YouTube Users by Country – Statistical Analysis

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📖 Project Overview

This project presents a comprehensive statistical analysis of YouTube user distribution across 87 countries worldwide.
The study applies descriptive statistics, confidence intervals, hypothesis testing, and outlier detection to uncover adoption trends and patterns that matter to content creators and market analysts. This is my academical work.

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🎯 Key Objectives

• Analyze YouTube user penetration across countries
• Calculate confidence intervals for population parameters
• Perform hypothesis testing on adoption rates
• Detect outliers and analyze distribution skewness
• Provide insights for digital creators and analysts

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📊 Dataset Information

• Total Countries: 87
• Mean YouTube Users: 66.03%
• Standard Deviation: 19.06
• Range: 13.83% – 98.49%
• Distribution Shape: Left-skewed (–1.13)

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🔍 Statistical Analysis Performed

Descriptive Statistics

• Summary of adoption rates
• Central tendency & variability

Confidence Interval Analysis

Confidence Level	Mean Interval	Variance Interval	Std. Deviation Interval
95%	(61.97, 70.09)	(275.25, 502.15)	(16.59, 22.41)
98%	(61.19, 70.87)	(261.72, 534.64)	(16.18, 23.12)

Sample Analysis (10 Countries)

Countries: India, USA, Brazil, Indonesia, Mexico, Japan, Pakistan, Germany, Vietnam, Turkey

• Sample Mean: 59.72%
• 95% CI: (48.27, 71.15)
• 98% CI: (45.44, 73.98)

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📈 Key Findings

Distribution Insights

• YouTube adoption shows left-skewness
• Most countries cluster at higher adoption levels
• Lower-adoption outliers identified

Outlier Detection (Low Adoption Countries)

• Nigeria (13.83%)
• Kenya (18.20%)
• Philippines (19.49%)
• Bangladesh (20.42%)
• Ghana (20.13%)
• Senegal (20.65%)

Hypothesis Testing

Test: Population Mean vs Lower Quartile (Q1 = 57.17)

• T-statistic: 0.04985
• P-value: 0.96036
• Conclusion: Fail to reject null hypothesis
• Interpretation: No significant difference between mean and Q1

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🛠️ Technical Implementation

Tools & Technologies

• Data Handling: Google Sheets
• Statistical Computing: XLMiner Analysis ToolPak
• Visualization: Google Sheets
• Documentation: Word

Statistical Methods Applied

• Descriptive Statistics
• Confidence Interval Estimation
• Hypothesis Testing (t-test)
• Outlier Detection (IQR Method)
• Distribution & Variance Analysis

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💡 Business Implications

For Content Creators

• Identify high-penetration regions for targeted strategies
• Optimize content distribution based on audience size

For Market Analysts

• Track digital platform adoption trends
• Benchmark regions against global averages
• Detect emerging growth markets

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🚀 Getting Started

Prerequisites

• R / RStudio
• Excel or Google Sheets
• Basic statistics knowledge