CBM Student Examples

Experience Wolfram Mathematica and the CBM model:

How happy are people in my country?

Summary: Happiness, like many other subjective measures, is difficult to define. But with careful assumptions, many governments and businesses can analyse subjective data and use it to improve future growth or the lives of their citizens. In this course, you will learn how the assumptions are made and how data scientists analyse reliable sources of data, ultimately finding a measure of how happy people are in your country.

You’ll learn to solve:

• Solve a real problem using the computational thinking process
• Make assumptions and define the problem precisely
• Choose and apply real tools to find answers
• Interpret the results of the analysis and present an opinion based upon evidence
• Assess the reliability of primary and secondary sources of data
• Convert subjective data into quantifiable measures

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).

Start by clicking on this link

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Does Gender Help with Your Maths Score?

- Summary: The ability to decide whether group A is different, either better or worse, than group B is an important technique within computational thinking and data science. It is useful in many areas, from medical experiments to sales figures to environmental changes. This short course introduces you to how problems like this can be tackled, first on small datasets, then on a national scale, comparing results to published reports. - You’ll learn to:

• Solve a real problem using the computational thinking process
• Define the problem precisely by removing unnecessary complexity
• Choose and apply real tools to analyse data
• Interpret the results of the analysis and present an opinion based upon evidence
• Appreciate the effect that sample size has on the variation in results
• Use box-and-whisker charts to compare two datasets

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).

Start by clicking on this link

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Cause or Correlation?

Summary: Knowing how one variable affects another is important in many instances in real life, from medical diagnoses to environmental impacts or financial trends. In this course, you will learn about dependent connections between variables, the possible cause(s) for such dependencies and how these are often misused in the media to make claims that are incorrect—particularly about how adopting one behaviour can cause something positive or negative to happen.

You’ll learn to:

• Solve a real problem using the computational thinking process
• Define the problem precisely by using the terms correlation, dependence and cause correctly
• Choose and apply real tools to calculate correlation coefficients
• Interpret the results of the analysis and present an opinion based upon evidence
• Be suspicious when zero correlation is found
• Be wary of media reports that state “Doing X causes Y!”

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).

Start by clicking on this link

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Can I Spot a Cheat?

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 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 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).

Start by clicking on this link

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