Deck 13: Why We Need Statistics

Question 1

Weighing the Evidence The altitude of Mt.Whitney is 4418 meters, while the altitude of Death Valley is 86 meters below sea level.The difference in their altitudes illustrates the concept of

A)central tendency.
B)probability.
C)statistical inference.
D)variability.

Answer 1

variability.

Question 2

Weighing the Evidence ____ makes statements about a population and all its samples based on sample data.

A)Power analysis
B)Replication
C)Significance testing
D)Statistical inference

Answer 2

Statistical inference

Question 3

Weighing the Evidence A ____ consists of all people, animals, or objects that share at least one characteristic in common.

A)population
B)sample
C)treatment block
D)treatment group

Answer 3

population

Question 4

Weighing the Evidence Dr.M.predicted that heart rate variability biofeedback would reduce depressive symptoms.She randomly assigned depressed patients to either receive 2 hours of heart rate variability training or 2 hours of yoga instruction and measured changes in Beck Depression Inventory scores.Since the heart rate variability group improved more than the yoga group, she

A)rejected the alternative hypothesis.
B)accepted the null hypothesis.
C)rejected the research hypothesis.
D)rejected H_0.

Question 5

Weighing the Evidence When a researcher rejects the null hypothesis, this means that the experimental results

A)are meaningful.
B)are proven.
C)are statistically significant.
D)can be replicated.

Question 6

Weighing the Evidence When a change in performance between two experimental groups is due to the independent variable, we should

A)conclude that both groups were sampled from the same population.
B)conclude that the results are accidental.
C)reject the alternative hypothesis.
D)reject the null hypothesis.

Question 7

Weighing the Evidence Statistical significance means that

A)normal variability in the dependent variable cannot account for our results.
B)the research hypothesis is true.
C)the scores for each group look like they came from the same population.
D)the variability in the dependent variable is large compared to the difference between group scores.

Question 8

Weighing the Evidence Variability refers to the

A)amount of fluctuation we see in a distribution of scores.
B)effect of the independent variable.
C)statistical significance of research findings.
D)typical score in a distribution.

Question 9

The Argument for Using Statistics Statistics are

A)numerical indexes of data characteristics.
B)objective techniques for evaluating experimental data.
C)quantitative measurements of samples.
D)all of these

Question 10

Weighing the Evidence The point of the Ms.Adams detective story is that we perform statistical tests to determine whether

A)the experimental hypothesis is true.
B)the independent variable caused changes in the dependent variable.
C)the null hypothesis is true.
D)the independent variable probably caused changes in the dependent variable.

Question 11

Weighing the Evidence Dr.L.compared the effectiveness of EEG biofeedback and stimulant medication in treating Attention Deficit Disorder with Hyperactivity.He assessed 40 teenage subjects using DSM-IV criteria and then randomly assigned them to either EEG biofeedback with stimulant medication or stimulant medication alone.The subjects were treated for 9 months and then reassessed.Since the EEG biofeedback with stimulant medication group showed greater symptom reduction than the stimulant medication only group, he

A)concluded that both groups were sampled from the same population.
B)rejected the alternative hypothesis.
C)rejected the null hypothesis.
D)rejected the research hypothesis.

Question 12

Weighing the Evidence Researchers use ____ to decide whether or not to reject the null hypothesis.

A)descriptive statistics
B)power analysis
C)statistical tests
D)summary statistics

Question 13

Weighing the Evidence Until we can determine otherwise, we assume that the

A)alternative hypothesis is true.
B)experimental hypothesis is true.
C)null hypothesis is true.
D)scores must have been sampled from different populations.

Question 14

Weighing the Evidence H₀ represents the

A)alternative hypothesis.
B)hypothesis an experimenter indirectly tests.
C)null hypothesis.
D)research hypothesis.

Question 15

Weighing the Evidence An experimenter has the greatest confidence when using a ____ to represent the larger population.

A)convenience sample
B)random sample
C)sample with unique characteristics
D)treatment block

Question 16

Weighing the Evidence The ____ hypothesis states that the performance of the treatment groups is so similar that the scores must have been sampled from the same population.

A)alternative
B)experimental
C)null
D)research

Question 17

Weighing the Evidence Students surveyed about the number of MP3s they download each week report widely diverse numbers.This pattern of results illustrates what we mean by

A)central tendency.
B)probability.
C)regression to the mean.
D)variability.

Question 18

Weighing the Evidence The Ms.Adams detective story makes the point that statistical tests allow us to

A)create an airtight case that proves the independent variable had an effect.
B)make statements about the likelihood that the independent variable had an effect.
C)prove the experimental hypothesis.
D)prove the null hypothesis.

Question 19

Weighing the Evidence Researchers directly test the ____ hypothesis.

A)alternative
B)experimental
C)null
D)research

Question 20

Weighing the Evidence When we set up statistical tests, we assume that

A)the alternative hypothesis is true.
B)the independent variable had no effect.
C)Type 1 errors are less costly than Type 2 errors.
D)variability is different within each treatment group.

Question 21

Applying Statistical Inference: An Example If an experimenter finds that the difference between two treatment groups is significant at the .05 level, then

A)the odds of obtaining this difference by chance are 95 in 100 times.
B)the probability of this treatment effect is 5%.
C)we would expect chance to produce a result this large less than 5 in 100 times.
D)we should accept the null hypothesis.

Question 22

Applying Statistical Inference: An Example All of these illustrate a directional hypothesis except:

A)Behavior therapy combined with antidepressant medication produces greater improvement in depressive symptoms than behavior therapy
Alone.
B)EEG biofeedback combined with a traditional 12-step program produces a higher abstinence rate in alcoholics than a traditional 12-step program
Alone.
C)Students experience more colds during midterms than the rest of the semester.
D)The risk of heart attack differs for patients who exercise or who are sedentary.

Question 23

Applying Statistical Inference: An Example Which criterion does an experimenter use to decide whether to accept or reject the null hypothesis?

A)beta
B)effect size
C)power
D)significance level

Question 24

Weighing the Evidence As the variability in a dependent variable ____, it becomes ____ to reject the null hypothesis.

A)increases, easier
B)increases, harder
C)decreases, harder
D)none of these

Question 25

Weighing the Evidence The results of an experiment are statistically significant when

A)the difference between group scores exceeds normal variability.
B)the difference between treatment means is large.
C)they can be replicated.
D)variability in each treatment condition is high.

Question 26

Weighing the Evidence We never directly test ____ when we evaluate the results of an experiment.

A)H₁
B)the alternative hypothesis
C)the null hypothesis
D)H₁ or the alternative hypothesis

Question 27

Applying Statistical Inference: An Example Since side effects can threaten patient lives, the developer of a new antipsychotic drug wants to minimize the risk of Type 2 error when measuring liver damage.Which level of significance should she use?

A)p < .001
B)p < .01
C)p < .03
D)p < .05

Question 28

Weighing the Evidence We are more likely to reject the null hypothesis when

A)the amount of variability in the population we sampled is low.
B)the experimental manipulation did not affect the dependent variable.
C)the sample has more variability than the population.
D)the test statistic is very small.

Question 29

Applying Statistical Inference: An Example A ____ is a set of scores that is symmetrical and bell-shaped.

A)frequency histogram
B)normal curve
C)sampling distribution
D)skewed distribution

Question 30

Applying Statistical Inference: An Example Where do most scores fall along a normal curve?

A)at the end with the longest tail
B)at the left end of the distribution
C)at the right end of the distribution
D)near the center

Question 31

Applying Statistical Inference: An Example We should select a significance level ____ in order to conduct a valid test of our hypothesis.

A)after we have collected all experimental data
B)after we have performed all statistical tests
C)based on our test statistic
D)before conducting the experiment

Question 32

Weighing the Evidence When we perform a statistical test, we evaluate

A)the internal validity of our experiment.
B)the power of our experiment.
C)whether the null hypothesis is a likely explanation for our results.
D)whether the research hypothesis is true.

Question 33

Applying Statistical Inference: An Example Typically, researchers

A)can precisely measure the degree of overlap between treatment populations.
B)expect a high degree of overlap between treatment groups when manipulation of the independent variable is effective.
C)find it easier to reject the null hypothesis when the variability of the dependent variable in the sampled population is high.
D)expect some degree of overlap between treatment populations.

Question 34

Applying Statistical Inference: An Example When we set our significance level at .01, this corresponds to the notation,

A)p < .01.
B)p = .01.
C)p ≥ .01.
D)p > .01.

Question 35

Applying Statistical Inference: An Example Many statistical tests assume that the population you have sampled is normally distributed.This means that if you could measure everyone in the population on the dependent variable,

A)the bulk of the scores would fall above the mean.
B)the distribution of scores would be symmetrical and bell-shaped.
C)the left end of the distribution would have the longest tail.
D)the right end of the distribution would have the longest tail.

Question 36

Applying Statistical Inference: An Example Which of these illustrates a directional hypothesis?

A)Cognitive Behavior Therapy is more effective in treating agoraphobia than psychoanalytic therapy.
B)Greek and independent student GPAs vary.
C)Men and women differ in manual dexterity.
D)Students who study together earn different test scores than students who study alone.

Question 37

Weighing the Evidence Statistical tests allow us to

A)determine the exact odds that the independent variable is responsible for the differences we observe between treatment groups.
B)compare the differences between treatment groups to normal variability in the dependent variable.
C)estimate the risk of committing a Type 2 error.
D)prove that the research hypothesis is true.

Question 38

Applying Statistical Inference: An Example Mercedes will reject the null hypothesis if she observes a difference between treatment conditions that is so large that it could have occurred by chance less than 1 in 100 times.The .01 value is Mercede's

A)effect size.
B)risk of committing a Type 2 error.
C)significance level.
D)statistical power.

Question 39

Applying Statistical Inference: An Example Calvin has set his alpha level at .05.He will reject the null hypothesis if he observes a difference between treatment conditions that is so large that it could have occurred by chance

A)5 in 100 times.
B)at least 5 in 100 times.
C)less than 5 in 100 times.
D)more than 5 in 100 times.

Question 40

Applying Statistical Inference: An Example Variability can be produced by experimental errors, which are fluctuations in subjects' scores produced by

A)experimenter bias.
B)extraneous variables in the experimental procedure.
C)influences on subjects not related to the independent variable.
D)all of these

Question 41

Applying Statistical Inference: An Example The risk of a Type 1 error is greatest for the ____ level of significance.

A).001
B).01
C).03
D).05

Question 42

Applying Statistical Inference: An Example Statisticians use ____ to represent the probability of committing a Type 2 error.

A)alpha
B)beta
C)1-alpha
D)1-beta

Question 43

Going Beyond Testing the Null Hypothesis Cohen persuasively argued that we should supplement probability values for rejecting the null hypothesis with

A)qualitative reports.
B)effect size.
C)confidence intervals.
D)effect size and confidence intervals.

Question 44

Applying Statistical Inference: An Example We can increase the power of a statistical test by

A)adopting a more extreme (.01 versus .05) significance level.
B)increasing beta.
C)increasing sample size.
D)selecting a nonparametric test.

Question 45

The Odds of Finding Significance As the amount of variability in a distribution of differences between sample means increases, the critical regions

A)fall closer to the center of the distribution.
B)fall farther from the center of the distribution.
C)increase in size.
D)lie closer to each other.

Question 46

Applying Statistical Inference: An Example When we change the level of significance from .05 to .01, the probability of a Type 1 error ____ and the probability of a Type 2 error

A)decreases, decreases.
B)decreases, increases.
C)increases, decreases.
D)increases, increases.

Question 47

Going Beyond Testing the Null Hypothesis Psychological Science has replaced p values with

A)confidence intervals.
B)nonparametric statistics.
C)effect size.
D)the average probability of replication.

Question 48

Applying Statistical Inference: An Example The _____ determines the significance level of an experiment.

A)experimental hypothesis
B)experimenter
C)number of degrees of freedom
D)sample size

Question 49

Applying Statistical Inference: An Example If you reject the null hypothesis when it is actually true,

A)you have committed a Type 1 error.
B)you have committed a Type 2 error.
C)you should report a significant treatment effect.
D)you should revise your level of significance.

Question 50

The Odds of Finding Significance For a two-tailed test of a hypothesis, each of the critical regions would be bounded by ___ if you chose

A).01
B).025
C).05
D).10

Question 51

Applying Statistical Inference: An Example All of these statements concerning the probability of Type 1 error are correct except:

A)The risk of Type 1 error is determined by sample size.
B)The risk of Type 1 error is equal to the significance level.
C)The risk of Type 1 error is inversely related to the risk of Type 2 error.
D)The risk of Type 1 error is represented by the Greek letter "alpha."

Question 52

Applying Statistical Inference: An Example Marty studied whether tattoos affect employer perception of job applicant responsibility.Although the independent variable (tattoo) did not really affect employer perceptions, differences in how he treated each treatment group caused him to mistakenly reject the null hypothesis.Marty's decision illustrates

A)confounding by extraneous subject variables.
B)measurement error.
C)Type 1 error.
D)Type 2 error.

Question 53

Applying Statistical Inference: An Example The significance level of an experiment is

A)chosen after the experimenter completes data collection.
B)equal to the chance of committing a Type 1 error.
C)equal to the chance of committing a Type 2 error.
D)equal to the chance of correctly rejecting the null hypothesis.

Question 54

Applying Statistical Inference: An Example A researcher discovered that antibiotic therapy is more effective in treating chronic ulcer than conventional medication.Since he knows this finding challenges conventional wisdom, he decides to use a strict evaluation criterion.The risk of committing a Type 1 error will be lowest if he chooses

A)p < .01.
B)p < .03.
C)p < .05.
D)p < .10.

Question 55

Going Beyond Testing the Null Hypothesis The Publication Manual of the American Psychological Association (2009) advocated reporting

A)probability values.
B)confidence intervals.
C)effect size.
D)all of these

Question 56

Applying Statistical Inference: An Example Donovan conducted an experiment to test the hypothesis that subjects learn words with positive connotations more quickly than words with negative connotations.Although the experimental manipulation produced a real effect, there was so much variability among subject responses that Donovan decided he could not reject the null hypothesis.Donovan's decision illustrates

A)experimental error.
B)measurement error.
C)Type 1 error.
D)Type 2 error.

Question 57

Applying Statistical Inference: An Example All of these statements about experimental error are correct except:

A)Experimental error can contribute to committing a Type 1 error.
B)Experimental error can contribute to committing a Type 2 error.
C)Experimental error can be due to experimenter behavior.
D)Experimental error can be caused by weak manipulation of the independent variable.

Question 58

Applying Statistical Inference: An Example If Mark chose a .01 significance level for his experiment and then found that the results could have occurred by chance more than 1 out of 100 times, he should

A)accept the alternative hypothesis.
B)accept the null hypothesis.
C)reject the null hypothesis.
D)report a trend towards significance.

Question 59

Applying Statistical Inference: An Example Statisticians use ____ to represent the power of an inferential test.

A)alpha
B)beta
C)1-alpha
D)1-beta

Question 60

Applying Statistical Inference: An Example We commit a Type 2 error when we

A)accept the null hypothesis when it is true.
B)fail to reject the alternative hypothesis when it is false.
C)fail to reject the null hypothesis when it is false.
D)report that our findings are significant when they are not.

Question 61

Organizing and Summarizing Data The ____ tells us whether scores are spread out a great deal or tightly clustered around the mean.

A)median
B)mode
C)range
D)variance

Question 62

Test Statistics All of these terms belong together except

A)descriptive statistics.
B)inferential statistics.
C)mean.
D)variance.

Question 63

Organizing and Summarizing Data The variance is the

A)average of the squared deviations about the mean.
B)difference between the highest and lowest scores.
C)sum of the deviations about the mean.
D)the square root of the average of the squared deviations about the mean.

Question 64

Organizing and Summarizing Data If the standard deviation of a distribution of test scores is 3 points, this means that

A)the average score was 3.
B)the average deviation score was 3.
C)three scores were above the mean and three scores were below the mean.
D)we can expect subjects in the group to deviate from the group mean by an average of 3 points.

Question 65

Organizing and Summarizing Data When your distribution of scores is 1 2 4 9 10 10, you should use the _____ to represent central tendency.

A)mean
B)median
C)mode
D)range

Question 66

Organizing and Summarizing Data To find the range of a set of scores, we calculate the

A)arithmetic average.
B)average squared deviation of scores about the mean.
C)difference between the highest and lowest scores.
D)square root of the average squared deviation of scores about the mean.

Question 67

Organizing and Summarizing Data The mean of a set of data is the

A)arithmetic average.
B)difference between the highest and lowest scores.
C)middle score in a distribution.
D)most frequent score in a distribution.

Question 68

Organizing and Summarizing Data Based on the range, which of the following sets of scores has the greatest variability?

A)3, 5, 6, 8, 10
B)1, 3, 5, 7, 9
C)0, 1, 3, 5, 18
D)14, 16, 18, 20, 22

Question 69

Organizing and Summarizing Data Two distributions that have the same variance must also have the same

A)mean.
B)median.
C)range.
D)standard deviation.

Question 70

Organizing and Summarizing Data The ____ divides a distribution of scores in half.

A)mean
B)median
C)mode
D)range