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saw5 [17]
3 years ago
8

A radio talk show host asked listeners to respond either yes or no to the question, "Is the candidate who spends the most on a c

ampaign the most likely to win?" Fifteen people called in and nine said yes. What is the implied population?
A. all callers
B. all adults
C. all radio listeners
D. all listeners of the radio talk show

What is the variable?
A. number of callers
B. opinion of a caller
C. number of listeners
D. opinion of a listener

Can you detect any bias in the selection of the sample?
A. Yes, nonresponse. Many listeners may not call in.
B. No, there is no bias in the selection of this sample.
C. Yes, there is a systematic bias against those that are not listening to the talk show.
D. Yes, voluntary response. Those with the strongest opinions are most likely to call in.
Mathematics
1 answer:
IgorLugansk [536]3 years ago
3 0

Answer:

  • Implied population is all listeners of the radio talk show
  • the variable is opinion of a listener
  • Yes, bias is voluntary response. Those with the strongest opinions are most likely to call in.

Step-by-step explanation:

Radio talk show host asked listeners to respond therefore the population is all listeners of the radio talk show.

The variable is the response "yes" or  "no"

There is voluntary response bias, because the respondents are volunteered to answer, therefore sample is consisted of self-selected listeners.

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<em>Well, The volume of the sink shaped like a half sphere is [2000/3] π in^2.</em>

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Marysya12 [62]

Answer:

a) 15.87% of the scores are expected to be greater than 600.

b) 2.28% of the scores are expected to be greater than 700.

c) 30.85% of the scores are expected to be less than 450.

d) 53.28% of the scores are expected to be between 450 and 600.

Step-by-step explanation:

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

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\mu = 500, \sigma = 100

a. Greater than 600

This is 1 subtracted by the pvalue of Z when X = 600. So

Z = \frac{X - \mu}{\sigma}

Z = \frac{600 - 500}{100}

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15.87% of the scores are expected to be greater than 600.

b. Greater than 700

This is 1 subtracted by the pvalue of Z when X = 700. So

Z = \frac{X - \mu}{\sigma}

Z = \frac{700 - 500}{100}

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2.28% of the scores are expected to be greater than 700.

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Z = \frac{X - \mu}{\sigma}

Z = \frac{450 - 500}{100}

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30.85% of the scores are expected to be less than 450.

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