1 . Suppose you drew a random sample from a population where the mean is 100 . The standard error of the sampling distribution is 10 . The mean for your sample is 80 . What could you conclude about your sample?
A . The sample mean does not occur very often by chance in the sampling distribution of means and probably did not come from the given population .
B . The sample mean occurs very often by chance in the sampling distribution of means and probably did not come from the given population .
C . The sample mean does not occur very often by chance in the sampling distribution of means but probably did come from the given population .
D . The sample mean occurs very often by chance in the sampling distribution of means and probably did come from the given population .
2 . What do we call that portion of the sampling distribution in which values are considered too unlikely to have occurred by chance?
A . Region of criterion value
B . Region of critical value
C . Region of rejection
D . Critical value
3 . Suppose you take a piece of candy out of a jar, look to determine its color, then put it back into the jar before you randomly select the next piece of candy . This type of sampling is called
A . an independent event .
B . sampling with replacement .
C . a dependent event .
D . sampling without replacement .
4 . There are 26 red cards in a playing deck and 26 black cards . The probability of randomly selecting a red card or a black card is 26/52 = 0 . 50 . Suppose you randomly select a card from the deck five times, each time replacing the card and reshuffling before the next pick . Each of the five selections has resulted in a red card . On the sixth turn, the probability of getting a black card
A . has got to be low because you’ve gotten so many red cards on the previous turns .
B . has got to be high because you’ve gotten so many red cards on the previous turns .
C . is the same as it has always been if the deck is a fair deck .
D . needs to be recomputed because you are sampling with replacement .
5 . What can you conclude about a sample mean that falls within the region of rejection?
A . The sample probably represents some population other than the one on which the sampling distribution was based .
B . The sample represents the population on which the sampling distribution was based .
C . Another sample needs to be collected .
D . The sample should have come from the given population .
6 . What can we conclude when the absolute value of a z-score for a sample mean is larger than the critical value?
A . The random selection procedure was conducted improperly .
B . The sample mean is reasonably likely to have come from the given population by random sampling .
C . The sample mean represents the particular raw score population on which the sampling distribution is based .
D . The sample mean does not represent the particular raw score population on which the sampling distribution is based .
7 . When rolling a pair of fair dice, the probability of rolling a total point value of “7” is 0 . 17 . If you rolled a pair of dice 1,000 times and the point value of “7” appeared 723 times, what would you probably conclude?
A . This is not so unlikely as to make you doubt the fairness of the dice .
B . Although not impossible, this outcome is so unlikely that the fairness of these dice is questionable .
C . Since the total point value of “7” has the highest probability of any event in the sampling distribution, this is an extremely likely outcome .
D . It is impossible for this to happen if the dice are fair .
8 . What is the appropriate outcome of a z-test?
A . Reject and accept
B . Reject and accept
C . Reject ; accept
D . Fail to reject ; accept
9 . The null hypothesis describes the
A . sample statistic and the region of rejection .
B . sample statistic if a relationship does not exist in the sample .
C . population parameters represented by the sample data if the predicted relationship exists .
D . population parameters represented by the sample data if the predicted relationship does not exist .
10 . In a one-tailed test, is significant only if it lies
A . nearer µ than and has a different sign from
B . in the tail of the distribution beyond and has a different sign from
C . nearer µ than and has the same sign as
D . in the tail of the distribution beyond and has the same sign as
11 . The key difference between parametric and nonparametric procedures is that parametric procedures
A . do not require that stringent assumptions be met .
B . require that certain stringent assumptions be met .
C . are used for population distributions that are skewed .
D . are used for population distributions that have nominal scores .
12 . Which of the following accurately defines a Type I error?
A . Rejecting when is true
B . Rejecting when is false
C . Retaining when is true
D . Retaining when is false
13 . If and what is the value of
A . 2 . 58
B . 0 . 52
C . –2 . 58
D . 0 . 78
14 . What happens to the probability of committing a Type I error if the level of significance is changed from a =0.01 to a =0.05?
A . The probability of committing a Type I error will decrease .
B . The probability of committing a Type I error will increase .
C . The probability of committing a Type I error will remain the same .
D . The change in probability will depend on your sample size .
15 . Suppose you perform a two-tailed significance test on a correlation between the number of books read for enjoyment and the number of credit hours taken, using 32 participants . Your is –0 . 15, which is not a significant correlation coefficient . Which of the following is the correct way to report this finding?
A . r(32) = –0 . 15, p > 0 . 05
B . r(31) = –0 . 15, p > 0 . 05
C . r(30) = –0 . 15, p < 0 . 05
D . r(30) = –0 . 15, p > 0 . 05
16 . Which of the following would increase the power of a significance test for correlation?
A. Changing a from 0 . 05 to 0 . 01
B. Increasing the variability in the Y scores
C. Changing the sample size from N = 25 to N = 100
D. Changing the sample size from N = 100 to N = 25
17 . If a sample mean has a value equal to µ, the corresponding value of t will be equal to
A . +1 . 0 .
B . 0 . 0 .
C . –1 . 0 .
D . +2 . 0 .
18 . What is ?
A . The estimated population standard deviation
B . The population standard deviation
C . The estimated standard error of the mean
D . The standard error of the mean
19 . In a one-tailed significance test for a correlation predicted to be positive, the null
hypothesis is ___________ and the alternative hypothesis is __________ .
A. Ho: ρ ≤ 0; Ha: ρ > 0
B. Ho: ρ < 0; Ha: ρ ≥ 0
C. Ho: ρ = 0; Ha: ρ > 0
D. Ho: ρ < 0; Ha ρ > 0
20 . How is the t-test for related samples performed?
A . By conducting a one-sample t-test on the sample of difference scores
B . By conducting an independent samples t-test on the sample of difference scores
C . By converting the scores to standard scores and then performing a related samples t-test
D . By measuring the population variance and testing it using an independent samples t-test
21 . What does the alternative hypothesis state in a two-tailed independent samples
22 . One way to increase power is to maximize the difference produced by the two conditions in the experiment . How is this accomplished?
A . Change a from 0 . 05 to 0 . 01 .
B . Change the size of N from 100 to 25 .
C . Design and conduct the experiment so that all the subjects in a sample are treated in a consistent manner .
D . Select two very different levels of the independent variable that are likely to produce a relatively large difference between the means .
23 . Suppose you perform a two-tailed independent samples t-test, using a = 0 . 05, with 15 participants in one group and 16 participants in the other group . Your is 4 . 56, which is significant . Which of the following is the correct way to report this finding?
A . t(31) = 4 . 56; p< 0 . 05
B . t(29) = 4 . 56; p < 0 . 05
C . t(29) = 4 . 56; p > 0 . 05
D . t(29) = 4 . 56; p = 0 . 05
24 . Suppose that you measure the IQ of 14 subjects with short index fingers and the IQ
of 14 subjects with long index fingers . You compute an independent samples t-test,
and the is 0 . 29, which is not statistically significant . Which of the following is the
most appropriate conclusion?
A . There is no relationship between length of index finger and IQ .
B . There is a relationship between length of index finger and IQ .
C . The relationship between length of index finger and IQ does not exist .
D . We do not have convincing evidence that our measured relationship between length of index finger and IQ is due to anything other than sampling error .
25 . The assumptions of the t-test for related samples are the same as those for the test for independent samples except for requiring
A . that the dependent variable be measured on an interval or ratio scale .
B . that the population represented by either sample form a normal distribution .
C . homogeneity of variance .
D . that each score in one sample be paired with a particular score in the other sample .
Use SPSS and the provided data set to answer the questions below:
26 . Test the age of the participants (AGE1) against the null hypothesis H 0 = 34 . Use a
one-sample t-test . How would you report the results?
A . t = -1 . 862, df = 399, p > . 05
B . t = -1 . 862, df = 399, p < . 05
C . t = 1 . 645, df = 399, p > . 05
D . t = 1 . 645, df = 399, p < . 05
27 . Test to see if there is a significant difference between the age of the participant and the age of the partner . Use a paired-sample t-test and an alpha level of 1% . How would you interpret the results of this test?
A . The partners are significantly older than the participants .
B . The partners are significantly younger than the participants
C . The age of the participants and partners are not significantly different .
D . Sometimes the partners are older, sometimes the participants are older .
28 . Look at the correlation between Risk-Taking (R) and Relationship Happiness (HAPPY) . Use the standard alpha level of 5% . How would you describe the relationship?
A . The relationship is non-significant .
B . There is a significant negative relationship .
C . There is a significant positive relationship .
D . The correlation is zero .
29 . If you randomly chose someone from this sample, what is the chance that they
described their relationship as either Happy or Very Happy?
A . 32%
B . 37%
C . 56%
D . 69%
30 . Perform independent sample t-tests on the Lifestyle, Dependency, and Risk-Taking
scores (L, D, and R) comparing men and women (GENDER1) . Use p < . 05 as your
alpha level . On each of the three scales, do men or women have a significantly
A . Lifestyle: Men, Dependency: Women, Risk-Taking: Men .
B . Lifestyle: Not significantly different, Dependency: Women, Risk-Taking: Men
C . Lifestyle: Women, Dependency: Women, Risk-Taking: Men
D . Lifestyle: Men, Dependency: Men, Risk-Taking: Not significantly different