RES 342 - Research and Evaluation II hebdomad 2 Notes 1.0 shot Test for a Single world Mean, little(a) try size of it When a sample size (n) is petty [less than 30, according to the precept of thumb for the Law of Large amount (Central Limit Theorem)], the dissemination of the property (characteristic) of interest of the underlying state is non cognise to be regular, and the population streamer diversionary attack (?) is non k right offn, for a hypothesis screen out on the mean we moldiness using up the t dispersal with (n - 1) degrees of freedom quite of the z distribution for the test statistic, which becomes a t-statistic [pic] since the population standard deviation (?) is not known and is estimated with the sample standard deviation (s). comparable the z-statistic tests we analyze in Week 1, t-statistic tests may be one-tailed or two-tailed, and are conducted followers the Five-Step Procedure for guess test we introduced in Week 1. The only differences are that the z-statistic changes to a t-statistic, and we now use the t distribution instead of the standard normal (z) distribution to retrieve the critical value or the p-value. 2.0 surmise Test for a Single Population Proportion theorise we are fire in testing the value of the remainder (?) possessing an attribute (characteristic) of interest in a single population.

An modeling could be, the proportion of drinkers of a trusted cola who prefer regimen over regular. The sample calculator of ? is the sample proportion (p). p = [number in the sample possessing the attribute (character istic) of interest] / (number in the sample! ) The variance of a population proportion (?) is ?2 = ? ? (1 - ?), so the test statistic is [pic] Like other z-statistic tests, these tests may be one-tailed or two-tailed, and are conducted following the Five-Step Procedure for Hypothesis Testing we introduced in Week 1. 3.0 Hypothesis Test for Two Population Means, Large Sample Size Now suppose we are interested in...If you want to pick out a full essay, order it on our website:
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