Inferential statistics is a method of describing a population without actually measuring the entire population itself. Instead of having to observe each member of the population, a sample can be drawn instead. Based upon the theories of probability, the measurement from the sample can then be used to describe the population. The measurement taken from the sample is called an estimator. Two critical things must be remembered: (1) the sample must be randomly drawn - that means, every member of the population has an equal chance of being picked, and, (2) the estimator does not exactly match the true population value, therefore, the chance for error must be included.
Z-tests, t-tests, and confidence intervals are classic, common types of inferential statistics.
