Being able to measure variations in data and identify abnormal variation is an important skill in many fields. In the financial sector, for example, fraudulent behaviour can cost huge sums of money. In this course, you will learn how to recognise patterns in data that differ “significantly” from the norm and learn how to provide evidence that the source of one dataset is different to another. You will learn how to use significance levels to quantify how unexpected the patterns or differences were, ultimately writing and interpreting your own hypothesis test.
You'll Learn To
Solve a real problem using the computational thinking process
Define the problem precisely by using a control to compare against
Choose and apply real tools to make decisions about significant differences
Interpret the results of the analysis and present an opinion based upon evidence
Choose significance levels to apply and learn their effect on type I and type II errors
Structure a hypothesis test to enable verification of your findings
ABOUT THIS INTERACTIVE COURSE
This self-study resource is part of the Computer-Based Maths (CBM) project and works in the Wolfram Cloud. It's free and easy to get started using the Wolfram Cloud—sign in with your Wolfram ID or create one. No plan is required. This full interactive course includes video reviews, chapter quizzes and an independent project. A certificate of course completion is available (further certification will be available in the future).
First time with our Computational Thinking modules? Please watch the video.