A statistic is an unbiased estimator of a parameter when
Unit 5 Review-Sampling Distributions

Quiz
•
Mathematics
•
9th - 12th Grade
•
Hard
Jen Cincotta
FREE Resource
13 questions
Show all answers
1.
MULTIPLE CHOICE QUESTION
5 mins • 1 pt
in many samples, the values of the statistic are centered at the parameter
in many samples, the values of the statistic are close to the parameter
the statistic is calculated from a random sample.
in a single sample, the value of the statistic is equal to the parameter
2.
MULTIPLE CHOICE QUESTION
5 mins • 1 pt
What is the mean of the sampling distribution of p-hat?
3.
MULTIPLE CHOICE QUESTION
5 mins • 1 pt
4.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
Researchers will conduct a study of the television-viewing habits of children. They will select a simple random sample of children and record the number of hours of television the children watch per week. The researchers will report the sample mean as a point estimate for the population mean. Which of the following statements is correct for the sample mean as a point estimator?
A sample of size 25 will produce more variability of the estimator than a sample of size 50.
A sample of size 25 will produce less variability of the estimator than a sample of size 50.
A sample of size 25 will produce a biased estimator, but a sample size of 50 will produce an unbiased estimator.
A sample of size 25 will produce a more biased estimator than a sample of size 50.
A sample of size 25 will produce a less biased estimator than a sample of size 50.
5.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
The time it takes all cross country runners to complete a course has a mean of 32.1 minutes with a standard deviation of 10.2 minutes. What is the probability that an SRS of 36 runners will have a mean completion time greater than 34 minutes?
.4261
.5739
.8681
.1319
6.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
When x̅ differs from sample to sample, we say this is an example of
variability among the samples
bias among the samples
not having large enough sample sizes
poor survey techniques
7.
MULTIPLE CHOICE QUESTION
5 mins • 1 pt
The central limit theorem refers to which of the following characteristics of the sampling distribution of the sample mean?
Regardless of the shape of the population’s distribution, the sampling distribution of the sample mean from sufficiently large samples will be approximately Normally distributed.
Regardless of the shape of the population’s distribution, the standard deviation of the sampling distribution of the sample mean from sufficiently large samples will be σ/√n.
Regardless of the shape of the population’s distribution, the mean of the sampling distribution of the sample mean from sufficiently large samples will be equal to the mean of the population.
As you take larger and larger samples from a Normally distributed population, the standard deviation of the sampling distribution of the sample mean gets smaller and smaller.
As you take larger and larger samples from a Normally distributed population, the mean of the sampling distribution of the sample mean gets closer and closer to the population mean.
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