← Chapter 6. Hypothesis Test for 2 Populations Export Options Alphabetize Word-Def Delimiter Tab Comma Custom Def-Word Delimiter New Line Semicolon Custom Data Copy and paste the text below. It is read-only. Select All In hypothesis testing, the critical value is: A number that establishes the boundary of the rejection region What does not need to be known in order to compute the p-value? The level of significance A sample of size of 100 selected from one population has 60 successes, and a sample of size of 150 selected from a second population has 95 successes. The test statistic for testing the equality of the population proportions equal to: -0.5319 A one-tailed test is a: Hypothesis test in which rejection region is one tail of the sampling distribution In testing the null hypothesis "Ho:p1-p2=0" , if Ho is false, this type of error is called: a Type II error The probability of making a Type I error is denoted by alpha The symbol for "x bar sub d" refers to: the mean difference in the pairs of observations taken from two dependent samples The number of degrees of freedom associated with the t test, when the data are gathered from a matched pairs experiment with 25 pairs, is: 24 If a hypothesis is not rejected at a 4% significance level, what will happen at a 2% level? Ho would not be rejected at the 2% level When creating a 95% confidence interval estimate for the means difference between two populations where sigma is not known, what is the upper limit of the confidence interval? Use the following summary information: Population 1: Sample Size (50), Sample Mean (175) and Sample Standard Deviation (18.5); Population 2: Sample Size (42), Sample Mean (158) and Sample Standard Deviation (32.4). 28.28 Excel's ___ function can be used to calculate a p-value for a hypothesis test NORMSDIST When the necessary conditions are met, a two-tail test is being conducted to test the difference between two population proportions. If the value of the test statistic z is 2.05, then the p-value is: 0.0404 If we are interested in testing whether the mean of population A is at least as big as the mean of population B, the alternative hypothesis should state: Ha: mu sub A - mu sub B < 0