Chapter 7 : Sampling and Sampling Distributions
Random samples of size 400 are taken from a population whose population proportion is 0.25. The expected value of the sample proportion is __________.
0.25
The branch of statistics that uses sample statistics to estimate a population parameter or test a hypothesis about such a parameter is BEST referred to as _____________.
Inferential statistics
In ___________, the population is divided up into mutually exclusive and collectively exhaustive groups called strata. The sample consists of randomly-selected elements from each stratum.
Stratified random sampling
T/F: If we had access to data that included the entire population, then the values of the parameters would be known and no statistical inference would be required,
True; if you have data that describes the entire population, the the answers are perfect and no sampling or estimation is needed.
In a statistical problem, a population consists of...
all items of interest.
The central limit theorem states that as n gets larger, the sampling distribution of the sample proportion....
approaches a normal distribution.
If a sample statistic consistently over- or under-estimates a population parameter, then there is _______.
bias.
A parameter is...
constant.
The sample size required to approximate the normal distribution depends on....
how much the population varies from normality.
Which of the following is considered an estimate? population mean = 5.2 population standard deviation = 3.7 population variance = 10 sample mean = 20
sample mean = 20
The probability distribution of the sample mean is commonly referred to as the _______.
sampling distribution of sample mean.
If we were to sample repeatedly from a given population, the average value of the sample means will equal.....
the population mean.
Selection bias occurs when....
there is a systematic exclusion of certain groups from consideration for the sample.
Nonresponse bias occurs when....
those responding to a survey or poll differ systematically from the non-respondents.
Stratified sampling is preferred to cluster sampling when the objective is....
to increase precision.
As a general guideline, the normal distribution approximation can be used to describe the sampling distribution of the sample mean when...
n greater than or equal to 30.
The expected value of sample mean is equal to the....
population mean.
Random samples of size 100 are taken from a population whose population proportion is 0.40. The expected value of the sample proportion is ________.
0.40
The standard deviation of the sampling distribution of sample mean is calculated as _________.
population standard deviation / square root of n.
What is a primary requirement of a "good" sample?
it is representative of the population we are trying to describe.
Which of the following statements is MOST accurate? - We use a parameter to make inference about the unknown sample statistic. - Examples of parameters include the sample mean and the sample proportion. - A parameter is a random variable who value depends on the chosen random sample. - A parameter is a constant although its value may be unknown.
a parameter is a constant although its value may be unknown.
An estimate is....
a particular value of an estimator.
A statistic is...
a random variable.
A theorem that allows us to use the normal probability distribution to approximate the sampling distribution of sample means and sample proportions whenever the sample size is large is known as the
central limit theorem
