A-Level Statistics Made Easy (Full Course)

An easy-to-understand guide to the Cambridge A-level Statistics Course (Paper 5)

What you'll learn
Data Representation: what a dataset is telling us visually (stem-and-leaf diagrams, box-and-whisker plots, histograms and cumulative frequency graphs);
Measures of Location in order to estimate the most likely outcome of an experiment (mean, median, mode);
Measures of Spread in order to understand how volatile or variable a dataset is (range, quartiles, interquartile range, standard deviation);
Sigma Notation and summation
Counting Methods: Learn efficient methods for counting the number of arrangements of a set number of objects using permutation and combination functions;
Probability: how to determine the likelihood of events occurring (Venn diagrams, unions, intersections, mutually exclusive outcomes, and independent trials);
Solving probability problems involving permutations, combinations, and tree diagrams;
The Binomial Distribution: theory and application;
Discrete Probability Distributions: theory and applications, as well as understanding of expectation, variance, and standard deviation;
The Normal Distribution: theory and application;
Using the Normal Distribution to Approximate the Binomial Distribution
Requirements
GCSE-level algebra and mathematical techniques
Description
Are you battling to understand statistics? Are you confused by intimidating formulae and jargon? Are you looking for an easy-to-understand, video-based learning platform to help you ace your exams? Well if so, this course is perfect for you. I designed this statistics course combining years of teaching, investment banking, and entrepreneurial experience. The result is an easy-to-understand and real-world applicable course with detailed explanations and worked examples, which will not only help you to understand statistical concepts; but will also help you to see how statistics is applied in real-world business scenarios.  This "learn-by-doing" approach, will empower you to master the concepts being taught quickly, via direct application. The video format of the course accelerates learning, and provides an engaging delivery mechanism for the educational content. Many students who learn more effectively using visual aids or animations will find the content and flow of the course absorbing and non-monotonous. For this reason this course provides an invaluable resource for students studying in full-time learning institutions, and also for students studying via distance learning. This course is recommended for students studying for their A-level mathematics qualification through the Cambridge University syllabus. It is however also applicable to almost all of the coursework contained in the Oxford A-level mathematics syllabus as well.

Overview

Section 1: Data Representation

Lecture 1 Introduction

Lecture 2 Chapter 1 Part 2 - Stem-and-Leaf Diagram

Lecture 3 Chapter 1 Part 3 - Bar charts and histograms

Lecture 4 Chapter 1 Part 4 - Cumulative Frequency Curves

Section 2: Measures of Location

Lecture 5 Chapter 2 Part 1 - Measures of Location

Lecture 6 Chapter 2 Part 2 - The Mean and Sigma Notation

Lecture 7 Chapter 2 Part 3 - The Mode

Section 3: Measures of Spread

Lecture 8 Chapter 3 Part 1 - The Range and 5 No. Summary

Lecture 9 Chapter 3 Part 2 - Sigma Notation Revisited

Lecture 10 Chapter 3 Part 3 - Variance and Std. Deviation

Lecture 11 Chapter 3 Part 4 - Variance and Std. Deviation For Frequency Tables

Lecture 12 Part 1 Summary

Section 4: Probability

Lecture 13 Chapter 4 - Part 1 Probability General Terms and Concepts

Lecture 14 Chapter 4 - Part 2 Mutually Exclusive Outcomes

Lecture 15 Chapter 4 Part 3 - Unions and Intersections

Lecture 16 Chapter 4 Part 4 - Conditional Probability

Lecture 17 Chapter 4 Part 5 - Tree Diagrams

Lecture 18 Chapter 4 Part 6 - Independence

Section 5: Permutations and Combinations

Lecture 19 Chapter 5 - Part 1 Permutations

Lecture 20 Chapter 5 - Part 2 Permutations With Repeated Items

Lecture 21 Chapter 5 - Part 3 Combinations

Lecture 22 Chapter 5 - Part 4 Combinations With Repeated Items

Lecture 23 Chapter 5 - Part 5 Complex Problems

Section 6: Discrete Probability Distributions

Lecture 24 Chapter 6 - Discrete Probability Distributions

Section 7: The Binomial Distribution

Lecture 25 Chapter 7 Part 1 - The Binomial Distribution

Lecture 26 Chapter 7 Part 2 - The Parameters of the Binomial Distribution

Lecture 27 Chapter 7 Part 3 - The Geometric Distribution

Lecture 28 Chapter 7 Part 4 - The Mode of the Geometric Distribution

Section 8: Expectation and Variance of a Random Variable

Lecture 29 Chapter 8 Part 1 - Expectation and Variance of a Random Variable

Lecture 30 Chapter 8 Part 2 - Expectation and Variance of a Binomial Random Variable

Lecture 31 Chapter 8 Part 3 - Expectation of a Geometrically Distributed Random Variable

Lecture 32 Part 2 Summary

Section 9: The Normal Distribution

Lecture 33 Chapter 9 Part 1 - The Normal Distribution Intro

Lecture 34 Chapter 9 Part 2 - The Normal Distribution Worked Examples

Lecture 35 Chapter 9 Part 3 - Standardizing The Normal Distribution

Lecture 36 Chapter 9 Part 4 - The Normal Approximation to the Binomial Distribution

Lecture 37 Chapter 9 Part 5 - Normal Approximation to Binomial Worked Examples

Lecture 38 Part 3 Summary

A-level students wishing to write the Cambridge paper 5 statistics exam