SOAN 3120 Lecture Notes - Lecture 4: Confidence Interval, Second Doctor, Central Limit Theorem

• School: University of Guelph
• Department: Sociology and Anthropology
• Course: SOAN 3120
• Professor: Ryan Broll

Document Summary

The single most important concept in inferential statistics. Definition: the theoretical, probabilistic distribution of a statistic for all possible samples of given size (n) The sampling distribution is a theoretical concept. Every application of inferential statistics involves 3 different distributions: population: empirical; unknown, sampling distribution: theoretical; known, sample: empirical; known. Information from the sample is linked to the population via the sampling distribution. Has a mean equal to the population mean. Has a standard deviation (called the standard error) equal to the population standard deviation, divided by the square root of n. Tells us the shape of the sampling distribution and defines its mean and standard deviation. If repeated random samples of size n are drawn from a normal population with mean and standard deviation, then the sampling distribution of sample means will be normal with a mean and standard deviation of o/square root of n.