22 Male Graduate Nepal 3.7
## 150 150 21 Female Graduate Pakistan 4.4
## 151 151 19 Male Undergraduate Sri Lanka 4.9
## 152 152 20 Female Undergraduate Maldives 3.6
## 153 153 22 Male Graduate Bangladesh 4.3
## 154 154 21 Female Graduate India 4.8
## 155 155 19 Male Undergraduate Nepal 3.5
## 156 156 20 Female Undergraduate Pakistan 4.2
## 157 157 22 Male Graduate Sri Lanka 4.7
## 158 158 21 Female Graduate Maldives 3.4
## 159 159 19 Male Undergraduate Bangladesh 4.1
## 160 160 20 Female Undergraduate India 4.6
## 161 161 19 Female Undergraduate Bangladesh 5.3
## 162 162 21 Male Graduate India 4.8
## 163 163 20 Female Undergraduate Nepal 5.5
## 164 164 22 Male Graduate Pakistan 4.7
## 165 165 19 Female Undergraduate Sri Lanka 5.1
## 166 166 21 Male Graduate Maldives 5.4
## 167 167 20 Female Undergraduate Bangladesh 4.9
## 168 168 22 Male Graduate India 5.2
## 169 169 19 Female Undergraduate Nepal 5.6
## 170 170 21 Male Graduate Pakistan 4.6
## 171 171 20 Female Undergraduate Sri Lanka 5.0
## 172 172 22 Male Graduate Maldives 5.3
## 173 173 19 Female Undergraduate Bangladesh 4.8
## 174 174 21 Male Graduate India 5.1
## 175 175 20 Female Undergraduate Nepal 5.7
## 176 176 22 Male Graduate Pakistan 4.5
## 177 177 19 Female Undergraduate Sri Lanka 4.9
## 178 178 21 Male Graduate Maldives 5.2
## 179 179 20 Female Undergraduate Bangladesh 4.7
## 180 180 22 Male Graduate India 5.0
## 181 181 19 Female Undergraduate Nepal 5.8
## 182 182 21 Male Graduate Pakistan 4.4
## 183 183 20 Female Undergraduate Sri Lanka 4.8
## 184 184 22 Male Graduate Maldives 5.1
## 185 185 19 Female Undergraduate Bangladesh 4.6
## 186 186 21 Male Graduate India 4.9
## 187 187 20 Female Undergraduate Nepal 5.9
## 188 188 22 Male Graduate Pakistan 4.3
## 189 189 19 Female Undergraduate Sri Lanka 4.7
## 190 190 21 Male Graduate Maldives 5.0
## 191 191 20 Female Undergraduate Bangladesh 4.5
## 192 192 22 Male Graduate India 4.8
## 193 193 19 Female Undergraduate Nepal 6.0
## 194 194 21 Male Graduate Pakistan 4.2
## 195 195 20 Female Undergraduate Sri Lanka 4.6
## 196 196 22 Male Graduate Maldives 4.9
## 197 197 19 Female Undergraduate Bangladesh 4.4
## 198 198 21 Male Graduate India 4.7
## 199 199 20 Female Undergraduate Nepal 6.1
## 200 200 22 Male Graduate Pakistan 4.1
## 201 201 19 Female Undergraduate Sri Lanka 4.5
## 202 202 21 Male Graduate Maldives 4.8
## 203 203 20 Female Undergraduate Bangladesh 4.3
## 204 204 22 Male Graduate India 4.6
## 205 205 19 Female Undergraduate Nepal 6.2
## 206 206 21 Male Graduate Pakistan 4.0
## 207 207 20 Female Undergraduate Sri Lanka 4.4
## 208 208 22 Male Graduate Maldives 4.7
## 209 209 19 Female Undergraduate Bangladesh 4.2
## 210 210 21 Male Graduate India 4.5
## 211 211 20 Female Undergraduate Nepal 6.3
## 212 212 22 Male Graduate Pakistan 3.9
## 213 213 19 Female Undergraduate Sri Lanka 4.3
## 214 214 21 Male Graduate Maldives 4.6
## 215 215 20 Female Undergraduate Bangladesh 4.1
## 216 216 22 Male Graduate India 4.4
## 217 217 19 Female Undergraduate Nepal 6.4
## 218 218 21 Male Graduate Pakistan 3.8
## 219 219 20 Female Undergraduate Sri Lanka 4.2
## 220 220 22 Male Graduate Maldives 4.5
## 221 221 19 Female Undergraduate USA 6.5
## 222 222 21 Male Graduate UK 5.8
## 223 223 20 Female Undergraduate Australia 4.5
## 224 224 22 Male Graduate Germany 4.2
## 225 225 19 Female Undergraduate Japan 3.8
## 226 226 21 Male Graduate Italy 5.5
## 227 227 20 Female Undergraduate South Korea 5.2
## 228 228 22 Male Graduate Russia 4.8
## 229 229 19 Female Undergraduate USA 7.0
## 230 230 21 Male Graduate UK 5.5
## 231 231 20 Female Undergraduate Australia 4.7
## 232 232 22 Male Graduate Germany 4.0
## 233 233 19 Female Undergraduate Japan 3.5
## 234 234 21 Male Graduate Italy 5.7
## 235 235 20 Female Undergraduate South Korea 5.0
## 236 236 22 Male Graduate Russia 4.5
## 237 237 19 Female Undergraduate USA 6.8
## 238 238 21 Male Graduate UK 5.6
## 239 239 20 Female Undergraduate Australia 4.6
## 240 240 22 Male Graduate Germany 4.1
## 241 241 19 Female Undergraduate Japan 3.7
## 242 242 21 Male Graduate Italy 5.4
## 243 243 20 Female Undergraduate South Korea 5.1
## 244 244 22 Male Graduate Russia 4.7
## 245 245 19 Female Undergraduate USA 6.9
## 246 246 21 Male Graduate UK 5.7
## 247 247 20 Female Undergraduate Australia 4.8
## 248 248 22 Male Graduate Germany 3.9
## 249 249 19 Female Undergraduate Japan 3.6
## 250 250 21 Male Graduate Italy 5.6
## 251 251 20 Female Undergraduate South Korea 4.9
## 252 252 22 Male Graduate Russia 4.6
## 253 253 19 Female Undergraduate USA 6.7
## 254 254 21 Male Graduate UK 5.4
## 255 255 20 Female Undergraduate Australia 4.4
## 256 256 22 Male Graduate Germany 4.0
## 257 257 19 Female Undergraduate Japan 3.4
## 258 258 21 Male Graduate Italy 5.3
## 259 259 20 Female Undergraduate South Korea 5.0
## 260 260 22 Male Graduate Russia 4.4
## 261 261 19 Female Undergraduate USA 6.6
## 262 262 21 Male Graduate UK 5.3
## 263 263 20 Female Undergraduate Australia 4.3
## 264 264 22 Male Graduate Germany 3.8
## 265 265 19 Female Undergraduate Japan 3.3
## 266 266 21 Male Graduate Italy 5.2
## 267 267 20 Female Undergraduate South Korea 4.8
## 268 268 22 Male Graduate Russia 4.3
## 269 269 19 Female Undergraduate USA 6.4
## 270 270 21 Male Graduate UK 5.2
## 271 271 20 Female Undergraduate Australia 4.5
## 272 272 22 Male Graduate Germany 3.7
## 273 273 19 Female Undergraduate Japan 3.2
## 274 274 21 Male Graduate Italy 5.4
## 275 275 20 Female Undergraduate South Korea 4.7
## 276 276 22 Male Graduate Russia 4.2
## 277 277 19 Female Undergraduate USA 6.6
## 278 278 21 Male Graduate UK 5.1
## 279 279 20 Female Undergraduate Australia 4.4
## 280 280 22 Male Graduate Germany 3.6
## 281 281 19 Female Undergraduate Japan 3.1
## 282 282 21 Male Graduate Italy 5.3
## 283 283 20 Female Undergraduate South Korea 4.6
## 284 284 22 Male Graduate Russia 4.1
## 285 285 19 Female Undergraduate USA 6.7
## 286 286 21 Male Graduate UK 5.0
## 287 287 20 Female Undergraduate Australia 4.3
## 288 288 22 Male Graduate Germany 3.5
## 289 289 19 Female Undergraduate Japan 3.0
## 290 290 21 Male Graduate Italy 5.2
## 291 291 20 Female Undergraduate South Korea 4.5
## 292 292 22 Male Graduate Russia 4.0
## 293 293 19 Female Undergraduate USA 6.8
## 294 294 21 Male Graduate UK 4.9
## 295 295 20 Female Undergraduate Australia 4.2
## 296 296 22 Male Graduate Germany 3.4
## 297 297 19 Female Undergraduate Japan 2.9
## 298 298 21 Male Graduate Italy 5.1
## 299 299 20 Female Undergraduate South Korea 4.4
## 300 300 22 Male Graduate Russia 3.9
## 301 301 19 Female Undergraduate USA 6.9
## 302 302 21 Male Graduate UK 4.8
## 303 303 20 Female Undergraduate Australia 4.1
## 304 304 22 Male Graduate Germany 3.3
## 305 305 19 Female Undergraduate Japan 2.8
## 306 306 21 Male Graduate Italy 5.0
## 307 307 20 Female Undergraduate South Korea 4.3
## 308 308 22 Male Graduate Russia 3.8
## 309 309 19 Female Undergraduate USA 7.0
## 310 310 21 Male Graduate UK 4.7
## 311 311 20 Female Undergraduate Australia 4.0
## 312 312 22 Male Graduate Germany 3.2
## 313 313 19 Female Undergraduate Japan 2.7
## 314 314 21 Male Graduate Italy 4.9
## 315 315 20 Female Undergraduate South Korea 4.2
## 316 316 22 Male Graduate Russia 3.7
## 317 317 19 Female Undergraduate USA 7.1
## 318 318 21 Male Graduate UK 4.6
## 319 319 20 Female Undergraduate Australia 3.9
## 320 320 22 Male Graduate Germany 3.1
## 321 321 19 Female Undergraduate Spain 5.2
## 322 322 21 Male Graduate Denmark 4.1
## 323 323 20 Female Undergraduate Ireland 5.0
## 324 324 22 Male Graduate India 5.8
## 325 325 19 Female Undergraduate Switzerland 4.0
## 326 326 21 Male Graduate Turkey 5.5
## 327 327 20 Female Undergraduate USA 6.8
## 328 328 22 Male Graduate Mexico 5.6
## 329 329 19 Female Undergraduate France 4.5
## 330 330 21 Male Graduate Canada 5.3
## 331 331 20 Female Undergraduate Spain 5.1
## 332 332 22 Male Graduate Denmark 3.9
## 333 333 19 Female Undergraduate Ireland 4.8
## 334 334 21 Male Graduate India 5.9
## 335 335 20 Female Undergraduate Switzerland 3.8
## 336 336 22 Male Graduate Turkey 5.4
## 337 337 19 Female Undergraduate USA 6.9
## 338 338 21 Male Graduate Mexico 5.7
## 339 339 20 Female Undergraduate France 4.4
## 340 340 22 Male Graduate Canada 5.2
## 341 341 19 Female Undergraduate Spain 5.0
## 342 342 21 Male Graduate Denmark 3.8
## 343 343 20 Female Undergraduate Ireland 4.7
## 344 344 22 Male Graduate India 6.0
## 345 345 19 Female Undergraduate Switzerland 3.7
## 346 346 21 Male Graduate Turkey 5.3
## 347 347 20 Female Undergraduate USA 7.0
## 348 348 22 Male Graduate Mexico 5.8
## 349 349 19 Female Undergraduate France 4.3
## 350 350 21 Male Graduate Canada 5.1
## 351 351 20 Female Undergraduate Spain 4.9
## 352 352 22 Male Graduate Denmark 3.7
## 353 353 19 Female Undergraduate Ireland 4.6
## 354 354 21 Male Graduate India 6.1
## 355 355 20 Female Undergraduate Switzerland 3.6
## 356 356 22 Male Graduate Turkey 5.2
## 357 357 19 Female Undergraduate USA 7.1
## 358 358 21 Male Graduate Mexico 5.9
## 359 359 20 Female Undergraduate France 4.2
## 360 360 22 Male Graduate Canada 5.0
## 361 361 19 Female Undergraduate Spain 4.8
## 362 362 21 Male Graduate Denmark 3.6
## 363 363 20 Female Undergraduate Ireland 4.5
## 364 364 22 Male Graduate India 6.2
## 365 365 19 Female Undergraduate Switzerland 3.5
## 366 366 21 Male Graduate Turkey 5.1
## 367 367 20 Female Undergraduate USA 7.2
## 368 368 22 Male Graduate Mexico 6.0
## 369 369 19 Female Undergraduate France 4.1
## 370 370 21 Male Graduate Canada 4.9
## 371 371 20 Female Undergraduate Spain 4.7
## 372 372 22 Male Graduate Denmark 3.5
## 373 373 19 Female Undergraduate Ireland 4.4
## 374 374 21 Male Graduate India 6.3
## 375 375 20 Female Undergraduate Switzerland 3.4
## 376 376 22 Male Graduate Turkey 5.0
## 377 377 19 Female Undergraduate USA 7.3
## 378 378 21 Male Graduate Mexico 6.1
## 379 379 20 Female Undergraduate France 4.0
## 380 380 22 Male Graduate Canada 4.8
## 381 381 19 Female Undergraduate Spain 4.6
## 382 382 21 Male Graduate Denmark 3.4
## 383 383 20 Female Undergraduate Ireland 4.3
## 384 384 22 Male Graduate India 6.4
## 385 385 19 Female Undergraduate Switzerland 3.3
## 386 386 21 Male Graduate Turkey 4.9
## 387 387 20 Female Undergraduate USA 7.4
## 388 388 22 Male Graduate Mexico 6.2
## 389 389 19 Female Undergraduate France 3.9
## 390 390 21 Male Graduate Canada 4.7
## 391 391 20 Female Undergraduate Spain 4.5
## 392 392 22 Male Graduate Denmark 3.3
## 393 393 19 Female Undergraduate Ireland 4.2
## 394 394 21 Male Graduate India 6.5
## 395 395 20 Female Undergraduate Switzerland 3.2
## 396 396 22 Male Graduate Turkey 4.8
## 397 397 19 Female Undergraduate USA 7.5
## 398 398 21 Male Graduate Mexico 6.3
## 399 399 20 Female Undergraduate France 3.8
## 400 400 22 Male Graduate Canada 4.6
## 401 401 19 Female Undergraduate Spain 4.4
## 402 402 21 Male Graduate Denmark 3.2
## 403 403 20 Female Undergraduate Ireland 4.1
## 404 404 22 Male Graduate India 6.6
## 405 405 19 Female Undergraduate Switzerland 3.1
## 406 406 21 Male Graduate Turkey 4.7
## 407 407 20 Female Undergraduate USA 7.6
## 408 408 22 Male Graduate Mexico 6.4
## 409 409 19 Female Undergraduate France 3.7
## 410 410 21 Male Graduate Canada 4.5
## 411 411 20 Female Undergraduate Spain 4.3
## 412 412 22 Male Graduate Denmark 3.1
## 413 413 19 Female Undergraduate Ireland 4.0
## 414 414 21 Male Graduate India 6.7
## 415 415 20 Female Undergraduate Switzerland 3.0
## 416 416 22 Male Graduate Turkey 4.6
## 417 417 19 Female Undergraduate USA 7.7
## 418 418 21 Male Graduate Mexico 6.5
## 419 419 20 Female Undergraduate France 3.6
## 420 420 22 Male Graduate Canada 4.4
## 421 421 19 Female Undergraduate Spain 4.2
## 422 422 21 Male Graduate Denmark 3.0
## 423 423 20 Female Undergraduate Ireland 3.9
## 424 424 22 Male Graduate India 6.8
## 425 425 19 Female Undergraduate Switzerland 2.9
## 426 426 21 Male Graduate Turkey 4.5
## 427 427 20 Female Undergraduate USA 7.8
## 428 428 22 Male Graduate Mexico 6.6
## 429 429 19 Female Undergraduate France 3.5
## 430 430 21 Male Graduate Canada 4.3
## 431 431 20 Female Undergraduate Spain 4.1
## 432 432 22 Male Graduate Denmark 2.9
## 433 433 19 Female Undergraduate Ireland 3.8
## 434 434 21 Male Graduate India 6.9
## 435 435 20 Female Undergraduate Switzerland 2.8
## 436 436 22 Male Graduate Turkey 4.4
## 437 437 19 Female Undergraduate USA 7.9
## 438 438 21 Male Graduate Mexico 6.7
## 439 439 20 Female Undergraduate France 3.4
## 440 440 22 Male Graduate Canada 4.2
## 441 441 19 Female Undergraduate Spain 4.0
## 442 442 21 Male Graduate Denmark 2.8
## 443 443 20 Female Undergraduate Ireland 3.7
## 444 444 22 Male Graduate India 7.0
## 445 445 19 Female Undergraduate Switzerland 2.7
## 446 446 21 Male Graduate Turkey 4.3
## 447 447 20 Female Undergraduate USA 8.0
## 448 448 22 Male Graduate Mexico 6.8
## 449 449 19 Female Undergraduate France 3.3
## 450 450 21 Male Graduate Canada 4.1
## 451 451 20 Female Undergraduate Spain 3.9
## 452 452 22 Male Graduate Denmark 2.7
## 453 453 19 Female Undergraduate Ireland 3.6
## 454 454 21 Male Graduate India 7.1
## 455 455 20 Female Undergraduate Switzerland 2.6
## 456 456 22 Male Graduate Turkey 4.2
## 457 457 19 Female Undergraduate USA 8.1
## 458 458 21 Male Graduate Mexico 6.9
## 459 459 20 Female Undergraduate France 3.2
## 460 460 22 Male Graduate Canada 4.0
## 461 461 19 Female Undergraduate Spain 3.8
## 462 462 21 Male Graduate Denmark 2.6
## 463 463 20 Female Undergraduate Ireland 3.5
## 464 464 22 Male Graduate India 7.2
## 465 465 19 Female Undergraduate Switzerland 2.5
## 466 466 21 Male Graduate Turkey 4.1
## 467 467 20 Female Undergraduate USA 8.2
## 468 468 22 Male Graduate Mexico 7.0
## 469 469 19 Female Undergraduate France 3.1
## 470 470 21 Male Graduate Canada 3.9
## 471 471 20 Female Undergraduate Spain 3.7
## 472 472 22 Male Graduate Denmark 2.5
## 473 473 19 Female Undergraduate Ireland 3.4
## 474 474 21 Male Graduate India 7.3
## 475 475 20 Female Undergraduate Switzerland 2.4
## 476 476 22 Male Graduate Turkey 4.0
## 477 477 19 Female Undergraduate USA 8.3
## 478 478 21 Male Graduate Mexico 7.1
## 479 479 20 Female Undergraduate France 3.0
## 480 480 22 Male Graduate Canada 3.8
## 481 481 19 Female Undergraduate Spain 3.6
## 482 482 21 Male Graduate Denmark 2.4
## 483 483 20 Female Undergraduate Ireland 3.3
## 484 484 22 Male Graduate India 7.4
## 485 485 19 Female Undergraduate Switzerland 2.3
## 486 486 21 Male Graduate Turkey 3.9
## 487 487 20 Female Undergraduate USA 8.4
## 488 488 22 Male Graduate Mexico 7.2
## 489 489 19 Female Undergraduate France 2.9
## 490 490 21 Male Graduate Canada 3.7
## 491 491 20 Female Undergraduate Spain 3.5
## 492 492 22 Male Graduate Denmark 2.3
## 493 493 19 Female Undergraduate Ireland 3.2
## 494 494 21 Male Graduate India 7.5
## 495 495 20 Female Undergraduate Switzerland 2.2
## 496 496 22 Male Graduate Turkey 3.8
## 497 497 19 Female Undergraduate USA 8.5
## 498 498 21 Male Graduate Mexico 7.3
## 499 499 20 Female Undergraduate France 2.8
## 500 500 22 Male Graduate Canada 3.6
## 501 501 19 Female Undergraduate Brazil 6.2
## 502 502 21 Male Graduate China 4.5
## 503 503 20 Female Undergraduate Netherlands 3.8
## 504 504 22 Male Graduate New Zealand 4.7
## 505 505 19 Female Undergraduate Singapore 5.1
## 506 506 21 Male Graduate Malaysia 5.5
## 507 507 20 Female Undergraduate UAE 6.5
## 508 508 22 Male Graduate Poland 4.2
## 509 509 19 Female Undergraduate India 6.8
## 510 510 21 Male Graduate Canada 4.8
## 511 511 20 Female Undergraduate Brazil 6.1
## 512 512 22 Male Graduate China 4.4
## 513 513 19 Female Undergraduate Netherlands 3.7
## 514 514 21 Male Graduate New Zealand 4.6
## 515 515 20 Female Undergraduate Singapore 5.2
## 516 516 22 Male Graduate Malaysia 5.6
## 517 517 19 Female Undergraduate UAE 6.6
## 518 518 21 Male Graduate Poland 4.1
## 519 519 20 Female Undergraduate India 6.9
## 520 520 22 Male Graduate Canada 4.7
## 521 521 19 Female Undergraduate Brazil 6.0
## 522 522 21 Male Graduate China 4.3
## 523 523 20 Female Undergraduate Netherlands 3.6
## 524 524 22 Male Graduate New Zealand 4.5
## 525 525 19 Female Undergraduate Singapore 5.3
## 526 526 21 Male Graduate Malaysia 5.7
## 527 527 20 Female Undergraduate UAE 6.7
## 528 528 22 Male Graduate Poland 4.0
## 529 529 19 Female Undergraduate India 7.0
## 530 530 21 Male Graduate Canada 4.6
## 531 531 20 Female Undergraduate Brazil 5.9
## 532 532 22 Male Graduate China 4.2
## 533 533 19 Female Undergraduate Netherlands 3.5
## 534 534 21 Male Graduate New Zealand 4.4
## 535 535 20 Female Undergraduate Singapore 5.4
## 536 536 22 Male Graduate Malaysia 5.8
## 537 537 19 Female Undergraduate UAE 6.8
## 538 538 21 Male Graduate Poland 3.9
## 539 539 20 Female Undergraduate India 7.1
## 540 540 22 Male Graduate Canada 4.5
## 541 541 19 Female Undergraduate Brazil 5.8
## 542 542 21 Male Graduate China 4.1
## 543 543 20 Female Undergraduate Netherlands 3.4
## 544 544 22 Male Graduate New Zealand 4.3
## 545 545 19 Female Undergraduate Singapore 5.5
## 546 546 21 Male Graduate Malaysia 5.9
## 547 547 20 Female Undergraduate UAE 6.9
## 548 548 22 Male Graduate Poland 3.8
## 549 549 19 Female Undergraduate India 7.2
## 550 550 21 Male Graduate Canada 4.4
## 551 551 20 Female Undergraduate Brazil 5.7
## 552 552 22 Male Graduate China 4.0
## 553 553 19 Female Undergraduate Netherlands 3.3
## 554 554 21 Male Graduate New Zealand 4.2
## 555 555 20 Female Undergraduate Singapore 5.6
## 556 556 22 Male Graduate Malaysia 6.0
## 557 557 19 Female Undergraduate UAE 7.0
## 558 558 21 Male Graduate Poland 3.7
## 559 559 20 Female Undergraduate India 7.3
## 560 560 22 Male Graduate Canada 4.3
## 561 561 19 Female Undergraduate Brazil 5.6
## 562 562 21 Male Graduate China 3.9
## 563 563 20 Female Undergraduate Netherlands 3.2
## 564 564 22 Male Graduate New Zealand 4.1
## 565 565 19 Female Undergraduate Singapore 5.7
## 566 566 21 Male Graduate Malaysia 6.1
## 567 567 20 Female Undergraduate UAE 7.1
## 568 568 22 Male Graduate Poland 3.6
## 569 569 19 Female Undergraduate India 7.4
## 570 570 21 Male Graduate Canada 4.2
## 571 571 20 Female Undergraduate Spain 6.1
## 572 572 23 Male Graduate Denmark 3.8
## 573 573 19 Female Undergraduate Ireland 5.5
## 574 574 22 Male Graduate India 7.2
## 575 575 21 Female Undergraduate Switzerland 4.2
## 576 576 24 Male Graduate Turkey 6.8
## 577 577 20 Female Undergraduate USA 5.9
## 578 578 22 Male Graduate Mexico 6.5
## 579 579 19 Female Undergraduate France 4.7
## 580 580 23 Male Graduate Canada 5.2
## 581 581 21 Female Undergraduate UK 6.3
## 582 582 24 Male Graduate Italy 4.9
## 583 583 20 Female Undergraduate Russia 6.7
## 584 584 22 Male Graduate China 5.8
## 585 585 19 Female Undergraduate Japan 4.5
## 586 586 23 Male Graduate Poland 6.4
## 587 587 21 Female Undergraduate Finland 4.1
## 588 588 24 Male Graduate Spain 6.6
## 589 589 20 Female Undergraduate Denmark 4.4
## 590 590 22 Male Graduate Ireland 5.7
## 591 591 19 Female Undergraduate India 7.0
## 592 592 23 Male Graduate Switzerland 4.3
## 593 593 21 Female Undergraduate Turkey 6.9
## 594 594 24 Male Graduate USA 5.6
## 595 595 20 Female Undergraduate Mexico 6.2
## 596 596 21 Male Undergraduate France 5.8
## 597 597 23 Female Graduate Canada 4.9
## 598 598 20 Male Undergraduate UK 6.4
## 599 599 22 Female Graduate Italy 5.1
## 600 600 19 Male Undergraduate Russia 6.7
## 601 601 24 Female Graduate China 5.5
## 602 602 21 Male Undergraduate Japan 4.3
## 603 603 23 Female Graduate Poland 6.2
## 604 604 20 Male Undergraduate Finland 4.5
## 605 605 22 Female Graduate Spain 6.3
## 606 606 19 Male Undergraduate Denmark 4.7
## 607 607 24 Female Graduate Ireland 5.9
## 608 608 21 Male Undergraduate India 7.1
## 609 609 23 Female Graduate Switzerland 4.4
## 610 610 20 Male Undergraduate Turkey 6.6
## 611 611 22 Female Graduate USA 5.4
## 612 612 19 Male Undergraduate Mexico 6.5
## 613 613 24 Female Graduate France 4.8
## 614 614 21 Male Undergraduate Canada 5.7
## 615 615 23 Female Graduate UK 6.1
## 616 616 20 Male Undergraduate Italy 4.6
## 617 617 22 Female Graduate Russia 6.8
## 618 618 19 Male Undergraduate China 5.6
## 619 619 24 Female Graduate Japan 4.2
## 620 620 21 Male Undergraduate Poland 6.3
## 621 621 23 Female Graduate Finland 4.4
## 622 622 20 Male Undergraduate Spain 6.5
## 623 623 22 Female Graduate Denmark 4.6
## 624 624 19 Male Undergraduate Ireland 5.8
## 625 625 24 Female Graduate India 7.0
## 626 626 21 Male Undergraduate Switzerland 4.5
## 627 627 23 Female Graduate Turkey 6.7
## 628 628 20 Male Undergraduate USA 5.5
## 629 629 22 Female Graduate Mexico 6.4
## 630 630 19 Male Undergraduate France 4.7
## 631 631 24 Female Graduate Canada 5.6
## 632 632 21 Male Undergraduate UK 6.2
## 633 633 23 Female Graduate Italy 4.8
## 634 634 20 Male Undergraduate Russia 6.9
## 635 635 22 Female Graduate China 5.7
## 636 636 19 Male Undergraduate Japan 4.4
## 637 637 24 Female Graduate Poland 6.1
## 638 638 21 Male Undergraduate Finland 4.3
## 639 639 23 Female Graduate Spain 6.4
## 640 640 20 Male Undergraduate Denmark 4.5
## 641 641 22 Female Graduate Ireland 5.9
## 642 642 19 Male Undergraduate India 7.2
## 643 643 24 Female Graduate Switzerland 4.6
## 644 644 21 Male Undergraduate Turkey 6.8
## 645 645 23 Female Graduate USA 5.3
## 646 646 22 Male Graduate Mexico 6.3
## 647 647 20 Female Undergraduate France 4.8
## 648 648 23 Male Graduate Canada 5.7
## 649 649 21 Female Undergraduate UK 6.2
## 650 650 24 Male Graduate Italy 4.7
## 651 651 19 Female Undergraduate Russia 6.8
## 652 652 22 Male Graduate China 5.6
## 653 653 20 Female Undergraduate Japan 4.3
## 654 654 23 Male Graduate Poland 6.2
## 655 655 21 Female Undergraduate Finland 4.4
## 656 656 24 Male Graduate Spain 6.5
## 657 657 19 Female Undergraduate Denmark 4.6
## 658 658 22 Male Graduate Ireland 5.8
## 659 659 20 Female Undergraduate India 7.1
## 660 660 23 Male Graduate Switzerland 4.5
## 661 661 21 Female Undergraduate Turkey 6.7
## 662 662 24 Male Graduate USA 5.4
## 663 663 19 Female Undergraduate Mexico 6.4
## 664 664 22 Male Graduate France 4.7
## 665 665 20 Female Undergraduate Canada 5.6
## 666 666 23 Male Graduate UK 6.3
## 667 667 21 Female Undergraduate Italy 4.8
## 668 668 24 Male Graduate Russia 6.9
## 669 669 19 Female Undergraduate China 5.7
## 670 670 22 Male Graduate Japan 4.4
## 671 671 20 Female Undergraduate Poland 6.1
## 672 672 23 Male Graduate Finland 4.3
## 673 673 21 Female Undergraduate Spain 6.4
## 674 674 24 Male Graduate Denmark 4.5
## 675 675 19 Female Undergraduate Ireland 5.9
## 676 676 22 Male Graduate India 7.2
## 677 677 20 Female Undergraduate Switzerland 4.6
## 678 678 23 Male Graduate Turkey 6.8
## 679 679 21 Female Undergraduate USA 5.3
## 680 680 24 Male Graduate Mexico 6.2
## 681 681 19 Female Undergraduate France 4.7
## 682 682 22 Male Graduate Canada 5.8
## 683 683 20 Female Undergraduate UK 6.1
## 684 684 23 Male Graduate Italy 4.8
## 685 685 21 Female Undergraduate Russia 6.7
## 686 686 24 Male Graduate China 5.5
## 687 687 19 Female Undergraduate Japan 4.2
## 688 688 22 Male Graduate Poland 6.3
## 689 689 20 Female Undergraduate Finland 4.4
## 690 690 23 Male Graduate Spain 6.5
## 691 691 21 Female Undergraduate Denmark 4.6
## 692 692 24 Male Graduate Ireland 5.9
## 693 693 19 Female Undergraduate India 7.0
## 694 694 22 Male Graduate Switzerland 4.5
## 695 695 20 Female Undergraduate Turkey 6.6
## 696 696 23 Male Graduate USA 5.5
## 697 697 21 Female Undergraduate Mexico 6.3
## 698 698 24 Male Graduate France 4.8
## 699 699 19 Female Undergraduate Canada 5.7
## 700 700 22 Male Graduate UK 6.2
## 701 701 20 Female Undergraduate Italy 4.7
## 702 702 23 Male Graduate Russia 6.8
## 703 703 21 Female Undergraduate China 5.6
## 704 704 24 Male Graduate Japan 4.3
## 705 705 19 Female Undergraduate Poland 6.2
## Most_Used_Platform Affects_Academic_Performance Sleep_Hours_Per_Night
## 1 Instagram Yes 6.5
## 2 Twitter No 7.5
## 3 TikTok Yes 5.0
## 4 YouTube No 7.0
## 5 Facebook Yes 6.0
## 6 Instagram Yes 4.5
## 7 LinkedIn No 8.0
## 8 Snapchat Yes 6.0
## 9 TikTok No 6.5
## 10 Instagram No 7.0
## 11 Snapchat Yes 6.2
## 12 TikTok Yes 5.8
## 13 LinkedIn No 7.2
## 14 Instagram Yes 5.5
## 15 YouTube No 6.8
## 16 TikTok Yes 6.0
## 17 LinkedIn No 7.8
## 18 Instagram Yes 5.7
## 19 Facebook No 6.7
## 20 Snapchat Yes 5.9
## 21 TikTok Yes 5.5
## 22 LinkedIn No 7.3
## 23 Instagram Yes 5.8
## 24 TikTok Yes 5.4
## 25 Facebook No 6.9
## 26 Instagram Yes 5.2
## 27 YouTube No 6.6
## 28 TikTok Yes 5.9
## 29 LinkedIn No 7.4
## 30 Instagram Yes 5.3
## 31 Facebook No 6.7
## 32 Snapchat Yes 5.7
## 33 TikTok Yes 5.4
## 34 LinkedIn No 7.2
## 35 Instagram Yes 5.8
## 36 TikTok Yes 5.5
## 37 Facebook No 6.8
## 38 Instagram Yes 5.1
## 39 YouTube No 6.5
## 40 TikTok Yes 5.8
## 41 LinkedIn No 7.3
## 42 Instagram Yes 5.4
## 43 Facebook No 6.6
## 44 Snapchat Yes 5.7
## 45 TikTok Yes 5.3
## 46 LinkedIn No 7.1
## 47 Instagram Yes 5.9
## 48 TikTok Yes 5.6
## 49 Facebook No 6.7
## 50 Instagram Yes 5.2
## 51 YouTube No 6.4
## 52 TikTok Yes 5.8
## 53 LinkedIn No 7.2
## 54 Instagram Yes 5.5
## 55 Facebook No 6.5
## 56 Snapchat Yes 5.6
## 57 TikTok Yes 5.2
## 58 LinkedIn No 7.0
## 59 Instagram Yes 5.9
## 60 TikTok Yes 5.7
## 61 Facebook No 7.1
## 62 Instagram Yes 5.6
## 63 TikTok Yes 6.0
## 64 Snapchat Yes 5.2
## 65 LinkedIn No 7.4
## 66 Instagram Yes 5.8
## 67 YouTube No 6.5
## 68 TikTok Yes 5.4
## 69 LinkedIn No 7.2
## 70 Instagram Yes 5.9
## 71 Snapchat Yes 5.5
## 72 Facebook No 6.8
## 73 TikTok Yes 5.7
## 74 Instagram Yes 5.3
## 75 LinkedIn No 7.3
## 76 Snapchat Yes 5.8
## 77 TikTok Yes 5.4
## 78 Facebook No 7.0
## 79 YouTube Yes 5.9
## 80 Instagram Yes 5.2
## 81 LinkedIn No 7.1
## 82 TikTok Yes 5.7
## 83 Facebook No 6.6
## 84 LinkedIn No 7.2
## 85 Snapchat Yes 5.3
## 86 Instagram Yes 5.8
## 87 TikTok Yes 5.5
## 88 LinkedIn No 7.3
## 89 YouTube Yes 6.0
## 90 Instagram Yes 5.2
## 91 Facebook No 7.0
## 92 TikTok Yes 5.8
## 93 Snapchat No 6.5
## 94 Instagram Yes 5.4
## 95 LinkedIn No 7.4
## 96 TikTok Yes 5.7
## 97 Snapchat Yes 5.3
## 98 LinkedIn No 7.1
## 99 Instagram Yes 5.9
## 100 TikTok Yes 5.5
## 101 YouTube Yes 5.2
## 102 LinkedIn No 7.3
## 103 Facebook Yes 5.8
## 104 Instagram Yes 5.4
## 105 LinkedIn No 7.0
## 106 TikTok Yes 5.7
## 107 YouTube No 6.6
## 108 Snapchat Yes 5.5
## 109 LinkedIn No 7.2
## 110 Instagram Yes 5.8
## 111 Instagram Yes 6.2
## 112 TikTok Yes 5.9
## 113 Facebook No 7.1
## 114 Instagram Yes 6.0
## 115 TikTok Yes 6.3
## 116 Instagram No 7.2
## 117 Facebook Yes 5.8
## 118 Instagram Yes 6.1
## 119 TikTok No 7.3
## 120 Instagram Yes 6.2
## 121 Facebook Yes 5.9
## 122 Instagram No 7.4
## 123 TikTok Yes 6.3
## 124 Instagram Yes 5.8
## 125 Facebook No 7.5
## 126 Instagram Yes 6.4
## 127 TikTok Yes 5.7
## 128 Instagram No 7.6
## 129 Facebook Yes 6.5
## 130 Instagram Yes 5.6
## 131 TikTok No 7.7
## 132 Instagram Yes 6.6
## 133 Facebook Yes 5.5
## 134 Instagram No 7.8
## 135 TikTok Yes 6.7
## 136 Instagram Yes 5.4
## 137 Facebook No 7.9
## 138 Instagram Yes 6.8
## 139 TikTok Yes 5.3
## 140 Instagram No 8.0
## 141 Facebook Yes 6.9
## 142 Instagram Yes 5.2
## 143 TikTok No 8.1
## 144 Instagram Yes 7.0
## 145 Facebook Yes 5.1
## 146 Instagram No 8.2
## 147 TikTok Yes 7.1
## 148 Instagram Yes 5.0
## 149 Facebook No 8.3
## 150 Instagram Yes 7.2
## 151 TikTok Yes 4.9
## 152 Instagram No 8.4
## 153 Facebook Yes 7.3
## 154 Instagram Yes 4.8
## 155 TikTok No 8.5
## 156 Instagram Yes 7.4
## 157 Facebook Yes 4.7
## 158 Instagram No 8.6
## 159 TikTok Yes 7.5
## 160 Instagram Yes 4.6
## 161 Instagram Yes 6.1
## 162 Facebook No 7.2
## 163 TikTok Yes 5.9
## 164 Instagram Yes 6.3
## 165 Facebook No 7.0
## 166 TikTok Yes 6.0
## 167 Instagram Yes 6.4
## 168 Facebook No 7.1
## 169 TikTok Yes 5.8
## 170 Instagram Yes 6.5
## 171 Facebook No 7.3
## 172 TikTok Yes 5.7
## 173 Instagram Yes 6.6
## 174 Facebook No 7.4
## 175 TikTok Yes 5.6
## 176 Instagram Yes 6.7
## 177 Facebook No 7.5
## 178 TikTok Yes 5.5
## 179 Instagram Yes 6.8
## 180 Facebook No 7.6
## 181 TikTok Yes 5.4
## 182 Instagram Yes 6.9
## 183 Facebook No 7.7
## 184 TikTok Yes 5.3
## 185 Instagram Yes 7.0
## 186 Facebook No 7.8
## 187 TikTok Yes 5.2
## 188 Instagram Yes 7.1
## 189 Facebook No 7.9
## 190 TikTok Yes 5.1
## 191 Instagram Yes 7.2
## 192 Facebook No 8.0
## 193 TikTok Yes 5.0
## 194 Instagram Yes 7.3
## 195 Facebook No 8.1
## 196 TikTok Yes 4.9
## 197 Instagram Yes 7.4
## 198 Facebook No 8.2
## 199 TikTok Yes 4.8
## 200 Instagram Yes 7.5
## 201 Facebook No 8.3
## 202 TikTok Yes 4.7
## 203 Instagram Yes 7.6
## 204 Facebook No 8.4
## 205 TikTok Yes 4.6
## 206 Instagram Yes 7.7
## 207 Facebook No 8.5
## 208 TikTok Yes 4.5
## 209 Instagram Yes 7.8
## 210 Facebook No 8.6
## 211 TikTok Yes 4.4
## 212 Instagram Yes 7.9
## 213 Facebook No 8.7
## 214 TikTok Yes 4.3
## 215 Instagram Yes 8.0
## 216 Facebook No 8.8
## 217 TikTok Yes 4.2
## 218 Instagram Yes 8.1
## 219 Facebook No 8.9
## 220 TikTok Yes 4.1
## 221 Instagram Yes 6.0
## 222 TikTok Yes 6.5
## 223 Instagram No 7.5
## 224 Facebook No 7.8
## 225 LINE No 7.9
## 226 Instagram Yes 6.8
## 227 KakaoTalk Yes 6.5
## 228 VKontakte No 7.2
## 229 TikTok Yes 5.8
## 230 Instagram Yes 6.7
## 231 Facebook No 7.4
## 232 Instagram No 7.9
## 233 LINE No 8.0
## 234 TikTok Yes 6.5
## 235 KakaoTalk Yes 6.8
## 236 VKontakte No 7.4
## 237 Instagram Yes 5.9
## 238 Facebook Yes 6.6
## 239 Instagram No 7.3
## 240 Facebook No 7.7
## 241 LINE No 7.8
## 242 Instagram Yes 6.7
## 243 KakaoTalk Yes 6.6
## 244 VKontakte No 7.3
## 245 TikTok Yes 5.7
## 246 Instagram Yes 6.4
## 247 Facebook No 7.2
## 248 Instagram No 7.8
## 249 LINE No 8.1
## 250 TikTok Yes 6.6
## 251 KakaoTalk Yes 6.9
## 252 VKontakte No 7.5
## 253 Instagram Yes 5.8
## 254 Facebook Yes 6.5
## 255 Instagram No 7.4
## 256 Facebook No 7.6
## 257 LINE No 8.2
## 258 Instagram Yes 6.8
## 259 KakaoTalk Yes 6.7
## 260 VKontakte No 7.6
## 261 TikTok Yes 5.6
## 262 Instagram Yes 6.3
## 263 Facebook No 7.5
## 264 Instagram No 7.7
## 265 LINE No 8.3
## 266 TikTok Yes 6.9
## 267 KakaoTalk Yes 7.0
## 268 VKontakte No 7.7
## 269 Instagram Yes 5.7
## 270 Facebook Yes 6.4
## 271 Instagram No 7.3
## 272 Facebook No 7.8
## 273 LINE No 8.4
## 274 Instagram Yes 6.7
## 275 KakaoTalk Yes 7.1
## 276 VKontakte No 7.8
## 277 TikTok Yes 5.5
## 278 Instagram Yes 6.5
## 279 Facebook No 7.4
## 280 Instagram No 7.9
## 281 LINE No 8.5
## 282 TikTok Yes 6.8
## 283 KakaoTalk Yes 7.2
## 284 VKontakte No 7.9
## 285 Instagram Yes 5.4
## 286 Facebook Yes 6.6
## 287 Instagram No 7.5
## 288 Facebook No 8.0
## 289 LINE No 8.6
## 290 Instagram Yes 6.9
## 291 KakaoTalk Yes 7.3
## 292 VKontakte No 8.0
## 293 TikTok Yes 5.3
## 294 Instagram Yes 6.7
## 295 Facebook No 7.6
## 296 Instagram No 8.1
## 297 LINE No 8.7
## 298 TikTok Yes 7.0
## 299 KakaoTalk Yes 7.4
## 300 VKontakte No 8.1
## 301 Instagram Yes 5.2
## 302 Facebook Yes 6.8
## 303 Instagram No 7.7
## 304 Facebook No 8.2
## 305 LINE No 8.8
## 306 Instagram Yes 7.1
## 307 KakaoTalk Yes 7.5
## 308 VKontakte No 8.2
## 309 TikTok Yes 5.1
## 310 Instagram Yes 6.9
## 311 Facebook No 7.8
## 312 Instagram No 8.3
## 313 LINE No 8.9
## 314 TikTok Yes 7.2
## 315 KakaoTalk Yes 7.6
## 316 VKontakte No 8.3
## 317 Instagram Yes 5.0
## 318 Facebook Yes 7.0
## 319 Instagram No 7.9
## 320 Facebook No 8.4
## 321 Instagram Yes 6.8
## 322 Facebook No 7.8
## 323 Instagram Yes 7.0
## 324 WhatsApp Yes 6.5
## 325 Instagram No 7.9
## 326 Instagram Yes 6.7
## 327 TikTok Yes 5.5
## 328 WhatsApp Yes 6.6
## 329 Instagram No 7.5
## 330 Instagram Yes 6.9
## 331 TikTok Yes 6.7
## 332 Facebook No 7.9
## 333 Instagram Yes 7.1
## 334 WhatsApp Yes 6.4
## 335 Instagram No 8.0
## 336 TikTok Yes 6.8
## 337 Instagram Yes 5.4
## 338 WhatsApp Yes 6.5
## 339 Instagram No 7.6
## 340 TikTok Yes 7.0
## 341 Instagram Yes 6.9
## 342 Facebook No 8.0
## 343 TikTok Yes 7.2
## 344 WhatsApp Yes 6.3
## 345 Instagram No 8.1
## 346 Instagram Yes 6.9
## 347 TikTok Yes 5.3
## 348 WhatsApp Yes 6.4
## 349 Instagram No 7.7
## 350 Instagram Yes 7.1
## 351 TikTok Yes 7.0
## 352 Facebook No 8.1
## 353 Instagram Yes 7.3
## 354 WhatsApp Yes 6.2
## 355 Instagram No 8.2
## 356 TikTok Yes 7.0
## 357 Instagram Yes 5.2
## 358 WhatsApp Yes 6.3
## 359 Instagram No 7.8
## 360 TikTok Yes 7.2
## 361 Instagram Yes 7.1
## 362 Facebook No 8.2
## 363 TikTok Yes 7.4
## 364 WhatsApp Yes 6.1
## 365 Instagram No 8.3
## 366 Instagram Yes 7.1
## 367 TikTok Yes 5.1
## 368 WhatsApp Yes 6.2
## 369 Instagram No 7.9
## 370 Instagram Yes 7.3
## 371 TikTok Yes 7.2
## 372 Facebook No 8.3
## 373 Instagram Yes 7.5
## 374 WhatsApp Yes 6.0
## 375 Instagram No 8.4
## 376 TikTok Yes 7.2
## 377 Instagram Yes 5.0
## 378 WhatsApp Yes 6.1
## 379 Instagram No 8.0
## 380 TikTok Yes 7.4
## 381 Instagram Yes 7.3
## 382 Facebook No 8.4
## 383 TikTok Yes 7.6
## 384 WhatsApp Yes 5.9
## 385 Instagram No 8.5
## 386 Instagram Yes 7.3
## 387 TikTok Yes 4.9
## 388 WhatsApp Yes 6.0
## 389 Instagram No 8.1
## 390 Instagram Yes 7.5
## 391 TikTok Yes 7.4
## 392 Facebook No 8.5
## 393 Instagram Yes 7.7
## 394 WhatsApp Yes 5.8
## 395 Instagram No 8.6
## 396 TikTok Yes 7.4
## 397 Instagram Yes 4.8
## 398 WhatsApp Yes 5.9
## 399 Instagram No 8.2
## 400 TikTok Yes 7.6
## 401 Instagram Yes 7.5
## 402 Facebook No 8.6
## 403 TikTok Yes 7.8
## 404 WhatsApp Yes 5.7
## 405 Instagram No 8.7
## 406 Instagram Yes 7.5
## 407 TikTok Yes 4.7
## 408 WhatsApp Yes 5.8
## 409 Instagram No 8.3
## 410 Instagram Yes 7.7
## 411 TikTok Yes 7.6
## 412 Facebook No 8.7
## 413 Instagram Yes 7.9
## 414 WhatsApp Yes 5.6
## 415 Instagram No 8.8
## 416 TikTok Yes 7.6
## 417 Instagram Yes 4.6
## 418 WhatsApp Yes 5.7
## 419 Instagram No 8.4
## 420 TikTok Yes 7.8
## 421 Instagram Yes 7.7
## 422 Facebook No 8.8
## 423 TikTok Yes 8.0
## 424 WhatsApp Yes 5.5
## 425 Instagram No 8.9
## 426 Instagram Yes 7.7
## 427 TikTok Yes 4.5
## 428 WhatsApp Yes 5.6
## 429 Instagram No 8.5
## 430 Instagram Yes 7.9
## 431 TikTok Yes 7.8
## 432 Facebook No 8.9
## 433 Instagram Yes 8.1
## 434 WhatsApp Yes 5.4
## 435 Instagram No 9.0
## 436 TikTok Yes 7.8
## 437 Instagram Yes 4.4
## 438 WhatsApp Yes 5.5
## 439 Instagram No 8.6
## 440 TikTok Yes 8.0
## 441 Instagram Yes 7.9
## 442 Facebook No 9.0
## 443 TikTok Yes 8.2
## 444 WhatsApp Yes 5.3
## 445 Instagram No 9.1
## 446 Instagram Yes 7.9
## 447 TikTok Yes 4.3
## 448 WhatsApp Yes 5.4
## 449 Instagram No 8.7
## 450 Instagram Yes 8.1
## 451 TikTok Yes 8.0
## 452 Facebook No 9.1
## 453 Instagram Yes 8.3
## 454 WhatsApp Yes 5.2
## 455 Instagram No 9.2
## 456 TikTok Yes 8.0
## 457 Instagram Yes 4.2
## 458 WhatsApp Yes 5.3
## 459 Instagram No 8.8
## 460 TikTok Yes 8.2
## 461 Instagram Yes 8.1
## 462 Facebook No 9.2
## 463 TikTok Yes 8.4
## 464 WhatsApp Yes 5.1
## 465 Instagram No 9.3
## 466 Instagram Yes 8.1
## 467 TikTok Yes 4.1
## 468 WhatsApp Yes 5.2
## 469 Instagram No 8.9
## 470 Instagram Yes 8.3
## 471 TikTok Yes 8.2
## 472 Facebook No 9.3
## 473 Instagram Yes 8.5
## 474 WhatsApp Yes 5.0
## 475 Instagram No 9.4
## 476 TikTok Yes 8.2
## 477 Instagram Yes 4.0
## 478 WhatsApp Yes 5.1
## 479 Instagram No 9.0
## 480 TikTok Yes 8.4
## 481 Instagram Yes 8.3
## 482 Facebook No 9.4
## 483 TikTok Yes 8.6
## 484 WhatsApp Yes 4.9
## 485 Instagram No 9.5
## 486 Instagram Yes 8.3
## 487 TikTok Yes 3.9
## 488 WhatsApp Yes 5.0
## 489 Instagram No 9.1
## 490 Instagram Yes 8.5
## 491 TikTok Yes 8.4
## 492 Facebook No 9.5
## 493 Instagram Yes 8.7
## 494 WhatsApp Yes 4.8
## 495 Instagram No 9.6
## 496 TikTok Yes 8.4
## 497 Instagram Yes 3.8
## 498 WhatsApp Yes 4.9
## 499 Instagram No 9.2
## 500 TikTok Yes 8.6
## 501 WhatsApp Yes 6.3
## 502 WeChat No 7.8
## 503 Instagram No 8.2
## 504 Instagram Yes 7.5
## 505 TikTok Yes 7.0
## 506 WhatsApp Yes 6.8
## 507 Instagram Yes 6.5
## 508 Facebook No 7.9
## 509 WhatsApp Yes 6.0
## 510 Instagram Yes 7.4
## 511 Instagram Yes 6.4
## 512 WeChat No 7.9
## 513 TikTok No 8.3
## 514 Instagram Yes 7.6
## 515 TikTok Yes 6.9
## 516 WhatsApp Yes 6.7
## 517 Instagram Yes 6.4
## 518 Facebook No 8.0
## 519 WhatsApp Yes 5.9
## 520 TikTok Yes 7.5
## 521 WhatsApp Yes 6.5
## 522 WeChat No 8.0
## 523 Instagram No 8.4
## 524 Facebook Yes 7.7
## 525 TikTok Yes 6.8
## 526 WhatsApp Yes 6.6
## 527 Instagram Yes 6.3
## 528 Facebook No 8.1
## 529 WhatsApp Yes 5.8
## 530 Instagram Yes 7.6
## 531 TikTok Yes 6.6
## 532 WeChat No 8.1
## 533 Instagram No 8.5
## 534 Facebook Yes 7.8
## 535 TikTok Yes 6.7
## 536 WhatsApp Yes 6.5
## 537 Instagram Yes 6.2
## 538 Facebook No 8.2
## 539 WhatsApp Yes 5.7
## 540 TikTok Yes 7.7
## 541 WhatsApp Yes 6.7
## 542 WeChat No 8.2
## 543 Instagram No 8.6
## 544 Instagram Yes 7.9
## 545 TikTok Yes 6.6
## 546 WhatsApp Yes 6.4
## 547 Instagram Yes 6.1
## 548 Facebook No 8.3
## 549 WhatsApp Yes 5.6
## 550 Instagram Yes 7.8
## 551 TikTok Yes 6.8
## 552 WeChat No 8.3
## 553 Instagram No 8.7
## 554 Facebook Yes 8.0
## 555 TikTok Yes 6.5
## 556 WhatsApp Yes 6.3
## 557 Instagram Yes 6.0
## 558 Facebook No 8.4
## 559 WhatsApp Yes 5.5
## 560 TikTok Yes 7.9
## 561 WhatsApp Yes 6.9
## 562 WeChat No 8.4
## 563 Instagram No 8.8
## 564 Instagram Yes 8.1
## 565 TikTok Yes 6.4
## 566 WhatsApp Yes 6.2
## 567 Instagram Yes 5.9
## 568 Facebook No 8.5
## 569 WhatsApp Yes 5.4
## 570 Instagram Yes 8.0
## 571 Instagram Yes 7.2
## 572 Twitter No 7.8
## 573 TikTok Yes 6.8
## 574 Facebook Yes 5.9
## 575 Instagram No 7.5
## 576 TikTok Yes 6.2
## 577 Instagram Yes 6.7
## 578 Facebook Yes 6.1
## 579 Twitter No 7.4
## 580 Instagram Yes 7.0
## 581 TikTok Yes 6.4
## 582 Facebook No 7.3
## 583 Instagram Yes 6.0
## 584 WeChat Yes 6.5
## 585 Twitter No 7.6
## 586 Facebook Yes 6.3
## 587 Instagram No 7.7
## 588 TikTok Yes 6.2
## 589 Instagram No 7.4
## 590 Twitter Yes 6.8
## 591 Instagram Yes 5.8
## 592 Facebook No 7.5
## 593 TikTok Yes 6.1
## 594 Instagram Yes 6.9
## 595 Facebook Yes 6.3
## 596 Instagram Yes 6.7
## 597 TikTok No 7.3
## 598 Facebook Yes 6.2
## 599 Twitter No 7.1
## 600 Instagram Yes 6.0
## 601 WeChat Yes 6.8
## 602 Twitter No 7.6
## 603 Instagram Yes 6.4
## 604 Facebook No 7.4
## 605 TikTok Yes 6.3
## 606 Instagram No 7.2
## 607 Twitter Yes 6.6
## 608 Facebook Yes 5.7
## 609 Instagram No 7.4
## 610 TikTok Yes 6.2
## 611 Instagram Yes 6.9
## 612 Facebook Yes 6.1
## 613 Twitter No 7.3
## 614 Instagram Yes 6.7
## 615 TikTok Yes 6.4
## 616 Facebook No 7.2
## 617 Instagram Yes 5.9
## 618 WeChat Yes 6.8
## 619 Twitter No 7.5
## 620 TikTok Yes 6.3
## 621 Instagram No 7.4
## 622 Facebook Yes 6.2
## 623 Twitter No 7.3
## 624 Instagram Yes 6.6
## 625 TikTok Yes 5.8
## 626 Facebook No 7.3
## 627 Instagram Yes 6.1
## 628 Twitter Yes 6.8
## 629 Facebook Yes 6.2
## 630 Instagram No 7.2
## 631 TikTok Yes 6.7
## 632 Facebook Yes 6.3
## 633 Twitter No 7.1
## 634 Instagram Yes 5.9
## 635 WeChat Yes 6.7
## 636 Twitter No 7.4
## 637 TikTok Yes 6.4
## 638 Instagram No 7.5
## 639 Facebook Yes 6.2
## 640 Twitter No 7.3
## 641 Instagram Yes 6.5
## 642 TikTok Yes 5.7
## 643 Facebook No 7.2
## 644 Instagram Yes 6.0
## 645 Twitter Yes 6.8
## 646 Facebook Yes 6.2
## 647 Instagram No 7.1
## 648 TikTok Yes 6.6
## 649 Twitter Yes 6.3
## 650 Facebook No 7.2
## 651 Instagram Yes 5.9
## 652 WeChat Yes 6.7
## 653 Twitter No 7.5
## 654 TikTok Yes 6.3
## 655 Instagram No 7.4
## 656 Facebook Yes 6.1
## 657 Twitter No 7.3
## 658 Instagram Yes 6.6
## 659 TikTok Yes 5.8
## 660 Facebook No 7.3
## 661 Instagram Yes 6.0
## 662 Twitter Yes 6.8
## 663 TikTok Yes 6.2
## 664 Facebook No 7.2
## 665 Instagram Yes 6.7
## 666 Twitter Yes 6.2
## 667 TikTok No 7.1
## 668 Instagram Yes 5.9
## 669 WeChat Yes 6.7
## 670 Twitter No 7.4
## 671 Facebook Yes 6.4
## 672 Instagram No 7.5
## 673 TikTok Yes 6.2
## 674 Twitter No 7.3
## 675 Instagram Yes 6.5
## 676 Facebook Yes 5.7
## 677 TikTok No 7.2
## 678 Instagram Yes 6.0
## 679 Twitter Yes 6.8
## 680 Facebook Yes 6.3
## 681 Instagram No 7.2
## 682 TikTok Yes 6.6
## 683 Twitter Yes 6.4
## 684 Facebook No 7.1
## 685 Instagram Yes 6.0
## 686 WeChat Yes 6.8
## 687 Twitter No 7.5
## 688 TikTok Yes 6.2
## 689 Instagram No 7.4
## 690 Facebook Yes 6.1
## 691 Twitter No 7.3
## 692 Instagram Yes 6.5
## 693 TikTok Yes 5.8
## 694 Facebook No 7.3
## 695 Instagram Yes 6.1
## 696 Twitter Yes 6.7
## 697 TikTok Yes 6.2
## 698 Facebook No 7.1
## 699 Instagram Yes 6.6
## 700 Twitter Yes 6.3
## 701 TikTok No 7.2
## 702 Instagram Yes 5.9
## 703 WeChat Yes 6.7
## 704 Twitter No 7.5
## 705 Facebook Yes 6.3
## Mental_Health_Score Relationship_Status Conflicts_Over_Social_Media
## 1 6 In Relationship 3
## 2 8 Single 0
## 3 5 Complicated 4
## 4 7 Single 1
## 5 6 In Relationship 2
## 6 4 Complicated 5
## 7 9 Single 0
## 8 6 In Relationship 2
## 9 7 Single 1
## 10 7 In Relationship 1
## 11 5 Complicated 3
## 12 6 In Relationship 2
## 13 8 Single 1
## 14 5 Single 4
## 15 7 In Relationship 2
## 16 6 Complicated 3
## 17 8 Single 0
## 18 5 In Relationship 3
## 19 7 Single 1
## 20 6 Complicated 3
## 21 5 Single 4
## 22 8 In Relationship 1
## 23 6 Complicated 3
## 24 5 Single 4
## 25 7 In Relationship 2
## 26 5 Complicated 4
## 27 7 Single 1
## 28 6 In Relationship 3
## 29 8 Single 0
## 30 5 Complicated 4
## 31 7 Single 1
## 32 6 In Relationship 3
## 33 5 Complicated 4
## 34 8 Single 1
## 35 6 In Relationship 3
## 36 5 Complicated 4
## 37 7 Single 1
## 38 5 In Relationship 4
## 39 7 Complicated 2
## 40 6 Single 3
## 41 8 In Relationship 1
## 42 5 Complicated 4
## 43 7 Single 2
## 44 6 In Relationship 3
## 45 5 Single 4
## 46 8 Complicated 1
## 47 6 In Relationship 3
## 48 5 Single 4
## 49 7 In Relationship 2
## 50 5 Complicated 4
## 51 7 Single 2
## 52 6 In Relationship 3
## 53 8 Complicated 1
## 54 5 Single 4
## 55 7 In Relationship 2
## 56 6 Complicated 3
## 57 5 Single 4
## 58 8 In Relationship 1
## 59 6 Complicated 3
## 60 5 Single 4
## 61 7 Single 1
## 62 5 In Relationship 3
## 63 6 Complicated 3
## 64 4 Single 4
## 65 8 In Relationship 1
## 66 6 Single 3
## 67 7 Complicated 2
## 68 5 In Relationship 4
## 69 8 Single 1
## 70 6 Complicated 3
## 71 5 Single 4
## 72 7 In Relationship 2
## 73 6 Complicated 3
## 74 5 Single 4
## 75 8 In Relationship 1
## 76 6 Single 3
## 77 5 Complicated 4
## 78 7 In Relationship 2
## 79 6 Single 3
## 80 5 Complicated 4
## 81 8 In Relationship 1
## 82 6 Single 3
## 83 7 Complicated 2
## 84 8 In Relationship 1
## 85 5 Single 4
## 86 6 Complicated 3
## 87 5 In Relationship 4
## 88 8 Single 1
## 89 6 Complicated 3
## 90 5 Single 4
## 91 7 In Relationship 2
## 92 6 Complicated 3
## 93 7 Single 2
## 94 5 In Relationship 4
## 95 8 Complicated 1
## 96 6 Single 3
## 97 5 In Relationship 4
## 98 8 Complicated 1
## 99 6 Single 3
## 100 5 In Relationship 4
## 101 5 Complicated 4
## 102 8 Single 1
## 103 6 In Relationship 3
## 104 5 Single 4
## 105 7 Complicated 2
## 106 6 In Relationship 3
## 107 7 Single 2
## 108 5 Complicated 4
## 109 8 In Relationship 1
## 110 6 Single 3
## 111 5 Single 4
## 112 6 In Relationship 3
## 113 7 Single 2
## 114 5 Single 4
## 115 6 In Relationship 3
## 116 8 Single 2
## 117 5 In Relationship 4
## 118 6 Single 3
## 119 7 Single 2
## 120 5 In Relationship 4
## 121 6 Single 3
## 122 8 In Relationship 2
## 123 5 Single 4
## 124 6 In Relationship 3
## 125 7 Single 2
## 126 5 In Relationship 4
## 127 6 Single 3
## 128 8 In Relationship 2
## 129 5 Single 4
## 130 6 In Relationship 3
## 131 7 Single 2
## 132 5 In Relationship 4
## 133 6 Single 3
## 134 8 In Relationship 2
## 135 5 Single 4
## 136 6 In Relationship 3
## 137 7 Single 2
## 138 5 In Relationship 4
## 139 6 Single 3
## 140 8 In Relationship 2
## 141 5 Single 4
## 142 6 In Relationship 3
## 143 7 Single 2
## 144 5 In Relationship 4
## 145 6 Single 3
## 146 8 In Relationship 2
## 147 5 Single 4
## 148 6 In Relationship 3
## 149 7 Single 2
## 150 5 In Relationship 4
## 151 6 Single 3
## 152 8 In Relationship 2
## 153 5 Single 4
## 154 6 In Relationship 3
## 155 7 Single 2
## 156 5 In Relationship 4
## 157 6 Single 3
## 158 8 In Relationship 2
## 159 5 Single 4
## 160 6 In Relationship 3
## 161 5 Single 3
## 162 7 In Relationship 2
## 163 6 Single 4
## 164 5 In Relationship 3
## 165 7 Single 2
## 166 6 In Relationship 4
## 167 5 Single 3
## 168 7 In Relationship 2
## 169 6 Single 4
## 170 5 In Relationship 3
## 171 7 Single 2
## 172 6 In Relationship 4
## 173 5 Single 3
## 174 7 In Relationship 2
## 175 6 Single 4
## 176 5 In Relationship 3
## 177 7 Single 2
## 178 6 In Relationship 4
## 179 5 Single 3
## 180 7 In Relationship 2
## 181 6 Single 4
## 182 5 In Relationship 3
## 183 7 Single 2
## 184 6 In Relationship 4
## 185 5 Single 3
## 186 7 In Relationship 2
## 187 6 Single 4
## 188 5 In Relationship 3
## 189 7 Single 2
## 190 6 In Relationship 4
## 191 5 Single 3
## 192 7 In Relationship 2
## 193 6 Single 4
## 194 5 In Relationship 3
## 195 7 Single 2
## 196 6 In Relationship 4
## 197 5 Single 3
## 198 7 In Relationship 2
## 199 6 Single 4
## 200 5 In Relationship 3
## 201 7 Single 2
## 202 6 In Relationship 4
## 203 5 Single 3
## 204 7 In Relationship 2
## 205 6 Single 4
## 206 5 In Relationship 3
## 207 7 Single 2
## 208 6 In Relationship 4
## 209 5 Single 3
## 210 7 In Relationship 2
## 211 6 Single 4
## 212 5 In Relationship 3
## 213 7 Single 2
## 214 6 In Relationship 4
## 215 5 Single 3
## 216 7 In Relationship 2
## 217 6 Single 4
## 218 5 In Relationship 3
## 219 7 Single 2
## 220 6 In Relationship 4
## 221 5 Single 4
## 222 6 In Relationship 3
## 223 8 Single 2
## 224 7 In Relationship 2
## 225 8 Single 1
## 226 6 Single 3
## 227 6 In Relationship 3
## 228 7 Single 2
## 229 4 In Relationship 4
## 230 6 Single 3
## 231 7 In Relationship 2
## 232 8 Single 1
## 233 8 Single 1
## 234 5 In Relationship 3
## 235 6 Single 3
## 236 7 In Relationship 2
## 237 4 Single 4
## 238 6 In Relationship 3
## 239 7 Single 2
## 240 8 In Relationship 2
## 241 8 Single 1
## 242 5 Single 3
## 243 6 In Relationship 3
## 244 7 Single 2
## 245 4 In Relationship 4
## 246 6 Single 3
## 247 7 In Relationship 2
## 248 8 Single 1
## 249 8 Single 1
## 250 5 In Relationship 3
## 251 6 Single 3
## 252 7 In Relationship 2
## 253 4 Single 4
## 254 6 In Relationship 3
## 255 7 Single 2
## 256 8 In Relationship 2
## 257 8 Single 1
## 258 5 Single 3
## 259 6 In Relationship 3
## 260 7 Single 2
## 261 4 In Relationship 4
## 262 6 Single 3
## 263 7 In Relationship 2
## 264 8 Single 1
## 265 8 Single 1
## 266 5 In Relationship 3
## 267 6 Single 3
## 268 7 In Relationship 2
## 269 4 Single 4
## 270 6 In Relationship 3
## 271 7 Single 2
## 272 8 In Relationship 1
## 273 8 Single 1
## 274 5 Single 3
## 275 6 In Relationship 3
## 276 7 Single 2
## 277 4 In Relationship 4
## 278 6 Single 3
## 279 7 In Relationship 2
## 280 8 Single 1
## 281 8 Single 1
## 282 5 In Relationship 3
## 283 6 Single 3
## 284 7 In Relationship 2
## 285 4 Single 4
## 286 6 In Relationship 3
## 287 7 Single 2
## 288 8 In Relationship 1
## 289 8 Single 1
## 290 5 Single 3
## 291 6 In Relationship 3
## 292 7 Single 2
## 293 4 In Relationship 4
## 294 6 Single 3
## 295 7 In Relationship 2
## 296 8 Single 1
## 297 8 Single 1
## 298 5 In Relationship 3
## 299 6 Single 3
## 300 7 In Relationship 2
## 301 4 Single 4
## 302 6 In Relationship 3
## 303 7 Single 2
## 304 8 In Relationship 1
## 305 8 Single 1
## 306 5 Single 3
## 307 6 In Relationship 3
## 308 7 Single 2
## 309 4 In Relationship 4
## 310 6 Single 3
## 311 7 In Relationship 2
## 312 8 Single 1
## 313 8 Single 1
## 314 5 In Relationship 3
## 315 6 Single 3
## 316 7 In Relationship 2
## 317 4 Single 4
## 318 6 In Relationship 3
## 319 7 Single 2
## 320 8 In Relationship 1
## 321 6 Single 3
## 322 8 In Relationship 2
## 323 7 Single 3
## 324 5 In Relationship 4
## 325 8 Single 2
## 326 6 Single 3
## 327 5 In Relationship 4
## 328 6 Single 3
## 329 7 In Relationship 2
## 330 6 Single 3
## 331 6 Single 3
## 332 8 In Relationship 2
## 333 7 Single 3
## 334 5 In Relationship 4
## 335 8 Single 2
## 336 6 Single 3
## 337 5 In Relationship 4
## 338 6 Single 3
## 339 7 In Relationship 2
## 340 6 Single 3
## 341 6 Single 3
## 342 8 In Relationship 2
## 343 7 Single 3
## 344 5 In Relationship 4
## 345 8 Single 2
## 346 6 Single 3
## 347 5 In Relationship 4
## 348 6 Single 3
## 349 7 In Relationship 2
## 350 6 Single 3
## 351 6 Single 3
## 352 8 In Relationship 2
## 353 7 Single 3
## 354 5 In Relationship 4
## 355 8 Single 2
## 356 6 Single 3
## 357 5 In Relationship 4
## 358 6 Single 3
## 359 7 In Relationship 2
## 360 6 Single 3
## 361 6 Single 3
## 362 8 In Relationship 2
## 363 7 Single 3
## 364 5 In Relationship 4
## 365 8 Single 2
## 366 6 Single 3
## 367 5 In Relationship 4
## 368 6 Single 3
## 369 7 In Relationship 2
## 370 6 Single 3
## 371 6 Single 3
## 372 8 In Relationship 2
## 373 7 Single 3
## 374 5 In Relationship 4
## 375 8 Single 2
## 376 6 Single 3
## 377 5 In Relationship 4
## 378 6 Single 3
## 379 7 In Relationship 2
## 380 6 Single 3
## 381 6 Single 3
## 382 8 In Relationship 2
## 383 7 Single 3
## 384 5 In Relationship 4
## 385 8 Single 2
## 386 6 Single 3
## 387 5 In Relationship 4
## 388 6 Single 3
## 389 7 In Relationship 2
## 390 6 Single 3
## 391 6 Single 3
## 392 8 In Relationship 2
## 393 7 Single 3
## 394 5 In Relationship 4
## 395 8 Single 2
## 396 6 Single 3
## 397 5 In Relationship 4
## 398 6 Single 3
## 399 7 In Relationship 2
## 400 6 Single 3
## 401 6 Single 3
## 402 8 In Relationship 2
## 403 7 Single 3
## 404 5 In Relationship 4
## 405 8 Single 2
## 406 6 Single 3
## 407 5 In Relationship 4
## 408 6 Single 3
## 409 7 In Relationship 2
## 410 6 Single 3
## 411 6 Single 3
## 412 8 In Relationship 2
## 413 7 Single 3
## 414 5 In Relationship 4
## 415 8 Single 2
## 416 6 Single 3
## 417 5 In Relationship 4
## 418 6 Single 3
## 419 7 In Relationship 2
## 420 6 Single 3
## 421 6 Single 3
## 422 8 In Relationship 2
## 423 7 Single 3
## 424 5 In Relationship 4
## 425 8 Single 2
## 426 6 Single 3
## 427 5 In Relationship 4
## 428 6 Single 3
## 429 7 In Relationship 2
## 430 6 Single 3
## 431 6 Single 3
## 432 8 In Relationship 2
## 433 7 Single 3
## 434 5 In Relationship 4
## 435 8 Single 2
## 436 6 Single 3
## 437 5 In Relationship 4
## 438 6 Single 3
## 439 7 In Relationship 2
## 440 6 Single 3
## 441 6 Single 3
## 442 8 In Relationship 2
## 443 7 Single 3
## 444 5 In Relationship 4
## 445 8 Single 2
## 446 6 Single 3
## 447 5 In Relationship 4
## 448 6 Single 3
## 449 7 In Relationship 2
## 450 6 Single 3
## 451 6 Single 3
## 452 8 In Relationship 2
## 453 7 Single 3
## 454 5 In Relationship 4
## 455 8 Single 2
## 456 6 Single 3
## 457 5 In Relationship 4
## 458 6 Single 3
## 459 7 In Relationship 2
## 460 6 Single 3
## 461 6 Single 3
## 462 8 In Relationship 2
## 463 7 Single 3
## 464 5 In Relationship 4
## 465 8 Single 2
## 466 6 Single 3
## 467 5 In Relationship 4
## 468 6 Single 3
## 469 7 In Relationship 2
## 470 6 Single 3
## 471 6 Single 3
## 472 8 In Relationship 2
## 473 7 Single 3
## 474 5 In Relationship 4
## 475 8 Single 2
## 476 6 Single 3
## 477 5 In Relationship 4
## 478 6 Single 3
## 479 7 In Relationship 2
## 480 6 Single 3
## 481 6 Single 3
## 482 8 In Relationship 2
## 483 7 Single 3
## 484 5 In Relationship 4
## 485 8 Single 2
## 486 6 Single 3
## 487 5 In Relationship 4
## 488 6 Single 3
## 489 7 In Relationship 2
## 490 6 Single 3
## 491 6 Single 3
## 492 8 In Relationship 2
## 493 7 Single 3
## 494 5 In Relationship 4
## 495 8 Single 2
## 496 6 Single 3
## 497 5 In Relationship 4
## 498 6 Single 3
## 499 7 In Relationship 2
## 500 6 Single 3
## 501 6 Single 3
## 502 7 In Relationship 2
## 503 8 Single 2
## 504 7 In Relationship 3
## 505 6 Single 3
## 506 6 Single 3
## 507 5 In Relationship 4
## 508 7 Single 2
## 509 5 In Relationship 4
## 510 7 Single 3
## 511 6 Single 3
## 512 7 In Relationship 2
## 513 8 Single 2
## 514 7 In Relationship 3
## 515 6 Single 3
## 516 6 Single 3
## 517 5 In Relationship 4
## 518 7 Single 2
## 519 5 In Relationship 4
## 520 7 Single 3
## 521 6 Single 3
## 522 7 In Relationship 2
## 523 8 Single 2
## 524 7 In Relationship 3
## 525 6 Single 3
## 526 6 Single 3
## 527 5 In Relationship 4
## 528 7 Single 2
## 529 5 In Relationship 4
## 530 7 Single 3
## 531 6 Single 3
## 532 7 In Relationship 2
## 533 8 Single 2
## 534 7 In Relationship 3
## 535 6 Single 3
## 536 6 Single 3
## 537 5 In Relationship 4
## 538 7 Single 2
## 539 5 In Relationship 4
## 540 7 Single 3
## 541 6 Single 3
## 542 7 In Relationship 2
## 543 8 Single 2
## 544 7 In Relationship 3
## 545 6 Single 3
## 546 6 Single 3
## 547 5 In Relationship 4
## 548 7 Single 2
## 549 5 In Relationship 4
## 550 7 Single 3
## 551 6 Single 3
## 552 7 In Relationship 2
## 553 8 Single 2
## 554 7 In Relationship 3
## 555 6 Single 3
## 556 6 Single 3
## 557 5 In Relationship 4
## 558 7 Single 2
## 559 5 In Relationship 4
## 560 7 Single 3
## 561 6 Single 3
## 562 7 In Relationship 2
## 563 8 Single 2
## 564 7 In Relationship 3
## 565 6 Single 3
## 566 6 Single 3
## 567 5 In Relationship 4
## 568 7 Single 2
## 569 5 In Relationship 4
## 570 7 Single 3
## 571 5 Single 4
## 572 8 In Relationship 2
## 573 6 Single 4
## 574 4 Single 5
## 575 7 In Relationship 2
## 576 5 Single 4
## 577 6 In Relationship 3
## 578 5 Single 4
## 579 7 Single 2
## 580 6 In Relationship 3
## 581 5 Single 4
## 582 7 In Relationship 2
## 583 5 Single 4
## 584 6 In Relationship 3
## 585 8 Single 2
## 586 5 Single 4
## 587 7 In Relationship 2
## 588 5 Single 4
## 589 7 In Relationship 2
## 590 6 Single 3
## 591 4 Single 5
## 592 7 In Relationship 2
## 593 5 Single 4
## 594 6 In Relationship 3
## 595 5 Single 4
## 596 6 Single 3
## 597 7 In Relationship 2
## 598 5 Single 4
## 599 7 In Relationship 2
## 600 4 Single 4
## 601 6 In Relationship 3
## 602 8 Single 2
## 603 5 Single 4
## 604 7 In Relationship 2
## 605 5 Single 4
## 606 7 In Relationship 2
## 607 6 Single 3
## 608 4 Single 5
## 609 7 In Relationship 2
## 610 5 Single 4
## 611 6 In Relationship 3
## 612 5 Single 4
## 613 7 In Relationship 2
## 614 6 Single 3
## 615 5 Single 4
## 616 7 In Relationship 2
## 617 4 Single 5
## 618 6 In Relationship 3
## 619 8 Single 2
## 620 5 Single 4
## 621 7 In Relationship 2
## 622 5 Single 4
## 623 7 In Relationship 2
## 624 6 Single 3
## 625 4 Single 5
## 626 7 In Relationship 2
## 627 5 Single 4
## 628 6 In Relationship 3
## 629 5 Single 4
## 630 7 In Relationship 2
## 631 6 Single 3
## 632 5 Single 4
## 633 7 In Relationship 2
## 634 4 Single 5
## 635 6 In Relationship 3
## 636 8 Single 2
## 637 5 Single 4
## 638 7 In Relationship 2
## 639 5 Single 4
## 640 7 In Relationship 2
## 641 6 Single 3
## 642 4 Single 5
## 643 7 In Relationship 2
## 644 5 Single 4
## 645 6 In Relationship 3
## 646 5 Single 4
## 647 7 In Relationship 2
## 648 6 Single 3
## 649 5 Single 4
## 650 7 In Relationship 2
## 651 4 Single 5
## 652 6 In Relationship 3
## 653 8 Single 2
## 654 5 Single 4
## 655 7 In Relationship 2
## 656 5 Single 4
## 657 7 In Relationship 2
## 658 6 Single 3
## 659 4 Single 5
## 660 7 In Relationship 2
## 661 5 Single 4
## 662 6 In Relationship 3
## 663 5 Single 4
## 664 7 In Relationship 2
## 665 6 Single 3
## 666 5 Single 4
## 667 7 In Relationship 2
## 668 4 Single 5
## 669 6 In Relationship 3
## 670 8 Single 2
## 671 5 Single 4
## 672 7 In Relationship 2
## 673 5 Single 4
## 674 7 In Relationship 2
## 675 6 Single 3
## 676 4 Single 5
## 677 7 In Relationship 2
## 678 5 Single 4
## 679 6 In Relationship 3
## 680 5 Single 4
## 681 7 In Relationship 2
## 682 6 Single 3
## 683 5 Single 4
## 684 7 In Relationship 2
## 685 4 Single 5
## 686 6 In Relationship 3
## 687 8 Single 2
## 688 5 Single 4
## 689 7 In Relationship 2
## 690 5 Single 4
## 691 7 In Relationship 2
## 692 6 Single 3
## 693 4 Single 5
## 694 7 In Relationship 2
## 695 5 Single 4
## 696 6 In Relationship 3
## 697 5 Single 4
## 698 7 In Relationship 2
## 699 6 Single 3
## 700 5 Single 4
## 701 7 In Relationship 2
## 702 4 Single 5
## 703 6 In Relationship 3
## 704 8 Single 2
## 705 5 Single 4
## Addicted_Score perc_daily_usage perc_sleep
## 1 8 22 27
## 2 3 9 31
## 3 9 25 21
## 4 4 12 29
## 5 7 19 25
## 6 9 30 19
## 7 2 6 33
## 8 8 24 25
## 9 5 17 27
## 10 4 14 29
## 11 7 20 26
## 12 8 23 24
## 13 4 12 30
## 14 9 27 23
## 15 5 15 28
## 16 7 18 25
## 17 3 8 32
## 18 8 21 24
## 19 5 15 28
## 20 7 20 25
## 21 8 22 23
## 22 4 10 30
## 23 7 20 24
## 24 8 24 22
## 25 5 13 29
## 26 9 25 22
## 27 5 16 27
## 28 7 18 25
## 29 3 9 31
## 30 8 25 22
## 31 5 15 28
## 32 7 20 24
## 33 8 22 22
## 34 4 11 30
## 35 7 20 24
## 36 8 23 23
## 37 5 13 28
## 38 9 26 21
## 39 6 16 27
## 40 7 19 24
## 41 4 10 30
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## 45 8 23 22
## 46 4 11 30
## 47 7 20 25
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## 49 5 14 28
## 50 9 26 22
## 51 6 16 27
## 52 7 20 24
## 53 4 10 30
## 54 8 24 23
## 55 5 15 27
## 56 7 20 23
## 57 8 23 22
## 58 4 12 29
## 59 7 19 25
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## 61 5 13 30
## 62 8 23 23
## 63 7 18 25
## 64 9 25 22
## 65 3 10 31
## 66 7 20 24
## 67 6 16 27
## 68 8 24 22
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## 72 5 13 28
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## 89 7 18 25
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## 91 5 12 29
## 92 7 20 24
## 93 6 15 27
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## 95 4 10 31
## 96 7 20 24
## 97 8 24 22
## 98 4 12 30
## 99 7 19 25
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## 132 8 21 27
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## 135 8 20 28
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## 180 6 21 32
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## 429 5 15 35
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## 431 7 17 32
## 432 4 12 37
## 433 6 16 34
## 434 8 29 22
## 435 4 12 38
## 436 7 18 32
## 437 9 33 18
## 438 7 28 23
## 439 5 14 36
## 440 7 18 33
## 441 7 17 33
## 442 4 12 38
## 443 6 15 34
## 444 8 29 22
## 445 4 11 38
## 446 7 18 33
## 447 9 33 18
## 448 7 28 22
## 449 5 14 36
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## 451 7 16 33
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## 457 9 34 18
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## 507 8 27 27
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## 512 5 18 33
## 513 4 15 35
## 514 6 19 32
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## 517 8 27 27
## 518 5 17 33
## 519 8 29 25
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## 524 6 19 32
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## 529 8 29 24
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## 532 5 18 34
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## 535 7 22 28
## 536 7 24 27
## 537 8 28 26
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## 582 5 20 30
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## 585 4 19 32
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## 587 5 17 32
## 588 8 27 26
## 589 5 18 31
## 590 7 24 28
## 591 9 29 24
## 592 5 18 31
## 593 8 29 25
## 594 7 23 29
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## 596 7 24 28
## 597 5 20 30
## 598 8 27 26
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## 601 7 23 28
## 602 4 18 32
## 603 8 26 27
## 604 5 19 31
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## 606 5 20 30
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## 614 7 24 28
## 615 8 25 27
## 616 5 19 30
## 617 9 28 25
## 618 7 23 28
## 619 4 18 31
## 620 8 26 26
## 621 5 18 31
## 622 8 27 26
## 623 5 19 30
## 624 7 24 27
## 625 9 29 24
## 626 5 19 30
## 627 8 28 25
## 628 7 23 28
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## 631 7 23 28
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## 635 7 24 28
## 636 4 18 31
## 637 8 25 27
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## 642 9 30 24
## 643 5 19 30
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## 651 9 28 25
## 652 7 23 28
## 653 4 18 31
## 654 8 26 26
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## 656 8 27 25
## 657 5 19 30
## 658 7 24 27
## 659 9 30 24
## 660 5 19 30
## 661 8 28 25
## 662 7 22 28
## 663 8 27 26
## 664 5 20 30
## 665 7 23 28
## 666 8 26 26
## 667 5 20 30
## 668 9 29 25
## 669 7 24 28
## 670 4 18 31
## 671 8 25 27
## 672 5 18 31
## 673 8 27 26
## 674 5 19 30
## 675 7 25 27
## 676 9 30 24
## 677 5 19 30
## 678 8 28 25
## 679 7 22 28
## 680 8 26 26
## 681 5 20 30
## 682 7 24 27
## 683 8 25 27
## 684 5 20 30
## 685 9 28 25
## 686 7 23 28
## 687 4 18 31
## 688 8 26 26
## 689 5 18 31
## 690 8 27 25
## 691 5 19 30
## 692 7 25 27
## 693 9 29 24
## 694 5 19 30
## 695 8 27 25
## 696 7 23 28
## 697 8 26 26
## 698 5 20 30
## 699 7 24 27
## 700 8 26 26
## 701 5 20 30
## 702 9 28 25
## 703 7 23 28
## 704 4 18 31
## 705 8 26 26Next step is to add categories for addiction level and sleep hours.
addiction_description <- students %>%
mutate(addiction_category = case_when(
Avg_Daily_Usage_Hours < 2 ~ "Low risk addiction",
Avg_Daily_Usage_Hours >= 2 & Avg_Daily_Usage_Hours < 4 ~ "Moderate risk addiction",
Avg_Daily_Usage_Hours >= 4 ~ "High risk addiction",
TRUE ~ NA_character_
))sleep_description <- students %>%
mutate(sleep_category = case_when(
Sleep_Hours_Per_Night < 5 ~ "Poor (<5h)",
Sleep_Hours_Per_Night >= 5 & Sleep_Hours_Per_Night < 7 ~ "Fair (7-9h)",
Sleep_Hours_Per_Night >= 4 ~ "Good (9h+)",
TRUE ~ NA_character_
))Let’s provide some summaries and check the findings.
platform_usage <- group_by(students,Most_Used_Platform)
summarise(
platform_usage,
Female = round(mean(Avg_Daily_Usage_Hours[Gender == "Female"],na.rm = TRUE), 2),
Male = round(mean(Avg_Daily_Usage_Hours[Gender == "Male"],na.rm = TRUE), 2)
)## # A tibble: 12 × 3
## Most_Used_Platform Female Male
## <chr> <dbl> <dbl>
## 1 Facebook 4.79 4.44
## 2 Instagram 4.88 4.86
## 3 KakaoTalk 4.72 NaN
## 4 LINE 3.25 NaN
## 5 LinkedIn 2.65 2.44
## 6 Snapchat 5.12 5.04
## 7 TikTok 5.61 5.02
## 8 Twitter 4.95 4.78
## 9 VKontakte NaN 4.25
## 10 WeChat 5.62 4.72
## 11 WhatsApp 6.66 6.43
## 12 YouTube NaN 4.08We can observe that average daily usage on each platform is higher for females. There are only two platforms, YouTube and VKontakte, that are not used by females. In general women spend a lot more time on social media than men.
Statistical Analysis
Summary for Students’ age column.
summary(students$Age)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 18.00 19.00 21.00 20.66 22.00 24.00Summary for Students’ average daily usage hours column.
summary(students$Avg_Daily_Usage_Hours )## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 1.500 4.100 4.800 4.919 5.800 8.500Summary for Students’ sleep hours per night column.
summary(students$Sleep_Hours_Per_Night)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 3.800 6.000 6.900 6.869 7.700 9.600Summary for Students’ mental health score column.
summary( students$Mental_Health_Score)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## 4.000 5.000 6.000 6.227 7.000 9.000summary(students[, c("Age", "Avg_Daily_Usage_Hours", "Sleep_Hours_Per_Night", "Mental_Health_Score")])## Age Avg_Daily_Usage_Hours Sleep_Hours_Per_Night
## Min. :18.00 Min. :1.500 Min. :3.800
## 1st Qu.:19.00 1st Qu.:4.100 1st Qu.:6.000
## Median :21.00 Median :4.800 Median :6.900
## Mean :20.66 Mean :4.919 Mean :6.869
## 3rd Qu.:22.00 3rd Qu.:5.800 3rd Qu.:7.700
## Max. :24.00 Max. :8.500 Max. :9.600
## Mental_Health_Score
## Min. :4.000
## 1st Qu.:5.000
## Median :6.000
## Mean :6.227
## 3rd Qu.:7.000
## Max. :9.000Let’s calculate T-test comparing addiction scores between genders, meaning testing whether the mean Addicted_Score differs between Female and Male students.
t.test(Addicted_Score ~ Gender, data = students)##
## Welch Two Sample t-test
##
## data: Addicted_Score by Gender
## t = 1.3195, df = 685.84, p-value = 0.1875
## alternative hypothesis: true difference in means between group Female and group Male is not equal to 0
## 95 percent confidence interval:
## -0.0769293 0.3921817
## sample estimates:
## mean in group Female mean in group Male
## 6.515581 6.357955✅ Conclusion:
p-value = 0.1875 is greater than 0.05, so we fail to reject the null hypothesis.
This means there is no statistically significant difference in Addicted_Score between females and males in your data.
The confidence interval includes 0, which also supports no significant difference. There’s not enough evidence to say that female and male students differ in their average Addicted_Score in this dataset.
Now, we will calculate correlations between key variables.
corr_a <- lm(Avg_Daily_Usage_Hours ~ Addicted_Score, data = students)summary(corr_a)##
## Call:
## lm(formula = Avg_Daily_Usage_Hours ~ Addicted_Score, data = students)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.84903 -0.51250 0.06924 0.49184 2.01011
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 0.67597 0.10989 6.151 1.29e-09 ***
## Addicted_Score 0.65913 0.01658 39.763 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6981 on 703 degrees of freedom
## Multiple R-squared: 0.6922, Adjusted R-squared: 0.6918
## F-statistic: 1581 on 1 and 703 DF, p-value: < 2.2e-16Correlation Analysis:
Usage Hours vs Addiction Score:
✅ Interpretation of Coefficients:
Intercept = 0.676 When Addicted_Score is 0, the predicted average daily usage is 0.676 hours.
Addicted_Score = 0.659 For every 1-point increase in Addicted_Score, Avg_Daily_Usage_Hours increases by 0.659 hours, on average. This is a positive linear relationship.
p-values (< 2e-16) Both the intercept and slope are highly statistically significant, indicating the relationship is not due to random chance.
📊 Metric Interpretation Multiple R-squared = 0.6922 The model explains 69.2% of the variance in average daily usage. This is very strong for social science data.
Adjusted R-squared = 0.6918 Adjusted for number of predictors — still high.
Residual standard error = 0.6981 Average size of prediction errors is about 0.70 hours.
F-statistic = 1581, p < 2.2e-16 The overall regression model is statistically significant.
🔍 There is a strong, statistically significant positive relationship between Addicted_Score and Avg_Daily_Usage_Hours. Higher addiction scores are strongly associated with more screen time per day.
ggplot(students, aes(x = Addicted_Score, y = Avg_Daily_Usage_Hours)) +
geom_point() +
geom_smooth(method = "lm", se = TRUE, color = "blue") +
labs(title = "Linear Regression: Usage Hours vs. Addiction Score",
x = "Addicted Score",
y = "Average Daily Usage (Hours)")## Error : The fig.showtext code chunk option must be TRUE## `geom_smooth()` using formula = 'y ~ x'
corr_b <- lm(Avg_Daily_Usage_Hours ~ Sleep_Hours_Per_Night, data = students)
summary(corr_b)##
## Call:
## lm(formula = Avg_Daily_Usage_Hours ~ Sleep_Hours_Per_Night, data = students)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.86140 -0.26171 0.07333 0.52651 1.47333
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 10.97831 0.17938 61.20 <2e-16 ***
## Sleep_Hours_Per_Night -0.88217 0.02577 -34.23 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7705 on 703 degrees of freedom
## Multiple R-squared: 0.625, Adjusted R-squared: 0.6245
## F-statistic: 1172 on 1 and 703 DF, p-value: < 2.2e-16Usage Hours vs Sleep Hours:
✅ Interpretation of Coefficients:
Intercept 10.978 If a student gets 0 hours of sleep, their predicted screen time is 10.98 hours/day. (This is a theoretical value, not practically meaningful.)
Sleep_Hours_Per_Night -0.882 For each additional hour of sleep, the average screen usage decreases by 0.88 hours/day. This shows a strong negative linear relationship.
p-values (< 2e-16) The relationship is highly statistically significant. The probability this happened by chance is nearly 0.
📊 Model Fit Metrics:
Multiple R-squared = 0.625 About 62.5% of the variation in screen usage is explained by sleep duration. That’s strong for behavioral data.
Residual standard error = 0.7705 On average, predictions deviate from the actual values by about 0.77 hours/day.
F-statistic = 1172, p < 2.2e-16 The model is statistically significant overall.
🔍 Students who sleep more tend to spend less time on screens per day. The relationship is strong, negative, and statistically significant.
ggplot(students, aes(x = Sleep_Hours_Per_Night, y = Avg_Daily_Usage_Hours)) +
geom_point() +
geom_smooth(method = "lm", se = TRUE, color = "blue") +
labs(title = "Linear Regression: Usage Hours vs. Sleep Hours",
x = "Sleep hours per night",
y = "Average Daily Usage (Hours)")## Error : The fig.showtext code chunk option must be TRUE## `geom_smooth()` using formula = 'y ~ x'
corr_c <- lm(Avg_Daily_Usage_Hours ~ Mental_Health_Score, data = students)
summary(corr_c)##
## Call:
## lm(formula = Avg_Daily_Usage_Hours ~ Mental_Health_Score, data = students)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.23707 -0.51410 0.07441 0.48590 2.46293
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 10.59452 0.16246 65.22 <2e-16 ***
## Mental_Health_Score -0.91149 0.02569 -35.48 <2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.7532 on 703 degrees of freedom
## Multiple R-squared: 0.6417, Adjusted R-squared: 0.6412
## F-statistic: 1259 on 1 and 703 DF, p-value: < 2.2e-16Usage Hours vs Mental Health:
✅ Interpretation of Coefficients: Intercept 10.59 This means when Mental_Health_Score = 0, the expected average daily usage is 10.59 hours.
Mental_Health_Score Coefficient = -0.91149 For every 1 unit increase in mental health score, the average daily social media usage decreases by ~0.91 hours, holding other factors constant.
The negative sign suggests an inverse relationship — better mental health (higher score) is associated with less social media use.
p-value < 2e-16 → extremely small. This coefficient is highly statistically significant, meaning the relationship is almost certainly not due to chance.
📊 Model Fit Metrics:
R-squared = 0.6417 About 64.2% of the variability in Avg_Daily_Usage_Hours is explained by Mental_Health_Score. This is a strong R² value for social/behavioral data.
Residual Standard Error = 0.7532 On average, the model’s predictions are off by ~0.75 hours.
🔍 There is a strong, statistically significant negative correlation between mental health scores and average daily social media usage. Specifically, individuals with higher mental health scores tend to use social media significantly less, and the model explains about 64% of the variation in usage.
ggplot(students, aes(x = Mental_Health_Score, y = Avg_Daily_Usage_Hours)) +
geom_point() +
geom_smooth(method = "lm", se = TRUE, color = "blue") +
labs(title = "Linear Regression: Usage Hours vs. Mental Health",
x = "Mental health score",
y = "Average Daily Usage (Hours)")## Error : The fig.showtext code chunk option must be TRUE## `geom_smooth()` using formula = 'y ~ x'
Data Visualization
ggplot(data = students, aes(x = Avg_Daily_Usage_Hours)) +
geom_histogram(aes(y = after_stat(density)), bins = 20, fill = "#69b3a2", color = "black", alpha = 0.7) +
geom_density(color = "blue", linewidth = 1) +
geom_vline(aes(xintercept = mean(Avg_Daily_Usage_Hours, na.rm = TRUE)),
color = "red", linetype = "dashed") +
labs(
title = "Average Daily Social Media Usage Hours",
x = "Hours",
y = "Density"
) +
theme_minimal()## Error : The fig.showtext code chunk option must be TRUE
Average daily hours on the social media platforms is 4.92.
round(mean(students$Avg_Daily_Usage_Hours),2)## [1] 4.92ggplot(data = students, aes(x = Age, y = Avg_Daily_Usage_Hours, fill = Gender)) +
geom_col(position = position_dodge(width = 0.9)) +
labs(title = "Daily Social Media Usage by Age and Gender",
x = "Age",
y = "Avg Daily Usage (Hours)") +
theme_minimal()## Error : The fig.showtext code chunk option must be TRUE
ggplot(data = students, aes(x = Gender, fill = Relationship_Status)) +
geom_bar(position = position_dodge(width = 0.9)) +
geom_text(stat = "count",
aes(label = after_stat(count), group = Relationship_Status),
position = position_dodge(width = 0.9),
vjust = -0.3) +
labs(title = "Gender Distribution and Relationship Status",
x = "Gender",
y = "Count") +
theme_minimal()## Error : The fig.showtext code chunk option must be TRUE
filtered_data <- students %>%
mutate(Most_Used_Platform = factor(Most_Used_Platform,
levels = names(sort(table(Most_Used_Platform), decreasing = TRUE))))
ggplot(data = filtered_data) +
geom_bar(mapping = aes(x = Most_Used_Platform, fill = Most_Used_Platform)) +
scale_fill_manual(values = rainbow(length(unique(filtered_data$Most_Used_Platform)))) +
geom_text(
stat = "count",
aes(x = Most_Used_Platform, label = after_stat(count)),
position = position_dodge(width = 0.9),
vjust = -0.3
) +
labs(
title = "Most Used Social Media Platforms",
x = "Platform",
y = "Count"
) +
theme_minimal() +
theme(
legend.position = "none",
axis.text.x = element_text(size = 7),
axis.text.y = element_text(size = 7),
theme(axis.text.x = element_text(angle = 45, hjust = 1)))## Error : The fig.showtext code chunk option must be TRUE
sleep_description$sleep_category <- factor(
sleep_description$sleep_category,
levels = c("Poor (<5h)", "Fair (7-9h)", "Good (9h+)")
)ggplot(data = sleep_description) +
geom_boxplot(
mapping = aes(x = sleep_category, y = Addicted_Score),
fill = "#69b3a2",
color = "black"
) +
labs(
title = "Social Media Addiction Score by Sleep Quality",
x = "Sleep Category",
y = "Addiction Score (0–10)"
) +
theme_minimal() +
theme(
plot.title = element_text(face = "bold", hjust = 0.7),
axis.title = element_text(face = "bold"),
axis.text.x = element_text(size = 9),
axis.text.y = element_text(size = 9)
)## Error : The fig.showtext code chunk option must be TRUE
ggplot(data = students) +
geom_boxplot(
mapping = aes(x = Academic_Level, y = Addicted_Score),
fill = "#69b3a2",
color = "black"
) +
labs(
title = "Social Media Addiction Score by Academic Level",
x = "Academic Level",
y = "Addiction Score (0–10)"
) +
theme_minimal() +
theme(
plot.title = element_text(face = "bold", hjust = 0.7),
axis.title = element_text(face = "bold"),
axis.text.x = element_text(size = 9),
axis.text.y = element_text(size = 9)
)## Error : The fig.showtext code chunk option must be TRUE
Key Insights from the Graph Analysis:
1. Usage Patterns and Demographics: Average daily social media usage among students is 4.92. The most popular platforms are Instagram, TikTok, Facebook. Females ages between 18 - 20 seems to use social media heavier than males. Our dataset is distributed evenly between females and males, and evenly spread between those in the relationship and being single.
2. Academic Impact: Students with higher addiction score are only on the high school level, whereas more educated ones seem to have lower addiction score and spending less hours on their social media platforms.
3. Addiction score and Sleep: There is a strong negative correlation between social media usage and mental health scores. Students with poor sleep quality (<5 hours) have significantly higher addiction scores.
Conclusion
The analysis of social media addiction among students aged 18 to 24 reveals a strong correlation between daily usage and several well-being indicators, including mental health, sleep quality, relationships, and academic performance. Our findings show that increased social media use is associated with higher addiction scores, reduced sleep hours, and poorer mental health. Students who spend more time on social media tend to experience greater challenges with their mental well-being, academic success, and sleep habits.
To support students’ well-being and academic performance, we recommend setting daily usage limits, using app blockers during study times, maintaining healthy sleep routines by avoiding screens before bedtime, and staying mindful of how excessive use may affect relationships and academic outcomes.