Quantitative Data Management And Analysis With R Course in Kenya
INTRODUCTION
This course is designed for participants who plan to use R for the management, coding, analysis and visualization of qualitative data. The course’s content is spread over seven modules and includes: Basics of Applied Statistical Modelling, Essentials of the R Programming, Statistical Tools, Probability Distributions, Statistical Inference, Relationship between Two Different Quantitative Variables and Multivariate Analysis . The course is entirely hands-on and uses sample data to learn R basics and advanced features.
DURATION
5 days
WHO SHOULD ATTEND?
Statistician, analyst, or a budding data scientist and beginners who want to learn how to analyze data with R,
COURSE OBJECTIVES:
- Analyze t data by applying appropriate statistical techniques
- Interpret the statistical analysis
- Identify statistical techniques a best suited to data and questions
- Strong foundation in fundamental statistical concepts
- Implement different statistical analysis in R and interpret the results
- Build intuitive data visualizations
- Carry out formalized hypothesis testing
- Implement linear modelling techniques such multiple regressions and GLMs
- Implement advanced regression analysis and multivariate analysis
COURSE CONTENT
MODULE ONE: Basics of Applied Statistical Modelling
- Introduction to the Instructor and Course
- Data & Code Used in the Course
- Statistics in the Real World
- Designing Studies & Collecting Good Quality Data
- Different Types of Data
MODULE TWO: Essentials of the R Programming
- Rationale for this section
- Introduction to the R Statistical Software & R Studio
- Different Data Structures in R
- Reading in Data from Different Sources
- Indexing and Subletting of Data
- Data Cleaning: Removing Missing Values
- Exploratory Data Analysis in R
MODULE THREE: Statistical Tools
- Quantitative Data
- Measures of Center
- Measures of Variation
- Charting & Graphing Continuous Data
- Charting & Graphing Discrete Data
- Deriving Insights from Qualitative/Nominal Data
MODULE FOUR: Probability Distributions
- Data Distribution: Normal Distribution
- Checking For Normal Distribution
- Standard Normal Distribution and Z-scores
- Confidence Interval-Theory
- Confidence Interval-Computation in R
MODULE FIVE: Statistical Inference
- Hypothesis Testing
- T-tests: Application in R
- Non-Parametric Alternatives to T-Tests
- One-way ANOVA
- Non-parametric version of One-way ANOVA
- Two-way ANOVA
- Power Test for Detecting Effect
MODULE SIX: Relationship between Two Different Quantitative Variables
- Explore the Relationship Between Two Quantitative Variables
- Correlation
- Linear Regression-Theory
- Linear Regression-Implementation in R
- Conditions of Linear Regression
- Multi-collinearity
- Linear Regression and ANOVA
- Linear Regression With Categorical Variables and Interaction Terms
- Analysis of Covariance (ANCOVA)
- Selecting the Most Suitable Regression Model
- Violation of Linear Regression Conditions: Transform Variables
- Other Regression Techniques When Conditions of OLS Are Not Met
- Regression: Standardized Major Axis (SMA) Regression
- Polynomial and Non-linear regression
- Linear Mixed Effect Models
- Generalized Regression Model (GLM)
- Logistic Regression in R
- Poisson Regression in R
- Goodness of fit testing
MODULE SEVEN: Multivariate Analysis
- Introduction Multivariate Analysis
- Cluster Analysis/Unsupervised Learning
- Principal Component Analysis (PCA)
- Linear Discriminant Analysis (LDA)
- Correspondence Analysis
- Similarity & Dissimilarity Across Sites
- Non-metric multi-dimensional scaling (NMDS)
- Multivariate Analysis of Variance (MANOVA)
GENERAL NOTES
- This course is delivered by our seasoned trainers who have vast experience as expert professionals in the respective fields of practice. The course is taught through a mix of practical activities, theory, group works and case studies.
- Training manuals and additional reference materials are provided to the participants.
- Upon successful completion of this course, participants will be issued with a certificate.
- We can also do this as tailor-made course to meet organization-wide needs. Contact us to find out more:training@skillsforafrica.org
- The training will be conducted at SKILLS FOR AFRICA TRAINING INSTITUTE IN NAIROBI KENYA.
- The training fee covers tuition fees, training materials, lunch and training venue. Accommodation and airport transfer are arranged for our participants upon request.
- Payment should be sent to our bank account before start of training and proof of payment sent to: training@skillsforafrica.org
Course Schedule
| Dates | Fees | Location | Apply |
|---|---|---|---|
| 07/07/2025 - 11/07/2025 | $1500 | Nairobi |
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| 14/07/2025 - 18/07/2025 | $3500 | Johannesburg |
|
| 21/07/2025 - 25/07/2025 | $1500 | Nairobi |
|
| 04/08/2025 - 08/08/2025 | $1500 | Nairobi |
|
| 11/08/2025 - 15/08/2025 | $1750 | Mombasa |
|
| 18/08/2025 - 22/08/2025 | $1500 | Nairobi |
|
| 01/09/2025 - 05/09/2025 | $1500 | Nairobi |
|
| 08/09/2025 - 12/09/2025 | $3500 | Dar es Salaam |
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| 15/09/2025 - 19/09/2025 | $1500 | Nairobi |
|
| 06/10/2025 - 10/10/2025 | $1500 | Nairobi |
|
| 13/10/2025 - 17/10/2025 | $3000 | Kigali |
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| 20/10/2025 - 24/10/2025 | $1500 | Nairobi |
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| 03/11/2025 - 07/11/2025 | $1500 | Nairobi |
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| 10/11/2025 - 14/11/2025 | $1750 | Mombasa |
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| 17/11/2025 - 21/11/2025 | $1500 | Nairobi |
|
| 01/12/2025 - 05/12/2025 | $1500 | Nairobi |
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| 15/12/2025 - 19/12/2025 | $1500 | Nairobi |
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