Data analysis
Data analysis is mostly careful counting plus resistance to a tempting conclusion. This course covers the summaries, the charts, the tests and the traps, in the order you meet them in real work.
What you'll learn
13 chapters, then the quiz
- 01What analysis is forA question first, then the numbers.
- 02Types of dataWhat kind of number you are holding.
- 03Collecting and samplingWhere the answer is usually decided.
- 04Cleaning dataMost of the work, and it shapes the result.
- 05Describing the middleMean, median and mode.
- 06Describing the spreadRange, quartiles and standard deviation.
- 07Choosing a chartThe picture is an argument.
- 08CorrelationMeasuring how two things move together.
- 09Getting to causationWhat it takes to say one thing caused another.
- 10Hypothesis testingWhat a p-value does and does not say.
- 11Traps and paradoxesWhere careful people still get caught.
- 12Tools of the tradeSpreadsheets, SQL and code.
- 13Communicating resultsThe analysis is not finished until it lands.
More ai & data tests
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