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Spotting a Cheat Based on Variations in Data: Computer-Based Maths (CBM) Module Interactive classroom activity that looks for fraudulent behavior by looking for unnatural data variations. Covers data patterns, comparing datasets, significance levels, hypothesis testing.
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 CBM 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.
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 CBM 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.
