Q&A Hero

Q: 65 Given the following hypotheses, is a one-tailed or two-tailed test more appropriate?

Q: 64 A researcher has calculated power as .40. a) What does this mean? b) What is the probability that this researcher will make a Type II error if the null hypothesis is false? Explain.

Q: 63 Given the following p values, would you reject or retain the null hypothesis if you want to be 95% confident that you are not making a Type I error. a) p = .05 b) p = 1.0 c) p = .10 d) p = .025 e) p = .075

Q: 62 Give an example of a hypothesis that would be appropriate for testing with a two-tailed test.

Q: 61 Give an example of a hypothesis that would be appropriate for testing with a one-tailed test.

Q: 60 A child psychologist is interested in determining if a new type of cognitive therapy will reduce behavior problems among children with ADHD more than Ritalin will in another group of children with ADHD. a) Write an appropriate null hypothesis. b) Write an appropriate research hypothesis.

Q: 59 When testing a hypothesis, we normally retain the null hypothesis when the test statistic is smaller than the critical value.

Q: 58 When the direction of difference between the sample mean and the population mean is not specified, a two-tailed test is appropriate.

Q: 57 If the alternative hypothesis in a study is H0 > 0, a one-tailed test is called for.

Q: 56 If .05 is the rejection level, we would reject the null hypothesis if the probability of the test statistic, given that the null hypothesis is true, was .07.

Q: 55 A standard error is the value of a statistic at or beyond which the null hypothesis is rejected.

Q: 54 The probability of making a Type I error is unrelated to the probability of making a Type II error.

Q: 53 Power is the probability of making a Type II error.

Q: 52 Alpha is the probability of making a Type I error.

Q: 51 Type II error is retaining the null hypothesis when it is true.

Q: 50 Type I error is rejecting the null hypothesis when it is true.

Q: 49 Another name for sampling error is a) variability due to chance. b) error variance. c) constancy. d) both a and b

Q: 48 A Type I error has occurred if we a) reject a null hypothesis that is really false. b) retain a null hypothesis that is really false. c) retain a null hypothesis that is really true. d) reject a null hypothesis that is really true.

Q: 47 A null hypothesis is rejected when a) the differences are due to sampling error. b) the probability of finding a difference that large if the population means are equal is very low. c) the probability of finding a difference that large if the population means are equal is very high. d) the distribution is not normal.

Q: 46 The probability of NOT rejecting a null hypothesis when it is false is called? a) a Type I error b) a Type II error c) experimenter error d) method error

Q: 45 The _______ assumes all means are equal for a given measure? a) alternative hypothesis b) random hypothesis c) predicted hypothesis d) null hypothesis

Q: 44 The probability of NOT rejecting a FALSE null hypothesis is also known asa) Type II Errorb) Type I Errorc) alpha d) both b and c

Q: 43 Rejecting a true null hypothesis is known asa) Type II Errorb) Type I Errorc) alpha d) both b and c

Q: 42 After running a t-test on the mean numbers of jelly beans that men and women eat over the course of the year, I conclude that men eat significantly more jelly beans than women. If men and women actually eat the same number of jelly beans, my conclusion is a) a valid conclusion b) a Type I error c) a Type II error d) an example of power

Q: 41 A Type I error concerns a) the probability of rejecting a true null hypothesis. b) the probability of rejecting a false null hypothesis. c) the probability of not rejecting a true null hypothesis. d) the probability of not rejecting a false null hypothesis.

Q: 40 The null hypothesis is the statement that a) population means are equal. b) population means differ between groups. c) it is the hypothesis you generally hope to prove. d) exciting things are going on.

Q: 39+ Dr. Harmon expected that her neurotic patients would come significantly earlier to all scheduled appointments compared to other patients, and planned to run a one-tailed test to see if their arrival times were much earlier. Unfortunately, she found the opposite result: the neurotic patients came to appointments later than other patients. What can Dr. Harmon conclude from her one-tailed test? a) Neurotic patients came to appointments significantly later than other patients. b) Neurotic patients came to appointments significantly earlier than other patients. c) Non-neurotic patients came to appointments significantly earlier than neurotic patients. d) Neurotic patients did not come to appointments significantly earlier than other patients.

Q: 38+ A researcher was interested in seeing if males or females in large lecture classes fell asleep more during in-class videos. The null hypothesis of this study is a) males will fall asleep more than females. b) females will fall asleep more than males. c) males and females fall asleep at the same rate. d) More information is needed.

Q: 37 The value of the test statistic that would lead us to reject the null hypothesis is called a) the critical value. b) the test value. c) the rejection value. d) the acceptance value.

Q: 36+ If we erroneously conclude that motorists are more likely to honk at low status cars than high status cars, we a) have made a Type I error. b) have made a Type II error. c) would have made that conclusion 5% of the time if the null hypothesis were true. d) both a and c

Q: 35+ Another name for a one-tailed test is a a) directional test. b) non-directional test. c) uniform test. d) specific test.

Q: 34 A two-tailed test is _______ powerful than a one-tailed test if we are sure the difference is in the direction that we would have predicted. a) more b) less c) equally d) We cannot tell.

Q: 33+ When we are willing to reject the null hypothesis for any extreme outcome, we are making a a) two-tailed test. b) one-tailed test. c) singular test. d) omnibus test.

Q: 32 We would like to a) maximize the power of a test. b) minimize the probability of a Type I error. c) do both a and b d) maximize the probability of a Type II error.

Q: 31+ Which of the following pairings is correct?a) Type I; Type II:: b) Type I; Type II :: c) Type I; Type II :: d) Type I; Type II ::

Q: 30 A Type II error refers to a) rejecting a true null hypothesis. b) rejecting a false null hypothesis. c) failing to reject a true null hypothesis. d) failing to reject a false null hypothesis.

Q: 29 Sometimes we reject the null hypothesis when it is true. This is technically referred to as a) a Type I error. b) a Type II error. c) a mistake. d) good fortune.

Q: 28 The area that encompasses the extreme 5% of a distribution is frequently referred to as a) the retention region. b) the rejection region c) the decision region. d) none of the above

Q: 27+ By convention, we often reject the null hypothesis if the probability of our result, given that the null hypothesis were true, is a) greater than .95. b) less than .05. c) greater than .05. d) either b or c

Q: 26 To reject a null hypothesis for the finger tapping example in the text, we would a) calculate the probability of that result if the null hypothesis were false. b) calculate the probability of that result if the null hypothesis were true. c) compare the probabilities of that result if the null hypothesis were true and if it were false. d) reject the null hypothesis unless that subject closely resembled normal subjects.

Q: 25 In the finger tapping example in the text, we would reject the null hypothesis when a) the patient tapped too quickly. b) the patient tapped too slowly. c) the patient tapped either very quickly or very slowly. d) We would be unlikely to ever reject the null hypothesis.

Q: 24 The difference between a test comparing two means and a test comparing the frequency of two outcomes is a) the test statistics that they employ and their calculation. b) the logic behind the two different hypothesis testing procedures. c) the way we go about drawing conclusions from the tests. d) all of the above

Q: 23+ We are most likely to reject a null hypothesis if the test statistic we compute is a) very small. b) quite extreme. c) what we would expect if the null hypothesis were true. d) equal to the number of observations in the sample.

Q: 22 Most psychological research is undertaken with the hope of a) proving the null hypothesis. b) proving the alternative hypothesis. c) rejecting the null hypothesis. d) discovering ultimate truth.

Q: 21 What is a major advantage of using null hypotheses? a) The null hypothesis gives us a starting point. b) If the null hypothesis is false, that provides evidence for an alternative hypothesis. c) We have procedures for testing null hypotheses. d) all of the above

Q: 20 Whether or not we reject the null hypothesis depends on a) the probability of the result given the null hypothesis is true. b) how far the data depart from what we would expect if the null hypothesis were true. c) the size of some test statistic. d) all of the above

Q: 19+ If the data are reasonably consistent with the null hypothesis, we are likely to a) accept the alternative hypothesis. b) reject the null hypothesis. c) retain the null hypothesis. d) accept the null hypothesis.

Q: 18+ Which of the following is a statement of H1?

Q: 17+ Which of the following is most likely to represent a statement of the null hypothesis?

Q: 16 The basic reason for running an experiment is usually to a) reject the null hypothesis. b) reject the experimental hypothesis. c) reject the research hypothesis. d) find a non-significant difference.

Q: 15 The hypothesis that we are trying to support by running an experiment is often called a) the null hypothesis. b) the test hypothesis. c) the sample hypothesis. d) the research hypothesis.

Q: 14 Sampling distributions help us test hypotheses about means by a) telling us exactly what the population mean is. b) telling us how variable the population is. c) telling us what kinds of means to expect if the null hypothesis is true. d) telling us what kinds of means to expect if the null hypothesis is false.

Q: 13 The sampling distribution of the mean that you saw in the text a) resembled a normal distribution. b) was very skewed. c) had a mean that was unusually large relative to the population mean. d) had little to do with the population mean.

Q: 12+ To look at the sampling distribution of the mean we would a) calculate a mean and compare it to the standard deviation. b) calculate a mean and compare it to the standard error. c) calculate many means and plot them. d) look the sampling distribution up in a book.

Q: 11 The standard deviation of a sampling distribution is known as a) the standard error. b) the variance. c) error. d) the sampling deviation.

Q: 10 If I calculate the probability of obtaining a particular outcome when the null hypothesis is true, I must deal with a) the outcome. b) a sampling distribution. c) conditional probability. d) all of the above

Q: 9+ The central feature of all hypothesis testing procedures is a) the sample mean. b) a sampling distribution. c) a range of outcomes. d) the type of experiment we run.

Q: 8 If we were to repeat an experiment a large number of times and calculate a statistic such as the mean for each experiment, the distribution of these statistics would be called a) the distributional distribution b) the error distribution. c) the sampling distribution. d) the test outcome.

Q: 7+ The basic idea behind hypothesis testing a) depends on the kind of test you want to run. b) has little to do with whatever data you collect. c) is largely the same across a wide variety of procedures. d) is important only if you want to compare two populations.

Q: 6 We are more likely to declare two populations to be different if a) the means of our samples are very different. b) the variability of our samples is very large. c) the samples are normally distributed. d) all of the above

Q: 5+ Another name for sampling error is a) variability due to chance. b) error variance. c) constancy. d) both a and b

Q: 4 In hypothesis testing our job would be much easier if a) sample statistics accurately reflected population parameters. b) subjects didn"t vary so much from one another. c) we knew the population values. d) all of the above

Q: 3 In testing hypotheses we have to take into account a) sample means. b) random variability. c) differences from one set of data to another. d) all of the above

Q: 2 One of the problems we face when we try to draw conclusions from data is that we have to deal with a) means. b) error variance. c) population size. d) hypotheses.

Q: 1 Hypothesis testing is necessarily part of a) descriptive statistics. b) order statistics. c) test construction statistics. d) inferential statistics.

Q: 40 When two teams compete against each other, the result for Team A can be win, draw, or lose. These events are a) independent. b) exhaustive. c) joint. d) conditional.

Q: 39 We might find that 65% of women report themselves to be politically liberal, while only 52% of men report that they are liberal. The proportions would be described as a) erroneous. b) biased. c) conditional on gender. d) independent.

Q: 38 p(getting a job | knowing the manager) is the notation for the probability of a) getting a job or knowing the manager. b) getting a job and knowing the manager. c) getting a job given that you know the manager. d) getting a job and not knowing what to give the manager.

Q: 37 If a set of events contains all of the possible outcomes, it is said to be a) mutually exclusive. b) independent. c) dependent. d) exhaustive.

Q: 36+ The events most likely to be mutually exclusive are a) ages. b) club memberships. c) your sex and the sex of your siblings. d) none of the above

Q: 35 Given a normal distribution of intelligence test scores (mean=100, s.d.=15), what is the probability that someone will score between 100 and 115? a) cannot be determined b) .15 c) .68 d) .34

Q: 34+ If Brian has a 50% chance of getting a job, and that job would either be at IBM or AT&T, what is the probability that he will soon be working at IBM?a) .50 2 = .25b) .50 - p(AT&T)c) .50 - p(IBM)d) .50 p(AT&T)

Q: 33+ Which of the following events are most likely to be independent? a) your score on your biology midterm and your score on the biology final b) your mother's attitudes about religion and your father's attitudes about religion c) the sex of your cousin's first child and the sex of your cousin's second child d) your philosophy professor's opinion on the meaning of life and your subsequent opinion on the meaning of life

Q: 32 Which of the following is NOT a joint probability? a) the probability that you will have a hyperactive child who is a boy b) the probability that you will have a hyperactive child who is a girl c) the probability that your child will be hyperactive given that she is a girl d) the probability that you live near the ocean and that you enjoy sailing

Q: 31+ If I am drawing observations out of a hat while sampling with replacement, the probability of drawing a certain outcome a) remains constant across all draws. b) changes as I continue drawing objects. c) decreases as I continue to draw objects. d) none of the above

Q: 30 When we sample with replacement we a) only use subjects who have been selected on two separate occasions. b) put the outcome back in the pool before sampling again. c) hold all outcomes out of the pool once they have been drawn. d) have probabilities that change after each draw.

Q: 29+ With continuous variables we a) cannot estimate probabilities because they are undefined. b) need to speak about the probability of falling within a defined interval. c) can only speak about probabilities as subjective probabilities. d) can only calculate probabilities in whole units.

Q: 28 For which kind of variable is the ordinate of a graph labeled as "density?" a) a discrete variable b) a positively skewed variable c) a continuous variable d) an independent variable

Q: 27+ Which of the following is most likely to be a discrete variable? a) the temperature outside your window b) the number of courses you will take in college c) the length of time you can hold your breath d) the speed with which you can perform a task

Q: 26 A continuous variable is one that a) can take on any value between two specified limits. b) we cannot estimate. c) can take on a limited number of possible values. d) can take on any value between -ï‚¥ and +ï‚¥.