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QUANT SKILLS
Data Analysis Primer: Essential Statistics for Management
16 HRS
PUBLISHED MAY 2025
This course provides business school students with the essential foundations in data analysis for management studies. The curriculum develops data literacy skills through a structured learning journey, requiring no prior analytical background.
Students will develop the analytical toolkit to: • Engage effectively with quantitative course content • Conduct independent data analysis required in academic projects • Critically evaluate statistical information in business publications and reports
The program focuses on practical application using Excel-based examples from real business scenarios. Interactive exercises build confidence in applying statistical techniques to authentic management challenges.
This accessible introduction to statistical methods equips students with the analytical capabilities essential for success in today's data-driven business environment.
Designed specifically for business school students with no prior background in data analysis.
⚡️ Includes the misuse of statistics
Students will learn to critique statistical claims, identify misleading visualizations, and recognize common analytical pitfalls in business reporting.
🌎️ Worked examples
Features practical Excel-based examples based on real-world applications.
✍️️ Designed for management students
All concepts are taught through relevant management examples, helping students immediately see how data analysis applies to business decision-making.
Business school students at all levels, from undergraduate to MBA.
AUTHOR
Dr. David Lefevre
Imperial College Business School
TOPIC
Foundations: Data Sourcing and Preparation
LESSONS
• Introduction • Choosing data: the different types of data • Collecting data: key principles, methods and an introduction to sampling • Evaluating and cleaning your data • Worked example: Exploring Michael's F&B chain performance dataset • Topic review and assessment
TOPIC
From Data to Insights: Describing and Visualizing Data
LESSONS
• Presenting data graphically • Measures of central tendency • Measures of dispersion • Asymmetry • Worked example: describing and visualising data in Excel • Topic review and assessment
TOPIC
Patterns and Predictions: Exploring Relationships in Data
LESSONS
• Correlation • Correlation versus causation • Simple linear regression • Worked example: Exploring Relationships in Michael's Restaurant • DataTopic review and assessment
TOPIC
Decision Making under Uncertainty: Probability & Expected Value
LESSONS
• Introduction: the world is random • Fundamentals of probability theory • Expected value for business decisions • Probability distributions • The normal distribution • What if our normal distribution is not standard? • Worked example: Probability analysis for tech workforce retention decisions • Topic review and assessment
TOPIC
From Samples to Populations: Statistical Inference
LESSONS
• Introduction to statistical inference: populations and samples • Sampling distributions: the probability distribution of sample means • Using the sample mean to infer the population mean • Worked example: Making Inferences about F&B Market Performance • Topic review and assessment
TOPIC
Testing Business Hypotheses
LESSONS
• How are hypothesis tests performed? • Hypothesis tests for population means • Hypothesis testing: two types of error • Further examples of hypothesis tests • Worked example: Hypothesis Testing for Tech Workforce Job Satisfaction • Topic review and assessment
PUBLISH DATE
May 2025
DURATION
Approx. 16 Hours
LEVEL
Business school students at all levels, from undergraduate to MBA.
AUTHOR
Dr. David Lefevre
Imperial College Business School
Upon completion of this course, students will be able to:
• Understand and engage effectively with analytical content encountered throughout management programme
• Conduct basic data analysis for academic projects using appropriate statistical methods and tools
• Critically interpret and evaluate statistical information presented in business publications and workplace reports
PUBLISH DATE
May 2025
DURATION
Approx. 16 Hours
LEVEL
Business school students at all levels, from undergraduate to MBA.
AUTHOR
Dr. David Lefevre
Imperial College Business School
TOPIC
Mathematical foundations for management I: understanding relationships
LESSONS
• Simple relationships in maths • Manipulating fractions • Fractions, decimals and ratios • Linear relationships • The form y = mx + c • Rearranging linear equations • Simultaneous equations • Inequalities • Linear relationships with more than two variables
