- Conduct and interpret chi-square single variance hypothesis tests
A test of a single variance assumes that the underlying distribution is normal. The null and alternative hypotheses are stated in terms of the population variance (or population standard deviation). The test statistic is:
- n = the total number of data
- s2 = sample variance
- σ2 = population variance
You may think of s as the random variable in this test. The number of degrees of freedom is df = n – 1. A test of a single variance may be right-tailed, left-tailed, or two-tailed. Example will show you how to set up the null and alternative hypotheses. The null and alternative hypotheses contain statements about the population variance.
Math instructors are not only interested in how their students do on exams, on average, but how the exam scores vary. To many instructors, the variance (or standard deviation) may be more important than the average.
Suppose a math instructor believes that the standard deviation for his final exam is five points. One of his best students thinks otherwise. The student claims that the standard deviation is more than five points. If the student were to conduct a hypothesis test, what would the null and alternative hypotheses be?
With individual lines at its various windows, a post office finds that the standard deviation for normally distributed waiting times for customers on Friday afternoon is 7.2 minutes. The post office experiments with a single, main waiting line and finds that for a random sample of 25 customers, the waiting times for customers have a standard deviation of 3.5 minutes.
With a significance level of 5%, test the claim that a single line causes lower variation among waiting times (shorter waiting times) for customers.
“AppleInsider Price Guides.” Apple Insider, 2013. Available online at http://appleinsider.com/mac_price_guide (accessed May 14, 2013).
Data from the World Bank, June 5, 2012.
To test variability, use the chi-square test of a single variance. The test may be left-, right-, or two-tailed, and its hypotheses are always expressed in terms of the variance (or standard deviation).
χ2= (n−1)⋅s2σ2 Test of a single variance statistic where:
n: sample size
s: sample standard deviation
σ: population standard deviationdf = n – 1 Degrees of freedom
- Use the test to determine variation.
- The degrees of freedom is the number of samples – 1.
- The test statistic is (n–1)⋅s2σ2, where n = the total number of data, s2 = sample variance, and σ2 = population variance.
- The test may be left-, right-, or two-tailed.