Data Analytics using R

Key	Value
Course Code	BBT 4106
Course Name	BBT 4106: Business Intelligence I (Week 4-6)
Semester	April to July 2026
Lecturer	Allan Omondi
Contact	aomondi@strathmore.edu
Note	The lecture contains both theory and practice. This notebook forms part of the practice. It is intended for educational purposes only. Recommended citation: BibTex

Technology Stack

Click here to download Quarto: https://quarto.org/docs/get-started/

Repository Structure

.
├── 0_ClickHouse_Connection.R
├── 0_admin_instructions
│ ├── 0_instructions_for_project_setup.md
│ ├── 1_instructions_for_python_installation.md
│ └── 2_instructions_for_project_teardown.md
├── 1_simple_linear_regression.qmd
├── 2_multiple_linear_regression.qmd
├── 3_a_binary_logistic_regression.qmd
├── 3_b_binary_logistic_regression_siwaka_dishes.qmd
├── 4_t_test.qmd
├── 5_ANOVA.docx
├── 5_ANOVA.html
├── 5_ANOVA.pdf
├── 5_ANOVA.qmd
├── 6_Friedman_Test.docx
├── 6_Friedman_Test.html
├── 6_Friedman_Test.pdf
├── 6_Friedman_Test.qmd
├── 7_correlation.html
├── 7_correlation.qmd
├── DataAnalytics.Rproj
├── LICENSE
├── README.md ← This is the file you are reading now
├── RecommendedCitation.bib
├── data
│ ├── advertising.csv
│ ├── business_correlation_data.csv
│ ├── clv_data.csv
│ ├── company_survival.csv
│ ├── complaints_data.csv
│ ├── credit_data.csv
│ ├── credit_risk_simple.csv
│ ├── loan_default.csv
│ ├── ml_results.csv
│ ├── sales_performance.csv
│ ├── siwaka_dishes_branch.csv
│ ├── siwaka_dishes_customer.csv
│ ├── siwaka_dishes_view_customerfeedback_data.csv
│ ├── siwaka_dishes_view_payment_data.csv
│ ├── siwaka_dishes_view_r_per_month_per_branch.csv
│ ├── sme_socialmedia_advertising_kenya.csv
│ ├── subscription_churn.csv
│ ├── supply_chain_sample.csv
│ ├── synthetic-data-for-business-correlation.R
│ ├── synthetic-data-for-ml-model-comparison.R
│ └── t-test-data.R
├── lab_submission_instructions.md
├── lecture_notes_on_computational_notebooks.md
├── lecture_notes_on_statistical_tests.md
└── lecture_notes_on_statistical_tests_examples.md
3 directories, 48 files

Lecture Notes

Refer to the files below, in the order specified, for more details:

1. Lecture Notes on Computational Notebooks
2. Lecture Notes on Statistical Tests
3. Lecture Notes on Examples of Statistical Tests

Lab Manual

Refer to the files below, in the order specified, for more details:

1. Simple Linear Regression
2. Multiple Linear Regression
3. Binary Logistic Regression Part a and Binary Logistic Regression Part b
4. t-Test
5. ANOVA
6. Friedman Test
7. Pearson's Correlation Coefficient and Spearman's Rank Correlation

Lab Submission Instructions

• Lab Submission Instructions

Setup Instructions

• Setup Instructions

Teardown Instructions

• Teardown Instructions