Exploring a simplified coin flip example to lay the foundation of null and alternative hypotheses, p-values and significance levels.
Testing whether observations fit predictions, and whether events are independent, using a χ² distribution.
Using chi squared tests where numerical categories need to be combined, and goodness of fit tests using estimated parameters.
Using the t-distribution to compare a sample mean to a population mean with unknown variance.
Z-tests when the standard deviation is known, confidence intervals using Z and T distributions, critical values & regions, type Ⅰ vs ⅠⅠ errors.
Exploring a simplified coin flip example to lay the foundation of null and alternative hypotheses, p-values and significance levels.
Testing whether observations fit predictions, and whether events are independent, using a χ² distribution.
Using chi squared tests where numerical categories need to be combined, and goodness of fit tests using estimated parameters.
Using the t-distribution to compare a sample mean to a population mean with unknown variance.
Z-tests when the standard deviation is known, confidence intervals using Z and T distributions, critical values & regions, type Ⅰ vs ⅠⅠ errors.