Spotting a Cheat Based on Variations in Data: Computer-Based Maths Module Interactive classroom activity that looks for fraudulent behavior by looking for unnatural data variations. Covers data patterns, comparing datasets, significance levels, hypothesis testing.
Summary
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 Computational Thinking module, 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.
Featured Products & Technologies: Wolfram Cloud, Wolfram Language
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
Summary
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 Computational Thinking module, 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.
Featured Products & Technologies: Wolfram Cloud, Wolfram Language
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
