Statistical Analysis - Social Media Addiction
Statistical Analysis - Social Media Addiction
Course: Statistics - MATH-233
Professor: Wilmar Alzate Berrio
Date: June 15, 2025
1. Introduction
This study analyzes the relationship between students and their social media usage. It explores variables such as addiction levels, sleep, age, academic performance, and mental health. Using statistical tools, we aimed to understand patterns, tendencies, and the impact of digital consumption.
Key Finding: 65% of students under 20 show signs of social media addiction (score ≥ 7).
2. Variable Identification
Quantitative Variables
| Variable | Type | Description |
|---|---|---|
| Student ID | Discrete | Unique identifier |
| Age | Discrete | Years of age |
| Daily Usage Hours | Continuous | Daily social media average |
| Sleep Hours | Continuous | Nightly average |
| Mental Health | Discrete | Well-being scale |
| Social Media Conflicts | Discrete | Number of conflicts |
| Addiction Score | Discrete | Addiction level |
Interpretation: This table defines the numerical variables used in the study. These variables allow statistical operations such as mean and standard deviation, helping to detect behavioral patterns and assess student well-being based on measurable indicators.
Qualitative Variables
| Variable | Type | Description |
|---|---|---|
| Gender | Nominal | Male or Female |
| Academic Level | Ordinal | High School, Undergraduate, Graduate |
| Country | Nominal | Country of origin |
| Primary Platform | Nominal | Most used social network |
| Affects Performance | Nominal | Yes/No |
| Relationship Status | Nominal | Single, In Relationship, etc. |
Interpretation: These variables categorize students based on social and demographic traits. They are essential for comparative analysis and allow segmentation to study different trends in media use and impact.
3. Central Tendency and Dispersion
Analyzed variables include Age, Usage Hours, Sleep Hours, Mental Health, Conflicts, and Addiction Score.
| Variable | Mean | Median | Mode | Std. Deviation |
|---|---|---|---|---|
| Age | 20.66 | 21.0 | 20.0 | 1.40 |
| Usage Hours | 4.92 | 4.8 | 4.7 | 1.26 |
| Sleep Hours | 6.87 | 6.9 | 7.2 | 1.13 |
| Mental Health | 6.23 | 6.0 | 6.0 | 1.11 |
| Conflicts | 2.85 | 3.0 | 3.0 | 0.96 |
| Addiction Score | 6.44 | 7.0 | 7.0 | 1.59 |
Interpretation: This table summarizes the main statistical measures—mean, median, mode, and standard deviation—for each core variable. It gives a quick overview of the typical student behavior and how much variation exists. For example, the addiction score has the highest variability.
Findings show students use social media around 5 hours daily, with a moderate addiction score. Sleep hours average near 7, and mental health is slightly below optimal.
4. Quartiles and Percentiles
Using the variable Avg_Daily_Usage_Hours, we calculated key percentiles and quartiles.
| Quartile | Hours |
|---|---|
| Q1 (25%) | 4.10 |
| Q2 (Median) | 4.80 |
| Q3 (75%) | 5.80 |
Interpretation: Quartiles split the data into four equal parts, helping to understand the spread of usage. For instance, half of students use social media between 4.1 and 5.8 hours per day—this interquartile range reflects the "typical" users.
| Percentile | Hours |
|---|---|
| P5 | 2.82 |
| P50 | 4.80 |
| P95 | 7.00 |
Interpretation: Percentiles offer finer granularity. The P95 shows that only 5% of students spend more than 7 hours per day on social media—these are potential high-risk users.
The distribution is mostly symmetrical. Outliers account for only 0.4% of the data.
5. Graphical Representations
6. Probability Analysis
Addiction in Students Under 20
64.97% of students under 20 are considered addicted (Score ≥ 7). This emphasizes the need for awareness and self-control campaigns.
Countries with Higher Addiction
| Country | Avg. Addiction Score | Interpretation |
|---|---|---|
| USA | 7.8 | Highest addiction level |
| Mexico | 6.9 | Moderate-high addiction |
| Brazil | 6.5 | Medium-high addiction |
| India | 5.8 | Medium |
| Spain | 5.4 | Intermediate |
| Others | <5.0 | Lower levels |
7. Conclusions
The study reveals a strong connection between social media usage and student well-being. Nearly two-thirds of students under 20 show addictive behaviors. Sleep and mental health are affected, and usage trends vary by country. This data supports the need for actions to promote digital literacy and healthier technology habits.
Recommendations:
- Awareness campaigns about moderate usage
- Digital time management workshops
- Monitoring of academic impact
- Promotion of offline extracurricular activities
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