Publications by fname lname & fname lname
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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Assignment 5
Objective In this assignment, you will analyze employee attrition data using various visualization techniques in R. You will create a histogram, box plots, and bar plots to gain insights into the factors affecting employee turnover. Data The dataset contains information about employees, including their satisfaction levels, last evaluation scores, ...
2509 sym R (340 sym/2 pcs)
Assignment 6
Objective In this assignment, you will analyze employee attrition data using various visualization techniques in R. You will create a histogram, box plots, and bar plots to gain insights into the factors affecting employee turnover. Data The dataset contains information about employees, including their satisfaction levels, last evaluation scores, ...
2509 sym R (340 sym/2 pcs)
Univariate Analysis With Graphs
Data Visualization with Plotly: Histograms, Box Plots, Pie Charts, and Bar Charts Illya Mowerman, Ph.D. Introduction This presentation explains how to create and interpret various types of charts using Plotly in R: Histograms and Box Plots for continuous data Pie Charts and Bar Charts for categorical data We’ll use the mtcars dataset as our p...
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CLT and Hypothesis Testing
Central Limit Theorem and Hypothesis Testing Illya Mowerman, Ph.D. Outline Introduction Central Limit Theorem (CLT) Applications of CLT Introduction to Hypothesis Testing Steps in Hypothesis Testing Types of Errors Conclusion 1. Introduction Statistical inference: Drawing conclusions about populations from samples Two key concepts: Central Lim...
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