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Question
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.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?
A) The level of alpha needs to be doubled before finding the F-critical value in the table.
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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If a hypothesis test for a single population variance is to be conducted, which of the following statements is true?
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B) The chi-square distribution is used.
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When conducting a one-tailed hypothesis test of a population variance using a sample size of n = 24 and a 0.10 level of significance, the critical value is:
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C) 33.1962
D) 36.4150
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A frozen food company that makes burritos currently has employees making burritos by hand. It is considering purchasing equipment to automate the process and wants to determine if the automated process would result in lower variability of burrito weights. It takes a random sample from each process as shown below. Process 1 (by hand)
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The managers for a vegetable canning facility claim the standard deviation for the ounces per can on the new automated line is less than for the older manual line. Given this, the correct null and alternative hypotheses for performing the statistical test are:H0 : 1 = 2Ha : 1 2
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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.
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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.