STAT 1000Q Lecture 11: Stats Notes 11

• School: UConn
• Department: Statistics
• Course: STAT 1000Q
• Professor: Robert Apruzese

Document Summary

Sampling distributions and the central limit theorem. Shows how for the sample mean ( ) is from the . Mx is the average of all the sample means from all the samples of size n. (cid:454) is the sta(cid:374)dard deviatio(cid:374) of all the sa(cid:373)ple (cid:373)ea(cid:374)s. This is less spread out tha(cid:374) the fro(cid:373) of population. As sa(cid:373)ple size gets bigger, the gets s(cid:373)aller. Also called the standard error of x. To find mean and sd of population. Plug in to l1 and p( ) in l1 and l2. Example 1: suppose a population has a mean of 17 and a sd of 3. 75. If population distribution is normal, the sample distribution is also normal. If sample size is 30 or more, the distribution of the sample mean will be approximately bell shaped and normal.