Stats Problem?


Question:
For many years TV executives used the guideline that 30 percent of the audiences were watching each of the prime-time networks and 10 percent were watching cable stations on a weekday night. A random sample of 500 viewers in the Tampa–St. Petersburg, Florida area last Monday night showed that 165 homes were tuned in to the ABC affiliate, 140 to the CBS affiliate, 125 to the NBC affiliate, and the remainder were viewing a cable station. At the .05 significance level, can we conclude that the guideline is still reasonable?

Answers:
H0 : The guideline is reasonable (that is to say, same ratios still apply, or ABC = CBS = NBC = 30 %, rest = 10 % )

H1: The guideline is not reasonable (the ratios do not apply)


Use the Chi square test (χ^2). Why? Check your textbooks. :) Sample values are:

ABC = 165
CBS = 140
NBC = 125
rest = 70

Expected values (if the given ratios still stand)

ABC = 30 % * 500 = 150
CBS = 30 % * 500 = 150
NBC = 30 % * 500 = 150
rest = 10 % * 500 = 50

df = 4 - 1 = 3 (where df stands for degrees of freedom, and 4 stands for the number of stations)

Using this formula:

http://www.sixsigmafirst.com/chi_square_...

calculate the value of χ^2. fi are the values you obtained from the sample (165, 140, 120, 70), and f'i are expected values.

You can obtain the critical value of χ^2 for 3 degrees of freedom and α = 0.05 from the tables for χ^2 distribution (my tables say it's 7.815). After you've found it, compare it to the calculated value of χ^2.

If the calculated value of χ^2 is lower than the table value, H0 stands. If not, you could say that, with confidence of 0.95, we claim the guidelines to be untrue.
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