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Two Tailed Test for Independent Means: Mean Number of Commercials on Major Networks

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The historical reports from two major networks showed that the mean number of commercials aired during prime time was equal for both networks last year. In order to find out whether they still air the same number of commercials on average or not, random and independent samples of 85 recent prime time airings from both networks have been considered. The first network aired an average of 109.4 commercials during prime with a standard deviation of 5.7 . The second network aired 110.6 commercials with a standard deviation of 5.8 . Since the sample size is quite large, assume that the population standard deviations 5.7 and 5.8 can be estimated using the sample standard deviations. At the 0.10 level of significance, is there sufficient evidence to support the claim that the average number of commercials aired during prime time by the first station, µ1 is not equal to the average number of commercials aired during prime time by the second station µ2?
Perform a two-tailed test.
Null hypothesis: Ho:
Alternative hypothesis: H1
Type of test statistic:
The value of the test statistic? 3 decimal places
The two critical values at the 0.10 level of significance? 3 decimal places
Can we support the claim that the mean number of commercials aired during prime time by the first network is not equal to the mean number of commercials aired during prime time by the second network? Yes or no

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Solution Summary

Step by step method for testing the hypothesis under 5 step approach is discussed here. Excel template for each problem is also included. This template can be used to obtain the answers of similar problems.

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