OPER1135 Study Guide - Final Guide: Design Patterns, Standard Deviation, Sample Size Determination
16 Nov 2016
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1 sample t-test (means: 2nd distribution tcdf, stat calc t-test. 2 sample paired: precisely the same number end in both samples, something that is a comparison. 1 sample distribution: chi squared distribution test. 1 sample z t-test: h0 p=. 05, p>. 05, x-xbar/(sqrt(p*q)/n) 2 sample test (chi squared?: df = rows-1 * columns- 1, insert a table. Homogeneity test (check back cover of stats book for the formulas and all the hypothesis tests) Type one error: null is true, but reject it by accident. Type two error: null is false, but we accept it anyway. *a tests ability to correctly reject the hypothesis is the power. *beta is the probability of failing to reject the null. The sampling distribution of any mean becomes normal as the sample size grows the. Whenever we estimate the standard deviation of a sampling distribution, we call it a standard error.
