03. Information represented by numbers, which can be the subject of statistical analysis is a. a theory b. research c. data d. an hypothesis e. none of the above
04. A tentative answer to a research problem is a. an hypothesis b. a theory c. research d. statistics e. none of the above
Samples and Populations
07. A subset of cases from a population is a. a variable b. research c. data
*d. a sample e. none of the above
13. A group that includes all the cases in which the researcher is interested is: a. sample b. parameter
*c. population d. none of the above
14. A relatively small subset selected from a population is:
*a. sample b. statistic c. parameter d. none of the above
15. A measure such as mean or standard deviation used to describe the population distribution is: a. statistic
*b. parameter c. estimation d. none of the above

16. A measure such as mean or standard deviation used to describe the sample distribution is:
*a. statistic b. parameter c. estimation d. none of the above
17. A method of sampling that enables the researcher to specify for each case in the population the probability of its inclusion in the sample is: a. purposive sampling
*b. probability sampling c. survey d. none of the above
18. A simple random sample: a. is the most basic probability sampling design b. is purposive sampling c. is a sample designed in such a way to ensure that every member of the population has an equal chance of being selected
*d. a and c e. none of the above
19. A method of sampling in which every K-th member in the total population is chosen for inclusion in the sample after the first member of the sample is selected at random is: a. simple random sampling b. stratified sampling
*c. systematic random sampling d. none of the above
20. A method of sampling obtained by dividing the population into subgroups based on one or more variables central to our analysis and then drawing a random sample from each of the subgroups is: a. systematic random sampling b. simple random sampling
*c. stratified random sampling d. none of the above
21. A theoretical probability distribution of all possible sample values for the statistic in which we are interested is: a. probability sampling b. sampling error
*c. sampling distribution d. sample distribution e. none of the above

22. The discrepancy between a sample estimate of a population parameter and the real population parameter is: a. standard deviation b. skewness
*c. sampling error d. estimation e. none of the above
23. A theoretical probability distribution of sample means that would be obtained by drawing from the population all possible samples of the sample size is: a. sample distribution b. estimation
*c. sampling distribution of the mean d. none of the above
24. The standard deviation of the sampling distribution of the mean is
*a. standard error of the mean b. a randome sample c. always zero d. none of the above
1. Social scientists gather data from samples instead of populations because a. samples are much larger and more complete
b. samples are more trustworthy
c. populations are often too large to test
d. samples are more meaningful and interesting
3. Statistics are characteristics of samples while ________ are characteristics of
___________.
a. percentages, populations
b. medians, clusters
c. parameters, stratified samples
d. parameters, populations
4. A researcher questioned 45 incoming Freshman about their experiences drinking alcohol and used these responses to estimate the drinking behavior of the entire freshman class. In this example, the 45 interviewees were the __________ and the ___________ was the population.
a. sample, student body
b. parameters, freshman class
c. statistics, parameters
d. sample, freshman class
5. Compared to probability samples, non-probability samples a. are usually cheaper to assemble
b. are always much larger

c. are usually more expensive to assemble
d. allow for generalizations to populations
6. The goal of all techniques for selecting probability samples is to select samples that are
a. very large
b. non-random
c. easily located
d. representative
8. Unless a sample is __________, it cannot be used to make accurate generalizations to a population.
a. very large
b. non-probability
c. representative
d. stratified
12. For a simple random sample, each case and each combination of cases in the population
a. must be representative
b. must be included in the sample
c. must be contacted by the researcher
d. must have an equal probability of being chosen for the sample
13. The simple random sample requires
a. a defined population
b. a complete list of all cases in the population
c. a random selection process
d. all of the above
14. In systematic random sampling, the researcher randomly selects
a. the first case and every kth case thereafter
b. cases following any systematic pattern
c. every other case
d. cases according to their scores
15. A sampling technique that allows you to ensure proportional representativeness in a sample is
a. representative sampling
b. stratified sampling
c. systematic sampling
d. simple sampling
16. When using systematic sampling, the researcher must
a. select only representative cases
b. make sure that the list of the population is random or, at least, non-cyclical with respect to the variables of interest

c. select every case
d. select only respondents who are likely to cooperate
17. A major limitation for the application of stratified sampling is that
a. the samples so selected are not representative
b. it violates the rule of EPSEM
c. the samples are non-random
d. the exact composition of the population is often unknown
18. When a list of the population does not exist, the sampling technique most commonly used is
a. simple random
b. stratified
c. systematic
d. cluster
19. Cluster sampling often involves selecting
a. geographical areas
b. systematic stratified clusters
c. older respondents only
d. cases alphabetically
20. Results from cluster samples
a. are always representative of the population
b. are never representative of the population c. should be treated with more caution than results from simple random samples
d. should never be used to generalize to a population
21. I use the principle of EPSEM to select a sample from my church for an opinion poll.
The sample
a. is guaranteed to be representative of the population
b. has a high probability of being representative
c. should never be larger than 100
d. should be larger than the population
22. The sampling distribution links the ________ distribution to the __________ distribution.
a. stratified, EPSEM
b. statistical, empirical
c. sample, population
d. empirical, real
Independent and Dependent Variables
08. The variable to be explained is

a. the dependent variable b. the independent variable c. the explanatory variable d. b and c e. none of the above
09. The variable expected to account for the property you are trying to explain is a. the independent variable b. the dependent variable c. the explanatory variable d. data e. none of the above
12. A variable that influences or affects another variable is a. a dependent variable b. an independent variable c. a dichotomous variable d. a and b e. none of the above
14. A variable that is to be explained or predicted is a. a dependent variable b. an independent variable c. a dichotomous variable d. a and b e. none of the above
44. The dependent variable of the following statement, "An increase in the amount of crime in a neighborhood will cause neighborhood solidarity to increase," is a. neighborhood b. neighborhood solidarity c. crime d. a and c e. none of the above
45. The independent variable of the following statement, "The more similar the educational level of spouses, the more likely they are to agree on child-rearing practices," is a. spouses b. similarity of the educational level of spouses c. likelihood of agreement on child-rearing practices d. child-rearing practices e. none of the above
46. The dependent variable of the following statement, "Increasing the amount of welfare benefits will not reduce willingness to work among welfare recipients," is

a. amount of welfare benefits b. welfare recipients c. welfare recipients' willingness to work d. welfare benefits e. none of the above
47. The independent variable of the following statement, "A wife is more likely to leave an abusive marriage if she has an independent source of income than if she does not," is a. wife b. likelihood of leaving an abusive marriage c. whether or not she has an independent source of income d. independent source of income e. none of the above
48. In the following statement, "Elderly women are more likely to be housebound than elderly men," the dependent variable is a. women b. gender c. likelihood of being housebound d. age e. none of the above
Level of Measurement
13. A variable that has only two values or categories is a. a dependent variable b. an independent variable c. a dichotomous variable d. all of the above e. none of the above
15. A variable with a minimum sized unit that cannot be subdivided is a. a dependent variable b. an independent variable c. an ordinal variable d. a discrete variable e. none of the above
16. A variable that has a set of categories for the purpose of naming, labeling, or classifying the observations but does NOT have any intrinsic order is a. a nominal variable b. an ordinal variable c. an interval variable d. a continuous variable

e. none of the above
17. A variable that is measured with a fixed unit of measurement and expressed in the same unit is a. a nominal variable b. an ordinal variable c. an interval variable d. a dichotomous variable e. none of the above
18. A variable that has categories that can be put in order from low to high with an unknown differences between categories is a. a nominal variable b. an ordinal variable c. an interval variable d. a continuous variable e. none of the above
Frequency Distributions
23. The table showing the number of observations falling into the category of a variable is a. a frequency distribution b. a percentage distribution c. a cumulative frequency distribution d. a cumulative percentage distribution
24. Frequency distributions may be compiled for variables measured at which level? a. nominal b. ordinal c. interval-ratio d. all of the above
25. The table showing the percentage of observations falling into the category of a variable is a. a frequency distribution b. a percentage distribution c. a cumulative frequency distribution d. a cumulative percentage distribution
26. A table which shows the frequencies at or below the each category of a variable is a. a frequency distribution b. a percentage distribution c. a cumulative frequency distribution d. a cumulative percentage distribution

27. The major difference between frequency distributions for nominal and ordinal variables is a. the number of categories in the distribution b. the width of the intervals used to represent categories c. the order in which the categories are listed d. the headings used to label the columns
28. The table showing the percentage of observations at or below the each category of a variable is a. a frequency distribution b. a percentage distribution c. a cumulative frequency distribution d. a cumulative percentage distribution
Central Tendency, Variability
32. A skewed distribution a. is not symmetrical b. has a few extreme values on one side of the distribution c. has identical right and left tails d. a and b e. none of the above
33. Mean as a measure of central tendency can be used for a. a nominal variable b. an ordinal variable c. an interval variable d. a and c e. none of the above
34. Mode as a measure of central tendency can be used for a. a nominal variable b. an ordinal variable c. an interval variable d. all of the above e. none of the above
35. The best measure of central tendency for an interval level variable that is NOT badly skewed is a. mode b. median c. mean d. standard deviation e. none of the above

36. The best measure of central tendency for an interval level variable that is BADLY skewed is a. mode b. median c. mean d. standard deviation e. none of the above
37. The median cannot be found for variables measured at the nominal level because a. there is no central tendency b. their values cannot be ranked or ordered c. they are all representative cases d. the distribution is skewed
38. The measure of central tendency that is affected by every score in the distribution is a. the mean b. the median c. the mode d. all of the above
39. Income distributions almost always have a positive skew (since there are only a few very wealthy people). Therefore, the preferred measure of central tendency for this variable would be the a. mode b. median c. mean d. none of the above
40. Variability of a variable can be measured by a. variance b. range c. mean d. a and b e. none of the above
41. Standard deviation as a measure of variability can be used for a. a nominal variable b. an ordinal variable c. an interval variable d. a and c e. none of the above
42. The average of the squared deviations from the mean, which is used as a measure of variability of interval level variables, is a. variance

b. range c. IQV d. standard deviation e. none of the above
43. For all measures of variability, higher numeric values indicate a. greater uniformity b. greater similarity c. greater symmetry d. greater diversity
Normal Distribution
01. A normal distribution is: a. bell-shaped distribution b. symmetrical distribution c. a distribution with the mean, the median, and the mode all coinciding at its peak
*d. all of the above e. none of the above
02. The number of standard deviations that a given raw score is above or below the mean is:
*a. standard score b. alpha c. standard error d. none of the above
03. In order to transform a raw score to a z-score in a normal distribution, we have to know: a. mean b. standard deviation c. sample size
*d. a and b e. none of the above
05. A minus sign in a z-score means that: a. the mean of the raw score is less than zero
*b. the raw score is less than the mean of the distribution c. the original distribution is not normally distributed d. all of the above e. none of the above
06. A z-score of 2 means that:
*a. the raw score is 2 standard deviation larger than mean score b. the raw score is 2 standard deviation smaller than mean score

c. the mean is twice larger than standard deviation d. none of the above
07. A normal distribution represented in z-scores is:
*a. standard normal distribution b. skewed distribution c. t distribution d. none of the above
09. The mean in the original distribution corresponds to: a. a value of 1 in the standard normal distribution
*b. a value of zero in the standard normal distribution c. a value of -1 in the standard normal distribution d. none of the above
10. The standard normal distribution has: a. a mean of zero b. a standard deviation of 1
*c. all of the above d. none of the above
25. The central limit theorem states that if all possible random samples of size N are drawn from a population with a mean of M and a standard deviation of S, then as N becomes larger: a. the standard deviation of the sampling distribution of sample means becomes larger b. the sampling distribution of sample means becomes approximately normal c. the mean of sampling distribution of sample means becomes M
*d. b and c e. nono of the above
26. In order to utilize the central limit theorem: a. the population distribution must be normal
*b. the sample size should be larger than 50 cases c. the researcher has to know the population mean d. a and b e. none of the above
Estimation
27. A process whereby we select a random sample from a population and use a sample statistic to estimate a population parameter is: a. sampling b. stratification
*c. estimation d. all of the above e. none of the above

28. A sample statistic used to estimate the exact value of a population parameter is: a. confidence level
*b. point estimate c. standard error d. sampling e. none of the above
29. A range of values defined by the confidence level within which the population parameter is estimated to fall is:
*a. confidence interval b. point estimate c. variance d. none of the above
30. The likelihood, expressed as a percentage or a probability, that a specified interval will contain the population parameter is: a. variance
*b. confidence level c. confidence interval d. point estimate e. none of the above
31. If you as a researcher want to reduce the risk of error in your estimation, then you would:
*a. increase the confidence level (e.g., from 95% to 99%) b. decrease the confidence level (e.g., from 95% to 90%) c. use as many statistics as you can d. none of the above
32. In order to make a more precise estimate for the same confidence level, you would:
*a. increase the sample size b. decrease the sample size c. increase the confidence interval d. a and c e. none of the above
41. If the 95% confidence interval for income ranged from $31,573 to $37,301, the population mean could be: a. $31,573 b. $37,301 c. $34,867 d. $36,212
*e. all of the above

42. Compared to a 95% confidence interval, a 99% confidence interval will always contain:
*a. a larger range of values b. a smaller range of values c. a few additional high values d. a few additional low values
45. If CBS News reports that the average American watches the news 4.3 times a month, they are reporting: a. a sample mean b. a population mean c. a point estimate
*d. a and c e. none of the above
46. With a 95% confidence interval, we can be 95% certain that a. the sample mean falls within the specified range of values b. the point estimate is the correct value for the population mean c. the difference between the sample mean and the population mean is no more than 5% d. all of the above
*e. none of the above
Hypothesis Testing
33. A procedure that allows us to evaluate hypotheses about population parameters based on sample statistics is: a. random sampling b. theory building
*c. statistical hypothesis testing d. estimation e. none of the above
34. A research hypothesis (H1) is: a. a statement reflecting the substantive hypothesis b. a tentative answer to the research question c. always expressed in terms of population parameters
*d. all of the above e. none of the above
35. A null hypothesis (H0) is: a. a statement of "No difference" b. a contradictory statement of the research hypothesis c. always expressed in terms of sample statistics
*d. a and b e. none of the above

36. A type of hypothesis test that involves a directional hypothesis is: a. two-tailed test
*b. one-tailed test c. theory d. all of the above e. none of the above
37. A type of hypothesis test that involves a non-directional research hypothesis is a. one-tailed test b. right-tailed test c. left-tailed test
*d. two-tailed test e. none of the above
38. When a one-tailed test specifies that the population mean is greater than some specific value, we call it
*a. a right-tailed test b. a left-tailed test c. two-tailed test d. estimation e. none of the above
39. Rejection of the null hypothesis will: a. prove the null hypothesis is true b. prove the research hypothesis is true
*c. strengthen our belief in the research hypothesis d. all of the above e. none of the above
40. If a research hypothesis specifies that the population mean is not equal to some specified value, we have to do: a. one-tailed test b. left-tailed test
*c. two-tailed test d. a and b e. none of the above
43. If my reseach hypothesis stated that teenage girls were more likely to be depressed that teenage boys, my null hypothesis would be:
*a. teenage boys are just as likely to be depressed as teenage girls b. teenage boys are more likely to be depressed than teenage girls c. teenage boys are less likely to be depressed than teenage girls d. none of the above
47. The difference between the p value and alpha in a hypothesis test is

a. alpha is always larger b. alpha is always smaller
*c. alpha is always determined in advance of the test d. alpha represents the probability of the test statistic e. none of the above
48. If the p value of the test statistic is greater than alpha a. the test statistic is considered to be statistically significant b. we reject the null hypothesis c. we conclude that the research hypothesis is supported d. all of the above
*e. none of the above
49. The five steps of hypothesis testing include: a. making assumptions b. stating the research and null hypothesis and selecting alpha c. selecting the sampling distribution and specifying the test statistic d. computing the test statistic
*e. all of the above
50. Alpha is the level of probability at which the researcher is willing to a. risk making an error b. reject the null hypothesis c. decide the research hypothesis must be correct d. all of the above
*e. a and b
22. The sampling distribution links the ________ distribution to the __________ distribution.
a. stratified, EPSEM
b. statistical, empirical
c. sample, population
d. empirical, real
23. There are three distributions involved in every application of inferential statistics:
a. sample, sampling, and population
b. sample, stratification, cluster
c. EPSEM, random, probability
d. sampling, percentage, normal
26. In a sampling distribution of sample means, most of the sample means will
a. cluster around the true population value
b. be below the population mean in value
c. be above the population mean in value
d. not follow any particular pattern

27. The mean age of all college graduates is 35. If the population distribution is normal, the mean of any sampling distribution of sample mean ages of college graduates will be
a. within plus or minus 1 standard deviation of 35
b. close to 35
c. 35
d. determined by the size of the distribution
29. According to the theorems presented in Chapter 6, we can be sure that the sampling distribution is normal if
a. the population is small
b. the population is normal
c. the sample is stratified
d. the sample is normal
30. With a sample size of 75, a normal sampling distribution can be assumed if
a. the cases in the sample are homogeneous
b. the cases in the sample are heterogeneous
c. the population distribution is normal
d. the sample distribution is normal
31. I took a survey of 48 residents of the apartment complex where I live to determine their voting habits. I can only use this information to generalize to all the residents if
a. there is evidence of a normal population distribution
b. the 48 residents all have the same voting habits
c. the 48 residents are equally divided in their voting habits
d. the sample distribution is normal in shape
32. The standard error of the mean is the same thing as
a. the standard deviation of a sample
b. the standard deviation of a population
c. the standard deviation of a sampling distribution
d. the variance of a sample
33. By the theorems presented in the text, we know that the mean of a sampling distribution of sample means will be
a. the same as the population mean
b. close to the value of the sample mean
c. between the population and sample means in value
d. representative of the entire population
34. The Central Limit Theorem states that as sample size becomes large
a. the sampling distribution of sample means approaches normality
b. the sampling distribution of sample means becomes larger
c. the population distribution becomes normal d. the sample distribution becomes normal

35. According to the theorems presented in Chapter 6, we can be sure that the sampling distribution is normal if
a. the sample is large
b. the population is small
c. the sample is stratified
d. the sample is normal
36. Your sample size is 1000. It is safe to assume that
a. the shape of the sampling distribution of sample means is normal
b. the sample is representative of the population
c. the population distribution is normal
d. the sample distribution is normal
37. When we use larger samples (N > 100) we can assume a normal sampling distribution because of
a. common sense
b. the Central Limit Theorem
c. what we know about the population
d. what we know about the sample
39. The shape of the sampling distribution of sample means can be assumed to be normal when N is
a. a large percentage of the population
b. any number as long as you know the value of the population mean
c. 100 or more
d. at least twice the value of the population standard deviation
40. The purpose of inferential statistics is to acquire knowledge of the ____________ distribution from the ___________ distribution by means of the _____________ distribution
a. population, sample, sampling
b. sample, sampling, population
c. inductive, empirical, stratified
d. theoretical, empirical, theoretical
1. The central problem in the case of one sample hypothesis test is to determine
a. if a sample is random
b. if sample statistics are the same as those of the sampling distribution
c. if parameters are representative of population
d. if a sample came from a population with a certain characteristic
2. Like estimation procedures, hypothesis testing involves the risk that the sample
a. may not be representative
b. may not be biased
c. may be too large
d. may not be significant
3. Which of the following must be normally distributed in order to proceed with hypothesis testing of means and proportions?
a. the sample distribution
b. the sampling distribution
c. the population distribution

d. both the sample distribution and the population distribution
4. Which assumption must be true in order to justify the use of hypothesis testing?
a. random sampling
b. interval-ratio level of measurement
c. very large samples
d. samples have been stratified
5. To conduct a test of hypothesis with a single sample mean, we must assume
a. the sampling distribution is normal
b. random sampling
c. interval-ratio level of measurement
d. all of the above
6. The null hypothesis in the one sample case is a statement of
a. agreement with the research hypothesis
b. rejection
c. acceptance
d. no difference
7. In hypothesis testing, the _____________ is the critical assumption, the assumption which is actually tested.
a. research hypothesis
b. null hypothesis
c. assumption of a normal sampling distribution
d. assumption that the sample was randomly selected
8. The research hypothesis (H
1
) typically states what the researcher expects to find and
a. contradicts the null hypothesis
b. expands on the null hypothesis
c. modifies the null hypothesis
d. is not related to the null hypothesis
9. If we reject a null hypothesis of "no difference" at the 0.05 level
a. the odds are 20 to 1 in our favor that we have made a correct decision
b. the null hypothesis is true c. the odds are 5 to 1 in our favor that we have made a correct decision
d. the research hypothesis is true
13. A sample of people attending a professional football game average 13.7 years of formal education while the surrounding community averages 12.1. The difference is significant at the .05 level. What could we conclude?
a. the null hypothesis should be accepted
b. the research hypothesis should be rejected
c. the sample is significantly more educated than the community as a whole
d. the alpha level is too low
14. A researcher is interested in the effect that neighborhood crime watch efforts have on the crime rate in the inner city, but he is unwilling to predict the direction of the difference. The appropriate test of hypothesis would be
a. one-tailed

b. two-tailed
c. descriptive
d. symmetrical
15. Do sex education classes and free clinics that offer counseling for teenagers reduce the number of pregnancies among teenagers? The appropriate test of hypothesis would be
a. a one-tailed test
b. a two-tailed test
c. cross-sectional
d. participant observation
17. Given the same alpha level, the one-tailed test
a. makes it harder to reject the Ho
b. does not affect the probability of rejecting the Ho
c. makes it more likely that Ho will be rejected
d. is less dependable than the two-tailed test
18. A one-tailed test of significance could be used whenever
a. the researcher can predict a direction for the difference
b. the researcher feels like it
c. the null hypothesis is thought to be true
d. the alpha level exceeds 0.10
19. Comparing one- and two-tailed tests (with a constant alpha level and sample size), the probability of rejection will be higher for
a. the two-tailed test
b. the one-tailed test, if you have correctly predicted the direction of the difference
c. neither, the probability of rejection does not change
d. the test with the most conservative test statistic
21. If we reject a null hypothesis which is in fact true, we
a. have made a correct decision
b. have made a Type I error
c. have made a Type II error
d. should have used a one-tailed test
24. All other things being equal, with which of the following alpha levels would we be most likely to reject the null hypothesis?
a. .01
b. .001
c. .05
d. .10
28. Which of the following are we unlikely to know when conducting a test of hypothesis in the one sample case?
a. the sample standard deviation
b. the mean of the sample
c. the standard deviation of the population
d. the alpha level

37. Sixty percent of the respondents in a random sample drawn from a neighborhood are
Democrats. The community as a whole is 75% Democrat. The difference between sample and population has been tested and the null hypothesis has been rejected. What may we conclude?
a. a Type I error has been committed
b. a one-tailed test has been used
c. the neighborhood is significantly less likely to be Democrat
d. the difference is not significant
1. The central problem in the case of two-sample hypothesis test is to determine
a. if the samples are random
b. if sample statistics are the same as those of the sampling distribution
c. if the parameters are representative of the populations
d. if two populations differ significantly on the trait in question
2. When testing for the significance of the difference between two samples, which is the proper assumption for step 1?
a. random sampling
b. ordinal level of measurement
c. degrees of freedom are zero
d. samples are independent as well as random
3. When random samples are drawn so that the selection of a case for one sample has no effect on the selection of cases for another sample, the samples are a. dependent
b. independent
c. simple
d. systematic
4. To satisfy the requirement of independent random sampling, the researcher
a. must use only cluster sampling
b. may randomly select cases from one list of the population, then subdivide that sample
according to the trait of interest
c. may randomly select an entire neighborhood, then select any member of each family in that
neighborhood
d. must select only very small populations
6. When testing for the significance of the difference between two samples, the

null hypothesis reminds us that our interest is on differences between
a. the samples
b. the populations
c. the sampling distributions
d. the standard deviations
7. Rejection of the null hypothesis in the two-sample case implies that
a. the samples are different on the trait of interest
b. the populations from which the samples are drawn are different on the trait of interest
c. the samples are not different on the trait of interest d. the populations from which the samples are drawn are not different on the trait of interest
8. Samples of Republicans and Democrats have been tested for their level of support for welfare reform and the null hypothesis has been rejected. What may we conclude?
a. the difference is significant, there are differences between the parties on this issue
b. the difference is significant, the parties are the same on this issue
c. the difference is not significant
d. a Type I error has occurred
11. For testing the difference between two sample means, the level of measurement of the test variable is assumed to be a. nominal
b. ordinal c. interval
d. any of the above
28. The higher the alpha level, a. the lower the probability of rejecting the null hypothesis b. the larger the sample size has to be to reject the null hypothesis
c. the greater the probability of rejecting the null hypothesis
d. the more desirable the two-tailed test
31. The larger the sample size, the
a. more important the observed difference

b. more likely we are to reject the null hypothesis
c. less likely we are to reject the null hypothesis
d. lower the Z score
33. A difference between samples that is shown to be statistically significant is always
a. theoretically important
b. practically important
c. sociologically important
d. none of the above
35. If a difference between samples is not statistically significant, it is almost certainly __________. On the other hand, a statistically significant difference is not necessarily ___________.
a. important … due to random chance
b. unimportant … large
c. important … unimportant
d. unimportant … important