QMS 202 Study Guide - Midterm Guide: Statistic, Pooled Variance, Central Limit Theorem

• School: Ryerson University
• Department: Quantitative Methods
• Course: QMS 202
• Professor: Boza Tasic

Document Summary

Is distribution of x normal: is x is normal distribution in question, can i apply central limit theorem (clt)? n . 30, yes, if n 30, no: assume that x is normally distributed. Calculator > dist -> norm -> invn to nd z ( #) Df = n-1 -> dist -> t -> invt. Variable refers to x = life of item. Parameter refers to = population life of item. Determine sample size -> mean n = z2 2 e2. Determine sample size -> proportion n = z2 (1- ) e2 n = population x = average. Sample size: # of elements in sample, n. Population size: # of elements in population, n. Parameter: measurement describing the population ( or ) Con dence interval: interval that is likely to include a population parameter given a con dence level (usually expressed in percentage). Interval is (point estimate) (margin of error) (point estimate) (critical value) (standard error)