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

experiment?

Ho: mu1-mu2=0

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

higher score?

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