What you will learn

This course is a complete video guide to all the sections covered in the Cambridge A-level Paper 5 course. the course is split up into 3 main sections:

  • Descriptive Statistics: Data representation, measures of location and measures of spread;

  • Probability and Counting Methods: Probability, permutations and combinations, and discrete probability distributions;

  • Distribution Theory: The binomial distribution, expectation and variance, and the normal distribution;

Ace Your Exams!!

Build your confidence, practice at your own pace, learn about the real-world applications of statistics in everyday life.

Course curriculum

  • 1

    Welcome to the course!

  • 3

    Chapter 2: Measures of Location

    • Chapter 2 Part 1 - Measures of Location

    • Chapter 2 Part 2 - The Mean and Sigma Notation

    • Chapter 2 Part 3 - The Mode

  • 4

    Chapter 3: Measures of Spread

    • Chapter 3 Part 1 - The Range and 5 No. Summary

    • Chapter 3 Part 2 - Sigma Notation Revisited

    • Chapter 3 Part 3 - Variance and Std. Deviation

    • Chapter 3 Part 4 - Variance and Std. Deviation For Frequency Tables

    • Chapter 3 Summary

  • 5

    Chapter 4: Probability

    • Chapter 4 Part 1 - Probability General Terms and Concepts

    • Chapter 4 - Part 2 Mutually Exclusive Outcomes

    • Chapter 4 Part 3 - Unions and Intersections

    • Chapter 4 Part 4 - Conditional Probability

    • Chapter 4 Part 5 - Tree Diagrams

    • Chapter 4 - Part 6 Independence

  • 6

    Chapter 5: Permutations and Combinations

    • Chapter 5 - Part 1 Permutations

    • Chapter 5 - Part 2 Permutations With Repeated Items

    • Chapter 5 - Part 3 Combinations

    • Chapter 5 - Part 4 Combinations With Repeated Items

    • Chapter 5 - Part 5 Complex Problems

  • 7

    Chapter 6: Discrete Probability Distributions

    • Part 2 Summary

    • Chapter 6 - Discrete Probability Distributions

  • 8

    Chapter 7: The Binomial Distribution

    • Chapter 7 Part 1 - The Binomial Distribution

    • Chapter 7 Part 2 - The Parameters of the Binomial Distribution

    • Chapter 7 Part 3 - The Geometric Distribution

    • Chapter 7 Part 4 - The Mode of the Geometric Distribution

  • 9

    Chapter 8: Expectation and Variance of a Random Variable

    • Chapter 8 Part 1 - Expectation and Variance of a Random Variable

    • Chapter 8 Part 2 - Expectation and Variance of a Binomial Random Variable

    • Chapter 8 Part 3 - Expectation of a Geometrically Distributed Random Variable

  • 10

    Chapter 9: The Normal Distribution

    • Chapter 9 Part 1 - The Normal Distribution Intro

    • Chapter 9 Part 2 - The Normal Distribution Worked Examples

    • Chapter 9 Part 3 - Standardizing The Normal Distribution

    • Chapter 9 Part 4 - The Normal Approximation to the Binomial Distribution

    • Chapter 9 Part 5 - The Normal Approximation to the Binomial Distribution Worked Examples

    • Part 3 Summary

  • 11

    Next Steps...

    • Congratulations on Completing the Course!!

    • Before you go...

Instructor

Perry Fisher

Instructor

Perry Fisher

Perry has extensive experience in investment banking and education. While an investment banker he structured multimillion-dollar transactions, developed pricing models, managed investment-related risks, prepared client pitches and successfully closed deals. Prior to investment banking, Perry worked as a training facilitator for a small business incubator program. He also taught A-level Economics, Statistics and Mathematics at one of South Africa's most prestigious high schools, and authored mathematics textbooks for distance learning students. Perry holds a Bachelor’s degree in statistics and actuarial science and an honours degree in advanced mathematics of finance.