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Assignment 9
Objective In this assignment, you will analyze employee attrition data using chi-square tests and visualization techniques in R. For each chi-square test, interpret the results, both in technical and in non-technical terms, and create the appropriate graph. Data The dataset contains information about employees, including their satisfaction levels,...
2038 sym R (950 sym/4 pcs)
HR LR Model
library(readr) library(tidyverse) library(plotly) df <- read_csv("~/Library/Mobile Documents/com~apple~CloudDocs/Fairfield University/Fall 2024/DATA 6520/Assignments/Group/HR_comma_sep.csv") %>% mutate(employee_status = ifelse(left == 1 , 'Left' , 'Stayed') , work_accident = ifelse(Work_accident == 1 , 'Yes' , 'No') , promotio...
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HR Analysis - Small Data - Human Version
Analysis of Employee Attrition Drivers Illya Mowerman, Ph.D. Introduction This analysis explores the drivers of employee attrition using HR data including: Satisfaction levels Performance evaluations Number of projects Working hours Tenure Other workplace factors Exploratory Data Analysis - Numerical Variables Key observations: Satisfaction s...
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HR Analysis - Small Data - AI Version
Analysis of Employee Attrition Drivers AI Version Illya Mowerman, Ph.D. Introduction This analysis explores the drivers of employee attrition using HR data including: Satisfaction levels Performance evaluations Number of projects Working hours Tenure Other workplace factors Exploratory Data Analysis - Numerical Variables Key observations: Sat...
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Chi-Square Test
Chi-Square Analysis in R Statistical Testing for Categorical Data Illya Mowerman, Ph.D. Overview Introduction to Chi-Square Tests Chi-Square Test of Independence Chi-Square Goodness of Fit Test Practical Examples Assumptions and Requirements Practice Exercise Introduction Chi-square tests are fundamental statistical methods for analyzing catego...
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Assignment 8: t-test
Objective In this assignment, you will analyze employee attrition data using t-tests and visualization techniques in R. You will perform a t-test, interpret the results, both in technical and in non-technical terms, and create the appropriate graph. Data The dataset contains information about employees, including their satisfaction levels, last ev...
1952 sym R (743 sym/4 pcs)
t-test
Understanding t-tests with R Illya Mowerman, Ph.D. What is a t-test? Statistical test to compare means between groups Helps determine if differences between groups are statistically significant Common types: One-sample t-test: Compare a sample mean to a known value Independent two-sample t-test: Compare means of two independent groups Paired t-...
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Assignment 7: Correlations
Objective In this assignment, you will analyze employee attrition data using correlations and visualization techniques in R. You will perform a correlation, interpret the results, both in technical and in non-technical terms, and create the appropriate graph. Data The dataset contains information about employees, including their satisfaction level...
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Correlations
Correlations Illya Mowerman, Ph.D. Why correlations? It brings satistical significance when describing a realtionship between two continuous variables. What is the realtionship between: MPG vs HP? Can you see the relationship? ggplot(mtcars, aes(x = hp, y = mpg)) + geom_point() + labs(title = "Scatter Plot: MPG vs. Horsepower", x = "H...
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Story Telling
Storytelling in Business Analytics Illya Mowerman, Ph.D. Introduction Definition: Storytelling in business analytics is the art of transforming complex data insights into compelling narratives. Importance: Bridges the gap between data analysis and decision-making. Goal: To make data-driven insights accessible, engaging, and actionable for all st...
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