Our data come from _______, but we really care most about ______.

false
false
theories; mathematical models
true
samples; populations
false
populations; samples
false
subjective methods; objective methods
We study a sample to allow us to draw inferences about the population.
A random sample

false
false
is more likely to be representative of the population than any other kind of sample.
false
is always representative of the population.
false
allows you to directly calculate the parameters of the population.
false
all of the above are true.
true
all of the above are false.
Stratified sampling is more likely to be representative of the population than random sampling.
When participants who arrive for a research study are put into treatment groups
on the basis of chance,

false
false
random sampling has occurred.
true
random assignment has occurred.
false
the statistical conclusions will also be absolutely correct.
false
the research findings will be compromised because you should never randomly assign to groups.
Random assignment has occurred because the decision as to which subject goes into which group is random.
Uncertainty regarding conclusions about a population can be eliminated if you

false
false
a. use a large random sample.
true
b. obtain data from all members of the population.
false
c. depend upon the t-distribution.
false
d. both a and b.
The only way to eliminate uncertainty is to obtain data from the whole population. You can reduce uncertainty with a large sample.
Which of the following is (are) true? Using a random sample

false
true
is to accept some uncertainty about the conclusions.
true
enables you to calculate statistics.
true
is to risk drawing the wrong conclusions about the population.
false
biases your results.
All of the above except "biases your results." Random sampling does not produce bias, which means systematic rather than random error.
A random sample is one

false
false
that is haphazard.
false
that is unplanned.
true
in which every sample of a particular size has an equal probability of being selected.
false
that ensures that there will be no uncertainty in the conclusions.
A random sample is defined as one in which every sample of a particular size has an equal probability of being selected.
Which of the following is a random sample of a college student body?

false
false
Every fifth person coming out of the Campus Center between 8:30am and 10:00am.
This would be biased toward students who do not sleep late and toward students who visit the Campus Center.
true
Lisa Meyer, Todd Jones, and Maria Rivera, whose ID numbers were picked from a table of random numbers.
false
This is not a terrible way to sample, but it is not random.
Every 20th person in the student directory.
false
All are examples of random samples.
The correct choice is: Lisa Meyer, Todd Jones, and Maria Rivera, whose ID numbers were picked from a table of random numbers.
A biased sample is one that

false
false
is too small.
Bias has nothing to do with sample size. A small sample may, by chance, be non-representative of the population. However, bias refers only to systematic differences.
false
will always lead to a wrong conclusion.
There are times when the bias is small and the correct conclusion is likely to be reached despite the bias.
false
will likely have certain groups from the population over-represented or under-represented due only to chance factors.
If the over- or under-representation is due to chance, then the sample is not biased. Unbiased samples can be non-representative, especially if the sample size is small.
true
will likely have groups from the population over-represented or under-represented due to systematic sampling factors.
false
is always a good and useful sample.
A biased sample is usually not good or useful. In addition to the problem with the bias, a small sample size will often, by chance, over-represent some groups and under-represent others.
Only when the sampling is systematically favoring one group or another is the sample biased. Random samples, although they can be different from the population, are not biased. Bias is defined by the procedure for drawing the sample, not by the result.