COMMERCE 3MA3 Chapter Notes - Chapter 12: Central Limit Theorem, Type I And Type Ii Errors, Sampling Distribution

• School: McMaster University
• Department: Commerce
• Course: COMMERCE 3MA3
• Professor: Mohammad Hossein Tajvarpour

Document Summary

Ma(cid:396)gi(cid:374) of e(cid:396)(cid:396)o(cid:396): a (cid:272)o(cid:374) de(cid:374)(cid:272)e i(cid:374)te(cid:396)(cid:448)al a(cid:396)ou(cid:374)d the sa(cid:373)ple statisti(cid:272) that a popula(cid:396) pa(cid:396)a(cid:373)ete(cid:396) is e(cid:454)pe(cid:272)ted to be: budget available, rule of thumb, number of subgroups analyzed, traditional statistical methods. Central limit theorem: the idea that a distribution of a large number of sample means or sample proportions will approximate a normal distribution, regardless of the distribution of the population from which they were drawn. The area between the mean and plus or minus one standard deviation takes in 68. 26 percent of the area under the curve, or 68. 26 percent of the observations. Proportional property of the normal distribution: a feature indicating that the proportion of observations falling between the mean and a given number of standard deviations from the mean is the same for all normal distributions. Standard normal distribution: normal distribution with a mean of zero and a standard deviation of one. Population distribution: a frequency distribution of all the elements of a population.