Which of the following is correct?

parameters describe population characteristics

The variability of a statistic is described by

the spread of its sampling distribution.

The distribution of the value of a variable for all members of a population is

the population distribution of the variable.

If we take many simple random samples from the same population, we expect

the values of the statistic will vary from sample to sample.

A population has μ=100 and Ϭ=15. For n=100, the sampling distribution of sample means is

approximately Normal, μ=100, Ϭ=1.5.

The distribution of values from a single sample of size n from a population is

the distribution of sample data.

The distribution of values taken by a statistic in all possible samples of the same size is

the sampling distribution of the statistic.

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Stats - Ch 7

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Answers

1
Which of the following is correct?
All of these are correct statements.
statistics must be based on a simple random sample
parameters describe sample characteristics
parameters describe population characteristics
2
The variability of a statistic is described by
the spread of its sampling distribution.
the amount of bias present.
probability calculations.
the stability of the population it describes.
3
The distribution of the value of a variable for all members of a population is
the parameter.
the population distribution of the variable.
the sampling distribution.
the distribution of sample data.
4
For any statistic, if the mean of its sampling distribution is equal to the parameter, then
the statistic is biased.
the statistic is unbiased.
the statistic is non-varying.
the statistic is random.
5
To reduce the variability of estimates from a simple random sample, you should
increase the bias.
use a count, not a percent.
use a smaller sample.
use a larger sample.
6
If we take many simple random samples from the same population, we expect
the values of the statistic will vary from sample to sample.
the same values of the statistic for each sample.
a different value of the parameter for each sample.
a problem with voluntary response.
7
The sampling distribution of sample proportions is approximately Normal if
np ≥ 10 and nq ≥ 10.
the population is Normal or n ≥ 30.
All of these are correct.
n ≥ 30.
8
A population has μ=100 and Ϭ=15. For n=100, the sampling distribution of sample means is
approximately Normal, μ=100, Ϭ=15.
exactly Normal, μ=100, Ϭ=1.5.
approximately Normal, μ=100, Ϭ=1.5.
exactly Normal, μ=100, Ϭ=15.
9
The distribution of values from a single sample of size n from a population is
the parameter.
the distribution of sample data.
the sampling distribution.
the population distribution of the variable.
10
The distribution of values taken by a statistic in all possible samples of the same size is
the distribution of sample data.
the variance of the values.
the sampling distribution of the statistic.
the population parameter.

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