Statistical Inference
What a sample can and cannot tell you about the population behind it: how an estimator misses, what a confidence interval actually promises, and what a p-value is - together with the three places where each of those is routinely read as something stronger than it is.
Sign in to take quizzes, earn XP, and unlock stages as you reach 90% mastery.
Estimators, Bias and Standard Error
25 min · 100 XPAn estimator as a random variable with a distribution of its own, the split of its error into bias and variance, and the worked case where the textbook unbiased estimator is the worse of the two.
Open lesson →Sign in to take the 3-question quiz.
Confidence Intervals and What They Cover
30 min · 120 XPCoverage as a property of the procedure rather than of any one interval, why the t distribution is not a refinement you can skip, and an exact computation showing a standard interval delivering 87% where it advertises 95%.
Open lesson →Sign in to take the 3-question quiz.
Hypothesis Tests, p-values and Power
30 min · 120 XPWhat a p-value is a probability of and what it is not, the two error rates and the asymmetry between them, and the arithmetic showing that most significant findings can be false while every test behaves exactly as advertised.
Open lesson →Sign in to take the 3-question quiz.