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Question
In a hypothesis test involving two population variances, if the null hypothesis states that the two variances are strictly equal, then the test statistic is a chi-square statistic.Answer
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ANOVA: Single Factor
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In one-way analysis of variance, the within-sample variation is not affected by whether the null hypothesis is true or not.
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In a one-way analysis of variance test, the following null and alternative hypotheses are appropriate:
H0 : μ1 = μ2 = μ3
Hα : μ1 ≠μ2 ≠μ3
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In conducting one-way analysis of variance, the sample size for each group must be equal.
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In a one-way analysis of variance design, there is a single factor of interest but there may be multiple levels of the factor.
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Q:
In performing a one-tailed test for the difference between two population variances, which of the following statements is true?
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B) The sample variance that is predicted to be larger in the alternative hypothesis goes in the numerator when forming the F-test statistic.
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In a two-tailed hypothesis test involving two population variances, if the null hypothesis is true then the F-test statistic should be approximately equal to 1.0.
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When using a chi-square test for the variance of one population, we are assuming that the population is normally distributed.
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For a given significance level, increasing the sample size will tend to increase the chi-square critical value used in testing the null hypothesis about a population variance.
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Assume a sample of size n = 12 has been collected. To perform a hypothesis test of a population variance using a 0.05 level of significance, where the null hypothesis is:H0: 2 = 25The upper tail critical value is 21.92.