SSBM Lectures
AI use
How to Use (and Not Use) AI in 2026
Applied Statistics for Business Managers (Online)
Module 1: Descriptive Statistics & Data Types
Module 2: Probability & Distributions
Module 3: Confidence Intervals & Estimation
Module 4: Hypothesis Testing & Inference
Module 5: Correlation & Simple Regression
Module 6: Multiple Regression & Model Building
Applied statistics for business managers
Exam Review Problems
Final Exam: Applied Statistics (With Mark Scheme)
Final Exam: Applied Statistics (Questions)
Lecture 4: Statistical Inference (interactive notebooks)
notebooks (interactive notebooks)
Lecture 4: Statistical Inference for Business Decisions
Lecture 5 Case Study: Discussion Points
Lecture 5 Case Study: GreenGrocer's Delivery Dilemma
Lecture 5: Correlation & Simple Linear Regression (interactive notebooks)
notebooks (interactive notebooks)
Lecture 5: Correlation & Simple Linear Regression
Lecture 5 Test: Lectures 1–4 Review (With Answers)
Lecture 5 Test: Lectures 1–4 Review (Questions)
Lecture 6: Multiple Regression & Model Building (interactive notebooks)
notebooks (interactive notebooks)
Lecture 6: Multiple Regression & Model Building
strategy for ai
Module 1: Understanding AI Through the Lens of Technological Revolutions
Module 2: Organisational Decision-Making for Technology Adoption
Module 3: Data Strategy — The Foundation That Makes or Breaks Technology Investments
Module 4: Competitive Strategy in Technology-Driven Markets
Module 5: Ethics, Governance and Responsible Technology
Module 6: Hands-on — Working with AI as an Informed Practitioner
Module 7: Emerging Technologies, Horizon Scanning and Strategic Synthesis