Introduction

Categorical Data Analysis is a critical skill in modern data science, business analytics, machine learning, and applied statistics, enabling professionals to extract actionable insights from nominal, ordinal, and binary data. Categorical Data Analysis Training Course provides a hands-on, end-to-end understanding of categorical variables, contingency tables, hypothesis testing, and classification modeling, widely used in marketing analytics, healthcare research, social sciences, finance, and policy evaluation.

Designed with an industry-aligned, case-study-driven approach, this training blends statistical theory with real-world applications using tools like R, Python, and SQL-ready datasets. Learners will gain mastery in logistic regression, chi-square testing, log-linear models, and categorical machine learning techniques, empowering them to make data-driven decisions, improve predictive accuracy, and communicate insights through data storytelling and visualization.

Programme Curriculum

Categorical Data Analysis Training Course

Introduction

Course Duration

5 days

Course Objectives

Understand categorical data structures and data types
Apply exploratory data analysis (EDA) for categorical variables
Perform chi-square tests and association analysis
Analyze contingency tables and cross-tabulations
Interpret odds ratios and risk measures
Build and evaluate binary & multinomial logistic regression models
Implement log-linear modeling techniques
Handle high-dimensional categorical data
Apply feature encoding techniques
Conduct model diagnostics and goodness-of-fit testing
Use categorical data in machine learning workflows
Translate results into business insights and recommendations
Communicate findings using data visualization and storytelling

Target Audience

Data Analysts
Data Scientists
Business Intelligence Professionals
Market Research Analysts
Healthcare & Clinical Researchers
Social Science Researchers
Machine Learning Engineers
MBA & Analytics Students

Course Modules

Module 1: Foundations of Categorical Data

Types of categorical data
Real-world data examples
Data collection challenges
Data quality & preprocessing
Case Study: Customer demographic segmentation

Module 2: Exploratory Analysis & Visualization

Frequency tables & proportions
Bar plots, mosaic plots
Cross-tabulation analysis
Association measures
Case Study: Product preference analysis

Module 3: Chi-Square & Hypothesis Testing

Chi-square goodness-of-fit
Independence testing
Fisher’s exact test
Assumptions & limitations
Case Study: Website conversion analysis

Module 4: Logistic Regression Models

Binary logistic regression
Multinomial & ordinal models
Odds ratios interpretation
Model evaluation metrics
Case Study: Credit approval prediction

Module 5: Log-Linear Models

Model formulation
Interaction effects
Model selection
Likelihood ratio tests
Case Study: Healthcare diagnosis patterns

Module 6: Categorical Data in Machine Learning

Feature encoding strategies
Handling class imbalance
Tree-based models
Categorical boosting methods
Case Study: Customer churn prediction

Module 7: Advanced Topics & Diagnostics

Overfitting & regularization
Model validation techniques
Residual analysis
Bias & fairness considerations
Case Study: Hiring data bias analysis

Module 8: Business Applications & Storytelling

Translating results to decisions
KPI mapping
Dashboard integration
Stakeholder communication
Case Study: Marketing campaign optimization

Training Methodology

This course employs a participatory and hands-on approach to ensure practical learning, including:

Interactive lectures and presentations.
Group discussions and brainstorming sessions.
Hands-on exercises using real-world datasets.
Role-playing and scenario-based simulations.
Analysis of case studies to bridge theory and practice.
Peer-to-peer learning and networking.
Expert-led Q&A sessions.
Continuous feedback and personalized guidance.

Register as a group from 3 participants for a Discount

Send us an email: info@fineskilltrainingcenter.org or call +254769199797

Certification

Upon successful completion of this training, participants will be issued with a globally- recognized certificate.

Tailor-Made Course

We also offer tailor-made courses based on your needs.

Key Notes

a. The participant must be conversant with English.

b. Upon completion of training the participant will be issued with an Authorized Training Certificate

c. Course duration is flexible and the contents can be modified to fit any number of days.

d. The course fee includes facilitation training materials, 2 coffee breaks, buffet lunch and A Certificate upon successful completion of Training.

e. One-year post-training support Consultation and Coaching provided after the course.

f. Payment should be done at least a week before commence of the training, to Fineskill Training Center account, as indicated in the invoice so as to enable us prepare better for you.

Skills & Software Covered

Categorical modeling Contingency analysis Logistic regression Statistical interpretation

Programme Fee

Duration: 5 Days

Method: Online or Physical

Online Price: $1,000

Physical Price: $1,500

Certification: Accredited Certificate

View Available Dates 📄 Download Course Outline (PDF)

Available Sessions

Location

Month

Year

Sep 21 2026

21 Sep — 25 Sep 2026

💻 Online / Virtual session

Online $1,000