A-Level Maths: Statistics (Year 1 / As)

Master the statistics content from A-level maths (first year), and practice on real past paper exam questions.

What you'll learn

A-Level statistics

Probability

Hypothesis tests

Binomial distribution

Measures of location and spread

Data analysis

Requirements

Good knowledge of GCSE maths or equivalent

A good scientific calculator (e.g. Casio classwiz fx-991EX or graphical calculator).

Description

A-Level Maths: Statistics (Year 1 / AS) is a course for anyone studying A-Level Maths:This course covers everything in the statistics component of maths A-Level AS content, usually covered in the first year of study (Year 12). The course is suitable for all major exam boards, including Edexcel, OCR, AQA and MEI. It is also a great introduction to statistics for anyone interested in getting started.The main sections of the course are:Analysing Data - we will learn how to calculate means and medians, including from grouped data and using linear interpolation, as well as a range of different measures of spread, including interquartile range and standard deviation. We also how to merge data sets and how to code data.Representing Data - we will learn a wide range of different ways to represent data, such as histograms, cumulative frequency curves and box plots. We also look at what outliers are, and how to represent these.Bivariate Data - we will learn how to represent bivariate data in a scatter graph, how to interpret correlation, and look at regression lines.Probability - we learn what independent and mutually exclusive events are, and how to represent these in Venn diagrams and tree diagrams.Binomial Distribution - we learn what the binomial distribution is, how to calculate probabilities with it, including how to use a calculator to speed things up.Hypothesis Tests - we learn how carry out a binomial hypothesis test, including one-tailed and two-tailed tests, as well as critical regions.Sampling - we review all the major sampling techniques, both random and non-random, applying them to real data sets and discussing the strengths and weaknesses of each.Large Data Sets - I have made introductions to the large data set for Edexcel, AQA, OCR and MEI.There are four extra extended videos at the end where I go question-by-question through the statistics content in the specimen papers of Edexcel, OCR, AQA and MEI.What you get in this course:Videos: Watch as I explain each topic, introducing all the key ideas, and then go through a range of different examples, covering all the important ideas in each. In these videos I also point out the most common misconceptions and errors so that you can avoid them.Quizzes: Each sub-section is followed by a short quiz for you to test your understanding of the content just covered. Most of the questions in the quizzes are taken from real A-Level past papers. Feel free to ask for help if you get stuck on these!Worksheets: At the end of each chapter I have made a collection of different questions taken from real A-Level past papers for you to put it all together and try for yourself. At the bottom of each worksheet is a full mark-scheme so you can see how you have done.This course comes with:A 30 day money-back guarantee.A printable Udemy certificate of completion.Support in the Q&A section - ask me if you get stuck!I really hope you enjoy this course!Woody

Overview

Section 1: Introduction

Lecture 1 Introduction

Section 2: Measures of Location

Lecture 2 Mean from a List of Numbers

Lecture 3 Mean from a Frequency Table

Lecture 4 Finding the Mean Quickly Using a Calculator

Lecture 5 Estimating the Mean from Grouped Data

Lecture 6 Using a Calculator to Estimate the Mean from Grouped Data

Lecture 7 Estimating the Mean from Summary Statistics

Lecture 8 Median from List of Numbers

Lecture 9 Median from a Frequency Table

Lecture 10 Linear Interpolation (to estimate the median)

Lecture 11 Linear Interpolation - examples

Lecture 12 Linear Interpolation - harder examples

Section 3: Measures of Spread

Lecture 13 The Interquartile Range (IQR)

Lecture 14 Interquartile Range Examples

Lecture 15 Applications of Interquartile Range

Lecture 16 Linear Interpolation to Find the Interquartile Range

Lecture 17 Standard Deviation (Method 1)

Lecture 18 Standard Deviation (Method 2)

Lecture 19 MEI Students Only! - Standard Deviation Alternative Formula

Lecture 20 Standard Deviation Using the Calculator

Lecture 21 Variance

Lecture 22 Standard Deviation from Grouped Data

Lecture 23 OPTIONAL VIDEO! Proof that Methods 1 and 2 are the Same.

Section 4: Further Data Handling Techniques

Lecture 24 Merging Data: Means

Lecture 25 Merging Data: Standard Deviations

Lecture 26 Coding Data (part 1)

Lecture 27 Coding Data (part 2)

Section 5: Representing Data

Lecture 28 Outliers

Lecture 29 Outliers - An Alternative Definition

Lecture 30 Boxplots

Lecture 31 Skew

Lecture 32 Cumulative Frequency Curves

Lecture 33 Histograms - Drawing

Lecture 34 Histograms - Interpreting

Lecture 35 Histograms - Dimensions and Problem Solving

Section 6: Bivariate Data: Correlation and Regression

Lecture 36 Correlation

Lecture 37 Regression

Lecture 38 Data Analysis Practice Questions

Section 7: Probability

Lecture 39 Venn Diagrams (part 1)

Lecture 40 Venn Diagrams (part 2)

Lecture 41 Independent Events (part 1)

Lecture 42 Independent Events (part 2)

Lecture 43 Mutually Exclusive Events

Lecture 44 Tree Diagrams

Lecture 45 End of Chapter Practice Questions

Section 8: The Binomial Distribution

Lecture 46 Introduction to the Binomial Distribution

Lecture 47 The Binomial Formula (part 1)

Lecture 48 The Binomial Formula (part 2)

Lecture 49 Conditions for Using the Binomial Distribution

Lecture 50 Calculator Use: The Binomial Probability Distribution Function

Lecture 51 Calculator Use: The Binomial Cumulative Distribution (part 1)

Lecture 52 Calculator Use: The Binomial Cumulative Distribution (part 2)

Lecture 53 Other Binomial Calculations

Lecture 54 Forming New Binomial Distributions (part 1)

Lecture 55 Forming New Binomial Distributions (part 2)

Lecture 56 Discrete Random Variables

Lecture 57 End of Chapter Practice Questions

Section 9: Hypothesis Testing

Lecture 58 Hypothesis Testing Introduction

Lecture 59 One-Tailed Hypothesis Tests

Lecture 60 Two-Tailed Hypothesis Tests

Lecture 61 Critical Regions

Lecture 62 Actual Significance Levels

Lecture 63 End of Chapter Practice Questions

Section 10: Sampling Techniques

Lecture 64 Sampling and Populations

Lecture 65 Random Sampling

Lecture 66 Non-Random Sampling

Lecture 67 End of Chapter Practice Questions

Section 11: Large Data Sets

Lecture 68 Edexcel Large Data Set

Lecture 69 AQA Large Data Set

Lecture 70 OCR Large Data Set

Lecture 71 MEI Large Data Set

Section 12: Specimen Papers

Lecture 72 Edexcel AS Specimen Paper - Statistics Content

Lecture 73 AQA AS Specimen Paper - Statistics Content

Lecture 74 OCR AS Specimen Paper - Statistics Content

Lecture 75 MEI AS Specimen Paper - Statistics Content

Students taking (or planning to take) A-level maths.,Anyone interested in working through an introductory course in statistics.