Statistical testing to compare means

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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 90 recent prime time airings from both networks have been considered. The first network aired an average of 109.3 commercials during prime with a standard deviation of 5.3. The second network aired 110.7 commercials with a standard deviation of 5.4. Since the sample size is quite large, assume that the population standard deviations 5.3 and 5.4 can be estimated using the sample standard deviations. At the 0.05 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, is not equal to the average number of commercials aired during prime time by the second station ? Perform a two-tailed test. Then fill in the table below.

Carry your intermediate computations to at least three decimal places and round your answers as specified in the table. (If necessary, consult a list of formulas.)

1. The null hypothesis Ho

2. The alternative hypothesis H1

3. The test statistic choose one Z t chi square F

4. The value of the test statistic
(round to at least 3 decimal places)

5. The two critical values at the 0.05 % level of significance (round to at least 3 decimal places)

6. 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

Reference no: EM13112662

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