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 50 recent prime time airings from both networks have been considered. The first network aired an average of 110.9 commercials during prime with a standard deviation of 4.5 . The second network aired 109.1 commercials with a standard deviation of 4.7 . Since the sample size is quite large, assume that the population standard deviations 4.5 and 4.7 can be estimated using the sample standard deviations. At the 0.1 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. The null hypothesis: H0: The alternative hypothesis: H1: The type of test statistic: (Choose one)ZtChi squareF The value of the test statistic:(Round to at least three decimal places.) The two critical values at the 0.1 level of significance:(Round to at least three decimal places.) and 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 No

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Description: 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, ran

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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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

recent prime time airings from both networks have been considered. The first network aired an average of

110.9

commercials during prime with a standard deviation of

4.5

. The second network aired

109.1

commercials with a standard deviation of

4.7

. Since the sample size is quite large, assume that the population standard deviations

4.5

and

4.7

can be estimated using the sample standard deviations. At the

0.1

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.


The null hypothesis:	H0:
The alternative hypothesis:	H1:
The type of test statistic:	(Choose one)ZtChi squareF

The value of the test statistic: (Round to at least three decimal places.)
The two critical values at the 0.1 level of significance: (Round to at least three decimal places.)	and
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	No

Definition Definition Measure of central tendency that is the average of a given data set. The mean value is evaluated as the quotient of the sum of all observations by the sample size. The mean, in contrast to a median, is affected by extreme values. Very large or very small values can distract the mean from the center of the data. Arithmetic mean: The most common type of mean is the arithmetic mean. It is evaluated using the formula: μ = 1 N ∑ i = 1 N x i Other types of means are the geometric mean, logarithmic mean, and harmonic mean. Geometric mean: The nth root of the product of n observations from a data set is defined as the geometric mean of the set: G = x 1 x 2 ... x n n Logarithmic mean: The difference of the natural logarithms of the two numbers, divided by the difference between the numbers is the logarithmic mean of the two numbers. The logarithmic mean is used particularly in heat transfer and mass transfer. ln x 2 − ln x 1 x 2 − x 1 Harmonic mean: The inverse of the arithmetic mean of the inverses of all the numbers in a data set is the harmonic mean of the data. 1 1 x 1 + 1 x 2 + ...

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