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AI, Machine Learning & Data ScienceUdemy2024-12 Edition100% Free Video Course

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

A-Level Maths: Statistics (Year 1 / AS), 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. 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.

70 Video Lessons
26.3 Hours On-Demand
Created by Senior Industry Specialist
Uploaded Sep 2026
English
A-Level Maths: Statistics (Year 1 / AS)
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Course Features:
26.3 hours on-demand video
70 complete lectures
1 downloadable project zip file(s)
Streamable on mobile, tablet & desktop
Self-paced curriculum with progress tracking
Direct MP4 downloads & offline video access
Verified course archives hosted on cloud infrastructure.

What You'll Master in this Course

Master practical concepts and hands-on skills in AI, Machine Learning & Data Science
Complete 70 video lectures with real-world examples and workflows
Build confidence with step-by-step instructions from industry experts
Access downloadable course resources and exercise files

Course Curriculum70 Lectures

12 sections • 26.3 hours total length

Prefer offline learning? Download all 70 video lectures and project files for free.
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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), 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. 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.

Instructor

S

Senior Industry Specialist

Specialist in AI, Machine Learning & Data Science

Passionate educator focused on real-world practical skills, modern frameworks, and production-ready engineering practices. Delivering step-by-step masterclasses accessible to learners globally on MJ Accedemy.

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