Data science

Stage 2 · Lesson 6 of 8

Hypothesis tests and p-values

Statistics and probability you actually use

A starts by assuming there is no effect, the , then asks how surprising your data would be if that were true. The p-value is the probability of seeing a result at least as extreme as yours under the null. If it falls below a threshold chosen in advance, usually 0.05, you reject the null.

Two errors are possible: a , finding an effect that is not there, and a false negative, missing a real one. Power is the chance of detecting a real effect of a given size, and small have little of it.

Common trapreading the p-value as the probability that the null is true, or treating 0.049 and 0.051 as opposite answers rather than nearly the same evidence.

A question to check yourself, an AI practice session and 2 cheat sheet entries come with the full roadmap. Unlock

Resources for this stage

Start with· follow one of these

  • VideoFree
    StatQuest with Josh Starmer

    StatQuest · Beginner

    Free: short, clear videos on each concept, from the normal distribution to p-values and power

  • CourseFree
    Khan Academy Statistics and Probability

    Khan Academy · Beginner

    Free: the probability, sampling distributions, confidence intervals and significance tests units, with practice

Practise

  • Free textbook with end-of-chapter exercises on real data, and labs in R

  • Free: statistics taught through Python code on real datasets, with notebooks you can run

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