Quiz Over Chapter 6 of the
- The two main types of estimation are called _______ estimation and
- (T/F) When a researcher uses the techniques of estimation, he/she
is making a guess as to unknown characteristics of the sample based
upon the known characteristics of the population.
- What is a "sampling error"?
- If a population is made up of 600 males and 400 females, should you
expect that a simple random sample of 100 people will end up containing
60 males and 40 females?
- Can researchers prevent sampling errors by extracting stratified
random samples from populations?
- Under what 2 unrealistic conditions would a researcher be justified
in anticipating no sampling error?
Sampling Distributions and Standard Errors
- If 100 samples are taken from a population, with each sample having
n = 25, there would be __ entries in the sampling distribution of means
if the sample means are plotted.
- Which of the following terms is closest in meaning to the term "standard
- computational error
- sampling error
- standard score
- standard deviation
- Suppose 10,000 random samples of the same size are drawn from a population
having M=50 & SD=4. Each sample's mean is computed and then
displayed in a sampling distribution. About ___% of the sample
means would lie within one standard error of 50?
- In the expression SEM, the E stands for "error." What do the
S and the M stand for?
- (T/F) Only 1 word can legitimately be put in the blank in the phrase:
"standard error of the ____"
- In Excerpt 6.1, what abbreviation was used for the phrase, "estimated
standard error of the mean"?
- In Excerpt 6.3, thow many standard error bars are displayed in the figure?
Confidence Intervals: What They Look Like
- What does the number 10 signify in this statement: "95% CI: 10, 15"?
- If a researcher computes a sample mean and says "95% CI = (80-90),"
could the sample mean be 95?
- (T/F) Confidence intervals can be built for means & correlation
coefficients but not for percentages.
- If the CIs presented in Excerpts 6.4-6.5 are typical, what is the
most popular level of confidence used?
The Construction of Confidence Intervals
- In building a confidence interval, what does a researcher specify
- the two numerical values that define the interval
- the level of confidence desired
- (T/F) Using the same data, a confidence interval will get wider if
the confidence level is increased.
- A __________ relationship exists between the size of the sample &
the distance between the end points of the confidence interval.
- near zero
- absolutely zero
- If based on the same 25 scores, will a 95% CI for the mean turn out
the same as a 95% CI for the median?
The Proper Interpretation of Confidence Intervals
- (T/F) A confidence interval indicates the probability that
the population parameter lies somewhere between the numerical end points
of the CI.
- (T/F) To interpret a CI correctly, you must imagine that lots
of samples are drawn from the population.
The Advantage of Confidence Intervals Over Estimate Standard Errors
- Confidence intervals are more easily interpreted than "standard error
intervals" because CIs take into consideration __ whereas "standard
error intervals" do not.
- sampling error
- When does the advantage of confidence intervals over "standard error
intervals" become trivial?
- When a researcher engages in point estimation, does he/she stipulate
a confidence level?
- What statistical concept can be used to explain why point estimation
is unlikely to "hit the bullseye?"
- Should reliability and validity coefficients be considered to be
- (T/F) Point estimation should be respected because it is used twice
whenever CIs are built.
Warnings Concerning Interval and Point Estimation
- (T/F) If someone says "52 ± 3," the 3 might be referring
to the SD or it might be referring to the SEM.
- (T/F) If a researcher carefully puts his/her sample data into
the proper formula, he/she will still be unable to determine
the precise value of the standard error of the statistic being focused
- (T/F) If a confidence interval is built around a correlation
coefficient, it may be the case that the CI's end points are not the
same distance from the numerical value of r computed from the sample
- The 2nd sentence in the final paragraph of Chapter 6 says that "the
entire process of estimation requires that the data used to form the
inference come from _____ ."
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