Behaviorism of Z-Test

753 Words4 Pages
1) “Very satisfied” customers give the XYZ-Box video game system a rating that is at least 42. Suppose that the manufacturer of the XYZ-Box wishes to use the random sample of 65 satisfaction ratings to provide evidence supporting the claim that the mean composite satisfaction rating for the XYZ-Box exceeds 42. a. Letting μ represent the mean composite satisfaction rating for the XYZ-Box, set up the null and alternative hypotheses needed if we wish to attempt to provide evidence supporting the claim that μ exceeds 42. H0: μ≤42 H1: μ>42 b. In the context of this situation, interpret making a Type I error; interpret making a Type II error. Type I (α): reject the null hypothesis when the null hypothesis is true. That is, claim customer is very satisfied when actually the customer is not very satisfied. Type II (β): fail to reject the null hypothesis when the null hypothesis is false. That is, when actual customer is very satisfied, we thought they are not very satisfied. 2) How do we decide whether to use a z test or a t test when testing a hypothesis about a population mean? When the population variance is known, then use z-test, otherwise use t-test. 3) A wholesaler has recently developed a computerized sales invoicing system. Prior to implementing this system, a manual system was used. The distribution of the number of errors per invoice for the manual system is as follows: Errors per invoice 0 1 2 3 More Than 3 Percentage of Invoices 87% 8% 3% 1% 1% After implementation of the computerized system, a random sample of 500 invoices gives the following error distribution: Errors per invoice 0 1 2 3 More Than 3 Numbers of Invoices 479 10 8 2 1 a. Show that it is appropriate to carry out a chi-square test using these data. n*p0=500*0.87=435 n*p1=500*0.08=40 n*p2=500*0.03=15 n*p3=500*0.01=5 n*p4=500*0.01=5 all of them are greater
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