beginner pathway
Mathematics and Data Foundations
Build the math habits needed for statistics, open data, engineering and AI work.
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Numbers, Units, and Claims
Useful math starts by asking what a number measures, which unit it uses, and what comparison is being made. A count, rate, percentage, median and average can all tell different stories about the same situation.
Exercise
Choose a public statistic and write the numerator, denominator, unit and time window it would need before you trusted a comparison.
Assessment
Why is a percentage often more useful than a raw count?
A percentage includes a denominator, so it can support a fairer comparison than a raw count when group sizes differ.
Sources
Distributions, Not Single Numbers
A single average can hide the shape of data. Builders look at distribution, variation and sample size before drawing conclusions, especially when a tool or model might amplify a misleading summary.
Exercise
Make a tiny dataset of ten numbers, calculate an average, then describe one thing the average hides.
Assessment
What does spread describe?
Spread describes how much values vary around the center.
Sources
Math Reference Habits
A strong learner does not memorize every formula first. They learn how to find trustworthy definitions, identify notation, and keep a source trail so a calculation can be reviewed later.
Exercise
Find one math definition, write the source title and URL, then restate the definition in your own words.
Assessment
What should you record when using a formula from a reference?
Recording the source and version keeps later review possible.
Sources
Final mini-project
Create a one-page data note that explains a public statistic, its unit, its uncertainty and one chart.