A hypothesis test comparing two population variances uses the F distribution. The F distribution is not symmetric and its shape will depend on two values of degrees of freedom, a numerator and denominator degrees of freedom. It is important to note that the F values will never be negative. The F test statistic is calculated as follows where s12 is the variance from sample 1, s22 is the variance from sample 2, and s12 > s22. Since the F statistic is calculated using the larger variance as the numerator, only upper tail areas will be used when finding the p-value. F = s12 s22 The size of sample 1 is denoted by n1 and will have n1 − 1 degrees of freedom. The size of sample 2 is denoted by n2 and will have n2 − 1 degrees of freedom. It is given that a sample of 21 items from population 1 has a variance of s12 = 5.5. A sample of 26 items from population 2 has a variance of s22 = 2.25. Use these values to find the F test statistic, rounding the result to two decimal places. F = s12 s22 = 2.25 =

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A hypothesis test comparing two population variances uses the F distribution. The F distribution is not symmetric and its shape will depend on two values of degrees of freedom, a numerator and denominator degrees of freedom. It is important to note that the F values will never be negative. The F test statistic is calculated as follows where s12 is the variance from sample 1, s22 is the variance from sample 2, and s12 > s22. Since the F statistic is calculated using the larger variance as the numerator, only upper tail areas will be used when finding the p-value. F = s12 s22 The size of sample 1 is denoted by n1 and will have n1 − 1 degrees of freedom. The size of sample 2 is denoted by n2 and will have n2 − 1 degrees of freedom. It is given that a sample of 21 items from population 1 has a variance of s12 = 5.5. A sample of 26 items from population 2 has a variance of s22 = 2.25. Use these values to find the F test statistic, rounding the result to two decimal places. F = s12 s22 = 2.25 =
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