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Statistics for Data Science · Module 1 of 10

Why statistics matters

Statistics turns raw data into reliable conclusions.

📖 Key ideas

  1. Descriptive statistics summarise data; inferential statistics draw conclusions about populations.
  2. A population is everyone; a sample is a subset you measure.
  3. Variables are numerical (continuous/discrete) or categorical (nominal/ordinal).
  4. Good sampling avoids bias.
  5. Statistics underpins machine learning and A/B testing.
💡 Real-life example: Tasting a spoonful of soup (sample) to judge the whole pot (population) is statistics.
PopulationEntire group of interest
SampleSubset of the population
Descriptive statisticsSummaries of data
Inferential statisticsConclusions beyond the data