The critical condition that needs to be checked when dealing with proportions in two-sample z-intervals is whether the samples are independent and random, and if the conditions for using a normal distribution approximation are met. This includes checking sample sizes, independence, success-failure conditions, and large enough sample size assumptions.
Related terms
Random Sampling: A sampling method where every member of the population has an equal chance of being selected for the sample.
Success-Failure Conditions: Conditions used to check if the data satisfies requirements for using a normal distribution approximation in calculating confidence intervals or conducting hypothesis tests.
Large Sample Size Assumption: An assumption made when working with proportions that states that sample sizes should be large enough so that we can use approximations based on a normal distribution.