The document provides a detailed overview of statistical principles and methods, including probability rules, random sampling, hypothesis testing, confidence intervals, and error types. It emphasizes the importance of understanding random outcomes, the construction of sampling distributions, and the interpretation of statistical results in various educational contexts. The content is structured in a Q&A format, highlighting key concepts essential for statistical analysis.

1. CHAPTER 8
1. Consider using the addition rule when simple outcomes are connected by the word
a) and.
b) if.
c) but.
d) or.
2. An entire set of probabilities always sums to
a) some non-negative number.
b) some number between zero and one.
c) some positive number.
d) one.
3. A random selection of registered voters within the state of Nevada guarantees that
a) at least some registered voters will be selected from Reno.
b) at least some registered voters will be selected from each county.
c) all registered voters have an equal chance of being selected.
d) all registered voters will be adequately represented.
4. The random assignment of subjects to two or more experimental groups tends to produce
groups that are
a) equal at the outset of the experiment.
b) similar at the outset of the experiment.
c) noticeably different at the outset of the experiment.
d) noticeably different at the end of the experiment.
5. The probability that any offspring of alcoholic parents will be alcoholic equals .20. Therefore,
assuming independent outcomes, the probability that two children of alcoholic parents both will
be alcoholic equals
a) .04
b) .10
c) .20
d) .40

2. 6. Whether or not a sample is random depends entirely on the
a) outcome.
b) accuracy of the outcome.
c) size of the sample.
d) selection process.
7. Assume that in a statistics class the probability of receiving a grade of A equals .30 and the
probability of receiving a grade of B equals .30. The probability that a randomly selected student
from this class will receive a grade other than an A or a B equals
a) .09
b) .36
c) .40
d) .91
8. Statisticians often wish to determine whether random outcomes can be viewed as either
a) true or false.
b) real or theoretical.
c) biased or unbiased.
d) common or rare.
9. Assume that in a statistics class the probability of receiving a grade of A equals .30 and the
probability of receiving a grade of B equals .30. The probability that a randomly selected student
from this class will receive either an A or a B equals
a) .09
b) .30
c) .60
d) .90
10. Consider using the multiplication rule when simple outcomes are connected by the word
a) and.
b) if.
c) but.
d) or.
CHAPTER 9

3. 11. A random sample of 100 college students is taken from the student body of a large university
Assume that, in fact, a population mean of 20 hours and a population standard deviation of 15
hours describe the weekly study estimates for the entire student body. About 68 percent of the
sample means in this sampling distribution should be between
a) 18.50 and 21.50 hours.
b) 16.50 and 20.50 hours.
c) 19 and 21 hours.
d) 17 and 23 hours.
12. A random sample of 100 college students is taken from the student body of a large university
Assume that, in fact, a population mean of 20 hours and a standard deviation of 15 hours
describe the weekly study estimates for the entire student body. Therefore, the sampling
distribution of the mean has a mean that
a) approximates 20 hours.
b) equals 20 hours.
c) lies within a couple of hours of 20.
d) equals the one observed sample mean.
13. The standard error of the mean serves as a rough indicator of the average amount by which
sample means deviate from
a) the population mean.
b) each other.
c) some population characteristic.
d) the one observed sample mean.
14. A sampling distribution
a) reflects the shape of the underlying population.
b) is constructed from scratch.
c) serves as a bridge between sample and population.
d) remains unchanged even with shifts to new populations.
15. When sample size is sufficiently large, about ______ percent of all sample means are within
one standard error of the sampling distribution mean.
a) 50
b) 68
c) 95

4. d) 100
16. A random sample of 100 college students is taken from the student body of a large
university. Each student estimates the number of hours spent studying each week. Therefore, the
sampling distribution of the mean is
a) approximately normal in shape.
b) very compact.
c) equal to the population.
d) centered about the sample mean.
17.Given that the population standard deviation equals 40 and that the sample consists of 25
observations, the standard error of the mean equals
a) 0.80
b) 5
c) 8
d) 40
18. The sampling distribution of the mean describes
a) the entire population.
b) the entire sample.
c) all sample means that could occur just by chance.
d) the sampled distribution.
19. A random sample of 100 college students is taken from the student body of a large university
Assume that, in fact, a population standard deviation of 15 hours describes the weekly study
estimates for the entire student body. Therefore, the sampling distribution of the mean has a
standard error that is
a) very compact.
b) equal to 1.50 hours.
c) less than 15 hours.
d) known.
20. Construction of a sampling distribution from scratch is feasible when the population is
a) very small.
b) real.
c) large.

5. d) composed of observations that are whole numbers.
CHAPTER 10
21. To express a sample mean as a z ratio,
a) subtract the hypothesized population mean.
b) subtract the hypothesized population mean and divide by the standard deviation.
c) subtract the hypothesized population mean and divide by the variance.
d) subtract the hypothesized population mean and divide by the standard error.
22. A rare outcome signifies that, with respect to the null hypothesis,
a) nothing special is happening in the underlying population.
b) something special is happening in the underlying population.
c) nothing special is happening in the sample.
d) something special is happening in the sample.
23. A decision to reject the null hypothesis implies that
a) there is a lack of support for the alternative hypothesis.
b) there is support for the alternative hypothesis.
c) the sample is probably not representative.
d) the sample size is probably inadequate.
24. The alternative hypothesis
a) is the opposite of the null hypothesis.
b) specifies a range of possible values.
c) usually is identified with the research hypothesis.
d) is described by all of the above
25. In a z test, the z ratio indicates how many __________units the sample mean deviates from
the hypothesized population mean.
a) original
b) standard deviation
c) standard error
d) critical
26.Given the following information: = 1825;s= 120; n = 144; andmhyp= 1800, the value of the z
ratio equals

6. a) 0.17
b) 2.50
c) 25.00
d) 1825.00
27. The null hypothesis
a) is tested indirectly.
b) makes a claim about a range of values.
c) usually asserts that nothing special is happening with respect to some population
characteristic.
d) usually is identified with the research hypothesis.
28. One very prevalent decision rule specifies that the null hypothesis should be rejected if the
observed z
a) equals or is more positive than 1.96.
b) equals or is more negative than %u20111.96.
c) equals or is more positive than 1.96 or equals or is more negative than %u20111.96.
d) falls between %u20111.96 and 1.96.
29. When testing a hypothesis, rejection regions are located in the
a) extreme areas of the hypothesized sampling distribution.
b) middle areas of the hypothesized sampling distribution.
c) most sensitive areas of the hypothesized sampling distribution.
d) most questionable areas of the hypothesized sampling distribution.
30. A rare outcome
a) cannot be readily attributed to variability and leads to the retention of the null hypothesis.
b) cannot be readily attributed to variability and leads to the rejection of the null hypothesis.
c) can be readily attributed to variability and leads to the retention of the null hypothesis.
d) can be readily attributed to variability and leads to the rejection of the null hypothesis.
CHAPTER 11
31. If the null hypothesis is really false and we reject the hypothesis, we have made a
a) mistake.
b) correct decision.

7. c) type I error.
d) type II error.
32. The decision to retain the null hypothesis is __________ the decision to reject the null
hypothesis.
a) as strong as
b) stronger than
c) weaker than
d) unrelated to
33. The null hypothesis
a) supports the researcher's hypothesis.
b) contradicts the researcher's hypothesis.
c) reflects the true state of affairs.
d) reflects the truth most of the time.
34. Strong support for the research hypothesis occurs whenever
the null hypothesis is
a) retained.
b) rejected.
c) tested with a very large sample size.
d) stated precisely.
35. Metal detectors at airports are used to determine whether passengers are carrying weapons. If
the null hypothesis states that a passenger isn't carrying a weapon, a type I error would occur
whenever
a) a weapon%u2011free passenger passes the detector without activating the alarm.
b) a weapon%u2011free passenger passes the detector and activates the alarm.
c) a weapon%u2011carrying passenger passes the detector without activating the alarm.
d) a weapon%u2011carrying passenger passes the detector and activates the alarm.
36. Prior to a hypothesis test, we must be concerned about ______________ possible outcomes.
a) two
b) three
c) four
d) five

8. 37.Type I errors are sometimes called
a) misses.
b) wild goose chases.
c) false alarms.
d) all of the above
38. If sample size is excessively large, an effect usually will be
a) detected even though it has importance.
b) detected even though it lacks importance.
c) missed even though it has importance.
d) missed even though it lacks importance.
39. Having committed yourself to a one-tailed test, you must retain the null hypothesis regardless
of how far the observed z deviates from the hypothesized population mean in
a) the direction of no concern.
b) the direction of concern.
c) either direction.
d) the negative direction.
40.In real-life applications, unless there are obvious reasons for selecting either a larger or
smaller level of significance, select a level of significance equal to
a) .10
b) .05
c) .01
d) .001
CHAPTER 12
41.Although many different confidence levels have been used, the two most prevalent levels are
a) 90 and 95 percent.
b) 90 and 99 percent.
c) 95 and 99 percent.
d) 99 and 99.9 percent.
42. An investigator claims, with 95 percent confidence, that the interval between 10 and 16 miles

9. includes the mean one-way commute distance for all California commuters. To have 95 percent
confidence signifies that
a) the unknown population mean is definitely between 10 and 16 miles.
b) the unknown population mean is between 10 and 16 miles with probability .95.
c) if these intervals were constructed for a long series of samples, approximately 95 percent
would include the unknown mean commute distance for all Californians.
d) if sample means were obtained for a long series of samples, approximately 95 percent of all
sample means would be between 10 and 16 miles.
43. Although we never really know whether a particular 95 percent confidence interval is true or
false, we can be "reasonably confident" that
a) a second confidence interval would describe exactly the same range of values as the first
confidence interval.
b) a long series of confidence intervals would include the unknown population mean.
c) the one observed confidence interval includes the unknown population mean.
d) the one observed confidence interval contains the observed sample mean.
44. As sample size grows larger, a confidence interval approaches a
a) population survey.
b) point estimate.
c) standard error.
d) population range.
45. A false 95 percent confidence interval would be produced if, in fact, the one observed sample
mean
a) coincides with the unknown population mean.
b) deviates one%u2011half of a standard error unit above the unknown population mean.
c) deviates one and one%u2011half standard error units below the unknown population mean.
d) deviates three standard error units above the unknown population mean.
46. Consider the use of a
a) hypothesis test whenever a confidence interval has been constructed.
b) hypothesis test whenever you suspect the null hypothesis to be true.
c) confidence interval whenever the null hypothesis has been retained.
d) confidence interval whenever the null hypothesis has been rejected.

10. 47. Prior to attending college, randomly selected college-bound students participate in a summer
workshop on the development of good study habits. Subsequently, at the end of their first year in
college, they showed a dramatic increase in grade point averages, relative to the national average
of 2.75, as revealed by a 95 percent confidence interval of 2.90 to 3.30. This confidence interval
signifies that
a) every student who participated in the summer workshop had a GPA between 2.90 and 3.30.
b) about 95 percent of all students who participated in the summer workshop had GPAs
between 2.90 and 3.30.
c) the true population mean (for all students who could conceivably take the summer
workshop) is between 2.90 and 3.30.
d) we can be reasonably confident that the true population mean (for all students who could
conceivably take the summer workshop) is between 2.90 and 3.30.
48. A pollster reports, with 95 percent confidence, that between 55 and 61 percent of all
Americans favor mandatory drug testings for employees in positions of public trust (bus drivers,
airline pilots, etc). The margin of error in this survey equals
a) 3 percent.
b) 6 percent.
c) 55 percent.
d) some unknown percent.
49. A pollster reports, with 95 percent confidence, that between 55 and 61 percent of all
Americans favor mandatory drug testings for employees in positions of public trust (bus drivers,
airline pilots, etc). The point estimate for the unknown population proportion (who favor
mandatory drug testing) equals
a) 55 percent.
b) 58 percent.
c) 61 percent.
d) some unknown percent.
50. The larger the sample size,
a) the smaller the standard error and the narrower the confidence interval.
b) the smaller the standard error and the wider the confidence interval.

11. c) the larger the standard error and the narrower the confidence interval.
d) the larger the standard error and the wider the confidence interval.
Solution
1. Consider using the addition rule when simple outcomes are connected by the word
a) and.
b) if.
c) but.
d) or.
2. An entire set of probabilities always sums to
a) some non-negative number.
b) some number between zero and one.
c) some positive number.
d) one.
3. A random selection of registered voters within the state of Nevada guarantees that
a) at least some registered voters will be selected from Reno.
b) at least some registered voters will be selected from each county.
c) all registered voters have an equal chance of being selected.
d) all registered voters will be adequately represented.
4. The random assignment of subjects to two or more experimental groups tends to produce
groups that are
a) equal at the outset of the experiment.
b) similar at the outset of the experiment.
c) noticeably different at the outset of the experiment.
d) noticeably different at the end of the experiment.
5. The probability that any offspring of alcoholic parents will be alcoholic equals .20. Therefore,
assuming independent outcomes, the probability that two children of alcoholic parents both will
be alcoholic equals
a) .04
b) .10
c) .20

12. d) .40
6. Whether or not a sample is random depends entirely on the
a) outcome.
b) accuracy of the outcome.
c) size of the sample.
d) selection process.
7. Assume that in a statistics class the probability of receiving a grade of A equals .30 and the
probability of receiving a grade of B equals .30. The probability that a randomly selected student
from this class will receive a grade other than an A or a B equals
a) .09
b) .36
c) .40
d) .91
8. Statisticians often wish to determine whether random outcomes can be viewed as either
a) true or false.
b) real or theoretical.
c) biased or unbiased.
d) common or rare.
9. Assume that in a statistics class the probability of receiving a grade of A equals .30 and the
probability of receiving a grade of B equals .30. The probability that a randomly selected student
from this class will receive either an A or a B equals
a) .09
b) .30
c) .60
d) .90
10. Consider using the multiplication rule when simple outcomes are connected by the word
a) and.
b) if.
c) but.
d) or.