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Tech Layoffs 2020–2024 | Statistical Analysis in R

Author: Vesethmollyka VAR
Institution: Institut Mines-Télécom Business School
Course: Application of Statistics

R RStudio ggplot2


Overview

This project performs a statistical analysis of global tech industry layoffs from 2020 to 2024. Using R and ggplot2, the analysis explores layoff trends across continents, examines the relationship between company size and layoffs, and applies hypothesis testing to draw statistically grounded conclusions.

Dataset: tech_layoffs.csv — 1,418 company-level layoff records including company name, location, continent, company size before and after layoffs, and year.


Research Questions

  1. How did tech layoffs trend across continents from 2020 to 2024?
  2. Is there a statistically significant correlation between company size and the number of layoffs?
  3. Did company size change significantly before vs. after layoffs?

Methods & Analysis

Descriptive Statistics

  • Dataset structure and data type classification
  • Summary statistics on Laid_Off and Company_Size_before_Layoffs
  • Distribution analysis with skewness and kurtosis

Exploratory Data Analysis

  • Total layoffs aggregated by continent
  • Layoff trends tracked by continent across years (2020–2024)
  • Average layoffs by company size category (Small / Medium / Large)

Hypothesis Testing

  • Correlation test — relationship between company size and layoffs (with 95% confidence intervals)
  • Paired t-test — company size before vs. after layoffs
  • Linear regression — company size as a predictor of layoffs

Visualizations

Chart Description
Line graph Layoff trends across continents over time (2020–2024)
Scatter plot Company size vs. number of layoffs
Scatter plot with trend line Linear regression overlay
Histogram with density curve Company size distribution with skewness and kurtosis
Error bar plot Paired t-test results with confidence intervals

Libraries Used

library(dplyr)   # Data manipulation
library(psych)   # Descriptive statistics
library(ggplot2) # Visualizations

How to Run

# 1. Clone the repository
# 2. Set your working directory to the folder containing tech_layoffs.csv
# 3. Open Tech Layoff Analysis.R in RStudio
# 4. Run the script top to bottom

Files

File Description
Tech Layoff Analysis.R Full R analysis script (fixed and cleaned)
tech_layoffs.csv Dataset — 1,418 tech layoff records (2020–2024)
tech_layoffs.xlsx Dataset in Excel format
Application of Statistics - Vesethmollyka VAR - Final Report.pdf Written report with findings and interpretation
Tech Layoffs 2020-2024.pptx Presentation slides

Institut Mines-Télécom Business School — Application of Statistics

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Statistical analysis of global tech layoffs (2020-2024) using R — correlation, regression, hypothesis testing, and ggplot2 visualizations

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