3.1  Bias and variability

3.1.1  Bias

3.1.2  Bias vs. variability

3.2  Independence and non-independence

3.2.1  Independence of measurements

3.2.2  Independence of factor effects

3.2.3  Independence of sample composition

3.3  Play!

3.3.1  Virtual two-horse races

3.3.2  More (virtual) coin tossing

3.3.3  Fair and biased coins

3.3.4  No longer independent

bias, causality, coin tossing, confounding variables, context effects, controlled experiment, day effects, effective sample size, estimate, estimate of the variability, experimenter effects, external non-independence, extreme values, factor effects, fair coin, fair estimate, Fitts' Law, independence, independent, individual differences, interference effect, internal non-independence, learning effects, model the bias, negative correlation, non-independence, order effects, peripheral vision, positive correlation, positive learning, real world, sample composition, sample size, Simpson's paradox, snowball sample, social network data, standard deviation (s.d., σ), standard deviation of the population, standard deviation of the sample, systematic effects, tossing coins, unbiased, uniformity fallacy, unintentional bias, user experience, user studies, user test, variability, variance