Were any assumptions required in order for this inference to be valid? a. Yes, the sample of network 1 ad-breaks must be independent of the sample of network 2 ad-breaks. Each population must be normally distributed, i.e. the population of all ad-breaks shown on network 1 have lengths that must be normally distributed and the population of all ad-breaks shown on network 2 have lengths that must be normally distributed. b. Yes, the sample of network 1 ad-breaks must be independent of the sample of network 2 ad-breaks. The Central Limit Theorem applies, which states the sampling distribution is normal for any population distributions. c. No. The Central Limit Theorem applies, which states the sampling distribution is normal for any population distributions. d. Yes , each population must be normally distributed, i.e. the population of all ad-breaks shown on network 1 have lengths that must be normally distributed and the population of all ad-breaks shown on network 2 have lengths that must be normally distributed.

Holt Mcdougal Larson Pre-algebra: Student Edition 2012
1st Edition
ISBN:9780547587776
Author:HOLT MCDOUGAL
Publisher:HOLT MCDOUGAL
Chapter11: Data Analysis And Probability
Section11.5: Interpreting Data
Problem 1C
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Were any assumptions required in order for this inference to be valid?
a. Yes, the sample of network 1 ad-breaks must be independent of the sample of network 2 ad-breaks.
Each population must be normally distributed, i.e. the population of all ad-breaks shown on network 1 have lengths that must be normally distributed and the population of all ad-breaks shown on network 2 have lengths that must be normally distributed.
b. Yes, the sample of network 1 ad-breaks must be independent of the sample of network 2 ad-breaks.
The Central Limit Theorem applies, which states the sampling distribution is normal for any population distributions.
c. No. The Central Limit Theorem applies, which states the sampling distribution is normal for any population distributions.
d. Yes , each population must be normally distributed, i.e. the population of all ad-breaks shown on network 1 have lengths that must be normally distributed and the population of all ad-breaks shown on network 2 have lengths that must be normally distributed.

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