Statistics Homework | HomeworkDoers

Question 2

In a distribution that is skewed by a few extreme outliers, what would be the best choice for a measure of central tendency?

median

mode

mean

range

1 points

Question 3

In a physical geography course, the average score on the first exam across all sections of the course was 77.63%. Because all students were included in the calculation, the mean is assumed to be based on population data. The test average may be considered to be a:

measure of variability.

statistic.

parameter.

mode.

1 points

Question 4

The mean is the number that perfectly balances the:

		number of scores in the data set, such that half fall above the mean and half fall below.
		the scores around the mean, such that the sum of the deviations for scores above the mean exactly equals the sum of the deviations for scores below the mean.
		two most extreme scores in the data set.
		even and the odd scores in the data set.

1 points

Question 5

This table represents the fictional scores of a set of dieters who answered the question “how many times in a week would you estimate you hide your eating behavior (e.g., sneak food, eat in private, under-report consumption).”

Table: Hidden Eating Behaviors

X

Rating

6

9

5

2

4

5

3

7

2

3

1

21

Reference: Table 5

(Table: Hidden Eating Behaviors) The median reported acts of hiding eating is:

6.0.

5.0.

7.0.

5.5.

1 points

Question 6

Sixteen college freshmen were asked to record the number of alcoholic drinks that they typically consume in a week. Here are their data: 2, 4, 6, 0, 1, 10, 9, 0, 6, 3, 6, 8, 5, 4, 6, 2. What is the median number of alcoholic drinks consumed per week?

4.0

4.5

5.0

5.5

1 points

Question 7

This table represents the fictional ages of a set of participants who participated in a research study.

Table: Age

X

Age

9

33

8

41

7

40

6

38

5

42

4

39

3

16

2

44

1

33

Reference: Table 3

(Table: Age) The standard deviation in this data set is:

22.15.

6.56.

8.45.

7.97.

1 points

Question 8

The following source table depicts partial results of a fictional study investigating whether students’ stress levels vary as a function of the type of residence they inhabit (house, apartment, dorm room) and the noise volume to which they are subjected (soft, medium, loud). Six participants were recruited for each cell of the study.

Table: Residence and Noise

Source
SS

df

MS

F

Residence
7.64

2

Noise
2

1.11

Residence × Noise

Within
14.36

0.319

Total
27.84

Reference: Table 4

(Table: Residence and Noise) Using the source table and information provided, the critical cutoff for both main effects is ___________ while the critical cutoff for the interaction is _____________.

2.58; 3.21

3.21; 2.58

3.21; 3.21

3.58; 3.58

1 points

Question 9

The following source table depicts partial results of a fictional study investigating whether students’ stress levels vary as a function of the type of residence they inhabit (house, apartment, dorm room) and the noise volume to which they are subjected (soft, medium, loud). Six participants were recruited for each cell of the study.

Table: Residence and Noise

Source
SS

df

MS

F

Residence
7.64

2

Noise
2

1.11

Residence × Noise

Within
14.36

0.319

Total
27.84

Reference: Table 4

(Table: Residence and Noise) Using the source table and information provided, calculate the F statistic for the main effect of residence type.

2.84

3.48

11.98

6.84

1 points

Question 10

The following figure reflects the results of a study by Forys and Dahlquist (2007) investigating the effects of coping style and cognitive strategy on dealing with pain. Participants were first classified as having a monitoring or avoiding coping style. They were then randomly assigned to one of two cognitive strategy conditions, distraction or sensation monitoring. Participants were next instructed to use the cognitive strategy while submerging their hand in ice water. The researchers measured pain tolerance as the number of seconds participants were able to keep their hand in the ice water.

Figure: Strategies for Dealing with Pain

Reference: Figure 2

(Figure: Strategies for Dealing with Pain) The figure reflects a main effect of cognitive strategy. Which statement best describes the main effect?

		People using both distraction and sensation-monitoring cognitive strategies were able to keep their hand in the ice water for longer than 60 seconds, on average.
		People using a sensation-monitoring strategy were able to keep their hand in the ice water for longer.
		People using a distraction strategy were able to keep their hand in the ice water for longer.
		The effect of cognitive strategy depended on the coping style of the participant. People with an avoiding coping style kept their hand in the ice water longer when using a distraction strategy, but those with a monitoring coping style kept their hand in the ice water longer when using a sensation-monitoring strategy.

1 points

Question 11

The following source table depicts partial results of a fictional study investigating whether students’ stress levels vary as a function of the type of residence they inhabit (house, apartment, dorm room) and the noise volume to which they are subjected (soft, medium, loud). Six participants were recruited for each cell of the study.

Table: Residence and Noise

Source
SS

df

MS

F

Residence
7.64

2

Noise
2

1.11

Residence × Noise

Within
14.36

0.319

Total
27.84

Reference: Table 4

(Table: Residence and Noise) Using the source table and information provided, calculate the degrees of freedom for the interaction.

2

4

45

53

1 points

Question 12

The following figure reflects the results of a study by Forys and Dahlquist (2007) investigating the effects of coping style and cognitive strategy on dealing with pain. Participants were first classified as having a monitoring or avoiding coping style. They were then randomly assigned to one of two cognitive strategy conditions, distraction or sensation monitoring. Participants were next instructed to use the cognitive strategy while submerging their hand in ice water. The researchers measured pain tolerance as the number of seconds participants were able to keep their hand in the ice water.

Figure: Strategies for Dealing with Pain

Reference: Figure 2

(Figure: Strategies for Dealing with Pain) The figure reflects a main effect of coping style. Which statement best describes the main effect?

		People with monitoring and avoiding coping styles were able to keep their hand in the ice water for longer than 60 seconds, on average.
		People with an avoiding coping style were able to keep their hand in the ice water for longer.
		People with a monitoring coping style were able to keep their hand in the ice water for longer.
		The effect of coping style depended on the cognitive strategy employed. People with an avoiding coping style kept their hand in the ice water longer when using a distraction strategy, but those with a monitoring coping style kept their hand in the ice water longer when using a sensation-monitoring strategy.

1 points

Question 13

A researcher performs a 3 x 5 ANOVA examining how preferences for engagement with friends varied as a function of age (20, 30, or 40 year olds) and social media tools (Facebook, Twitter, LinkedIn, Google+, Instagram) with 26 participants in each cell of the study design. What is the degrees of freedom for the variable age?

1

2

3

4

1 points

Question 14

The following source table depicts partial results of a fictional study investigating whether students’ stress levels vary as a function of the type of residence they inhabit (house, apartment, dorm room) and the noise volume to which they are subjected (soft, medium, loud). Six participants were recruited for each cell of the study.

Table: Residence and Noise

Source
SS

df

MS

F

Residence
7.64

2

Noise
2

1.11

Residence × Noise

Within
14.36

0.319

Total
27.84

Reference: Table 4

(Table: Residence and Noise) Using the source table and information provided, calculate the total degrees of freedom.

42

54

45

53

1 points

Question 15

A researcher performs a 3 x 5 ANOVA examining how preferences for engagement with friends varied as a function of age (20, 30, or 40 year olds) and social media tools (Facebook, Twitter, LinkedIn, Google+, Instagram) with 26 participants in each cell of the study design. Using alpha of 0.05 and the closest values on the table in our textbook, what is the critical cutoff for the test of age?

3.04

2.42

2.14

4.71

1 points

Question 16

A type of scatterplot that indicates only the range of the actual data on each axis is a:

time series plot.

range-frame.

simple scatterplot.

histogram.

1 points

Question 17

Figure: Class Rank

Reference: Table 1

(Figure: Class Rank) From this graph, we know with certainty that a person with a class rank of 60 in the freshman year would have a class rank of 60 in his or her senior year. This statement is an example of a(n):

false face validity lie.

sneaky sample lie

interpolation lie.

change the interval lie.

1 points

Question 18

If you were graphing one scale independent variable and one scale dependent variable, you would use a:

scatterplot or line graph.

Pareto chart.

histogram or frequency polygon.

bar graph.

1 points

Question 19

If we have one nominal independent variable and one scale dependent variable, what type of graph should we use?

histogram or frequency polygon

frequency polygon

bar graph or Pareto chart

bar graph

1 points

Question 20

Data about text messaging shows that people 15–25 years old text at very high rates, while people 45–55 years old text less frequently. If there is no data about people in the range of 26–44 years old, why is it not safe to just infer that their rates will be between the other two?

		We cannot assume that missing data will fall along a straight line between existing data points. This is the lie of interpolation.
		It is not safe to extrapolate from the two known observations to a new age range about which we have not collected any data.
		The sample of participants in one group might be biased and we don’t want to base an inference on biased data.
		We can indeed infer that rates of texting for 26–44 year olds will be between the other two rates.

1 points

Question 21

Graphs, also called figures in APA style, that follow standards of appropriate design help to:

persuade an audience.

tell the story of data.

modify the data to prove the hypothesis.

edit the data.

1 points

Question 22

According to the text, pie charts are:

preferred by researchers.

often used in research.

better at presenting data than other charts.

very limited.

1 points

Question 23

When Cohen’s d is large (based on Cohen’s conventions), the amount of overlap between the two distributions being compared is ________%.

75

53

15

0

1 points

Question 24

If a researcher performs a meta-analysis and finds that the mean d = 0.11, and that the 95% confidence interval around this mean is (–0.04, 0.26), what could the researcher conclude?

		The researcher can conclude that all future studies of this effect will find effect sizes somewhere between -0.04 and 0.26.
		Because the confidence interval includes 0, there really is no evidence of an effect, on average, in the literature.
		There is a strong effect, but it is unclear what the direction of the effect is.
		Averaging across all of the literature, there is a strong effect, and this effect is statistically significant.

1 points

Question 25

If you are correct about the expected direction of an effect, then using a one-tailed hypothesis test instead of a two-tailed hypothesis test:

increases power.

decreases power.

makes power 1.0.

makes power 0.

1 points

Question 26

An overlap between two distributions of approximately 39% is most likely to result in a(n) ________ effect size.

small

medium

large

unconventional

1 points

Question 27

According to Cohen’s convention, a value of ________ is a large effect size.

0.2

0.5

0.8

340

1 points

Question 28

We calculate a statistical power and find that it is 0.61. This means that if the null hypothesis is ________, we have a ________% chance of rejecting the null hypothesis.

false; 39

false; 61

true; 39

true; 61

1 points

Question 29

Hypothesis testing alone may oversimplify results. All but one of the following is a way to enhance our analysis:

increases in standard error

confidence intervals

effect size calculations

statistical power analyses

1 points

Question 30

Statistical convention for the minimal acceptable power is:

0.95.

0.75.

0.90.

0.80.

1 points

Question 31

Which of the following formulas for calculating the subjects sum of squares for a within-groups ANOVA is correct?

Σ(M_participant – GM)²

Σ(M_participant – X)²

Σ(M)(n – 1)

Σ(M_participant – GM)

1 points

Question 32

Which F statistic represents a new calculation as part of the within-groups ANOVA?

F_between

F_within

F_subjects

F_total

1 points

Question 33

Within-groups degrees of freedom is calculated by:

		subtracting 1 from the total number of groups in the study.
		multiplying the number of subjects by the number of conditions in the study and then subtracting 1.
		subtracting 1 from the total number of subjects in the study.
		for each condition, subtracting 1 from the number of subjects in that group and then adding together the totals for all the groups.

1 points

Question 34

The one-way within-groups design can be viewed as an extension of what other research design because of its ability to analyze data from more groups?

independent-samples t test

paired-samples t test

Tukey HSD test

between-groups ANOVA

1 points

Question 35

The ________ sum of squares is unique to the within-subjects design.

between-groups

within-groups

total

subjects

1 points

Question 36

In addition to hypothesis testing, post-hoc tests are required as a way to assess:

		the power of the statistical analysis.
		the number of subjects needed to correctly reject the null hypothesis.
		where the significant differences exist among groups.
		whether the significant differences found are large enough to matter.

1 points

Question 37

Because of their benefits in reducing variability, what types of designs are always preferred?

between-groups designs

post-hoc designs

within-groups designs

correlational designs

1 points

Question 38

The Bonferroni, Scheffé, and Tukey are all examples of:

hypothesis tests.

post-hoc tests.

effect size statistics.

confidence intervals.

1 points

Question 39

Imagine that you’ve just read the results of a study that finds a positive correlation between gum chewing and life expectancy. Which of the following statements would be a statistically appropriate response to the results of the study?

		You purchase a lifetime supply of gum because chewing gum is good for your health.
		You bemoan the possibility of living so long that you will have to chew lots of gum.
		You become curious about what third variables might cause both increases in gum chewing and increases in life expectancy.
		You tell all your friends and family members to chew gum because it is good for their health.

1 points

Question 40

The Pearson correlation coefficient is a statistic that:

		measures the causal association between scale variables.
		measures association between scale, ordinal and nominal variables.
		quantifies a linear relation between two scale variables.
		quantifies relatedness in terms of variability between variables.

1 points

Question 41

When the data in a scatterplot form an overall pattern through which it would make sense to draw a straight line, the relationship is said to be:

curvilinear.

uncorrelated.

linear.

causal.

1 points

Question 42

The model of possible causal explanations for a correlation is called the:

1-2-3 model.

A-B-C model.

cause-and-effect model.

causal explanation model.

1 points

Question 43

Which of the following values of the correlation coefficient indicates the weakest relationship between two variables?

0.42

–0.30

–0.87

0.03

1 points

Question 44

A perfect linear relationship will yield a Pearson’s r value of:

1.00.

–1.00.

0.

1.00 or –1.00.

1 points

Question 45

Before calculating the correlation coefficient, it is advisable to create a ________ as a way of displaying the association between the two variables.

scatterplot

line graph

histogram

polygon

1 points

Question 46

Psychometricians are concerned with:

developing high quality tests and measures.

fixing psychological issues in people.

studying illness and the onset of psychological illness.

statistics and computers.

1 points

Question 47

The subscript M included in the symbols, µ_M and σ_M, indicates that

		the mean is the subject.
		the values are population parameters.
		the values are measures for the sampling distribution of the mean.
		the mean of the distribution of means is being presented .

1 points

Question 48

Imagine that we know the following information for populations living in cities and rural areas. In big cities, average commutes are 40 minutes with a standard deviation of 15 minutes. In rural areas, the average commute is 25 minutes with a standard deviation of 6 minutes.
Imagine Kris from the city travels 10 minutes to get to work and Rich from the country travels 34 minutes. Which commute is more unusual?

		Kris’s, because her commute is so short.
		Rich’s, commute because it is 1.5 standard deviations above average.
		Rich’s, because it is rare for people in the country to have such a long commute.
		Kris’s, commute because it is 2 standard deviations below average.

1 points

Question 49

The normal curve is:

unimodal, symmetric, and defined mathematically.

bimodal, symmetric, and defined.

multimodal and asymmetric.

mathematically defined, bimodal, and symmetric.

1 points

Question 50

The pattern of data that is symmetric around a midpoint and fairly accurately predicts reality is called a:

bell.

skewed distribution.

normal curve.

standardized distribution.

1 points

Question 51

The z-score distribution ________ has a mean of ________.

always; 0

sometimes; 0

always; 1

sometimes; 1

1 points

Question 52

The distribution of means based on samples of size 45, pulled from a population distribution with a mean of 100 and a standard deviation of 15, would have a standard error of:

2.24.

3.00.

25.82.

4.50.

1 points

Question 53

When creating a distribution of means, it is important that whatever scores are sampled to compute the means are:

		replaced back into the population for additional sampling.
		separated out from the population so that they cannot be re-sampled.
		recorded in order to create a distribution of scores.
		balanced across the mean so that extreme scores are controlled.

1 points

Question 54

What research technique is crucial to drawing the conclusion that the independent variable caused the change in the dependent variable?

random selection

random assignment to groups

double-blind experiment

quasi-experiment

1 points

Question 55

When you read your college textbooks, you may sometimes find errors in them. If you track the number of errors based on the edition of the textbook, you might find that first editions have more errors than third, fifth, and tenth editions. What kind of variable is the number of errors found?

nominal

ordinal

scale

independent

1 points

Question 56

A weight-management researcher was interested in whether the size of breakfast could deter overall food consumption throughout the rest of the day. He creates two breakfast groups, a 350-calorie breakfast and a 750-calorie breakfast, assigns six participants to each group and tracks their total calories eaten in one day. Because of the detailed attention needed to accurately interview participants about their eating, he works with the high-calorie group and has his assistant interview the low-calorie group. What is the dependent variable in this study?

total calories consumed

the low- and high-calorie breakfasts

weight loss experienced in the day

the researcher conducting the interviews

1 points

Question 57

The outcome variable that we expect to change with changes in the independent variable is the ________ variable.

confounding

noise

dependent

extraneous

1 points

Question 58

Wendy is a Weight Watchers group leader. To get a better idea of how to help those she will be working with to achieve their weight-loss goals, she wishes to know the average weight-loss goal of the individuals in her group. What kind of statistic should Wendy use?

reliability

population

inferential

descriptive

1 points

Question 59

A researcher wanted to determine whether eating Pop-Tarts for breakfast increased the aggression of second graders during their morning play period. After feeding a group of 20 students Pop-Tarts for breakfast she observed that, on average, the students committed 4.5 aggressive behaviors during their morning play period. In this example, the sample is:

the 4.5 aggressive behaviors.

the 20 students the researcher observed.

all second graders.

all second graders who ate Pop-Tarts for breakfast.

1 points

Question 60

A researcher wanted to determine whether eating Pop-Tarts for breakfast increased the aggression of second graders during their morning play period. After feeding a group of 20 students Pop-Tarts for breakfast she observed that, on average, the students committed 4.5 aggressive behaviors during their morning play period. In this example, the descriptive statistic is:

the 4.5 aggressive behaviors.

the 20 students the researcher observed.

all second graders.

all second graders who ate Pop-Tarts for breakfast.

1 points

Question 61

Rather than considering a long list of body weights for all women studied by the Centers for Disease Control and Prevention, the CDC might report a single number. This is known as a:

inferential statistic.

sample.

population.

descriptive statistic.

1 points

Question 62

This polygon represents a fictional distribution of scores.

Figure: Frequency Polygon

Reference: Figure 3

(Figure: Frequency Polygon) Based on the frequency distribution, how many participants scored between 1 and 3?

2

3

3.5

18

1 points

Question 63

This table represents the fictional scores of a set of participants who rated their happiness on a scale from 1 to 7, with 1 indicating very unhappy and 7 indicating very happy.

Table: Happiness

X

F

7

3

6

5

5

11

4

10

3

2

2

1

1

2

Reference: Table 1

(Table: Happiness) How many participants did not rate their happiness as either 4 or 5?

16

13

32

11

1 points

Question 64

This polygon represents a fictional distribution of ages for speed-daters. The researcher wanted to know how many people in their 20s attended such events. The polygon shows the number of people ranging in age from 20 to 29.

Figure: Speed-Daters in Their 20s

Reference: Figure 4

(Figure: Speed-Daters in Their 20) What seems to be the shape of the distribution of speed-daters in their 20s?

symmetrical

negatively skewed

neutral

positively skewed

1 points

Question 65

This table shows tests scores for a cumulative final exam in a general education, social science course, such as introduction to psychology.

Table: Test Scores

Interval Frequency

90–99

23

80–89

41

70–79

78

60–69

36

50–59

18

40–49

7

30–39

12

20–29

3

Reference: Table 4

(Table: Test Scores) If passing is a 60% or higher, what percentage of the class failed this test?

15.39

19.11

26.12

18.34

1 points

Question 66

Researchers often want to understand individual variables and the values observed. Rather than examining a long list of numbers, they might consider organizing and displaying the values using a:

scale variable.

raw data sorter.

inferential model.

frequency distribution.

1 points

Question 67

This table represents the fictional scores of a set of participants who rated their level of depression on a scale from 0 to 10, with 0 indicating no feelings of depression and 10 indicating very depressed.

Table: Depression

Score	Frequency	Percent
10	1	2.86
9	6	17.14
8	1	2.86
7	1	2.86
6	4	11.43
5	2	5.71
4	1	2.86
3	1	2.86
2	11	31.43
1	5	?
0	2	5.71

Reference: Table 2

(Table: Depression) How many participants reported their level of depression at 5 or above?

		15
		11
		31
		19

1 points

Question 68

This table shows summer salaries for some hypothetical college students.

Table: Summer Salaries

Interval

Frequency

6000–6999

6

5000–5999

19

4000–4999

31

3000–3999

66

2000–2999

52

1000–1999

24

0–999

13

Reference: Table 5

(Table: Summer Salaries) What kind of frequency distribution is this?

histogram

grouped frequency table

frequency polygon

frequency table

1 points

Question 69

This table represents the fictional scores of a set of participants who rated their level of depression on a scale from 0 to 10, with 0 indicating no feelings of depression and 10 indicating very depressed.

Table: Depression

Score	Frequency	Percent
10	1	2.86
9	6	17.14
8	1	2.86
7	1	2.86
6	4	11.43
5	2	5.71
4	1	2.86
3	1	2.86
2	11	31.43
1	5	?
0	2	5.71

Reference: Table 2

(Table: Depression) How many participants rated their depression levels?

		10
		44
		35
		100

1 points

Question 70

A duplication of scientific results in a different context or with a different sample is:

grounds for dismissal from most academic institutions.

plagiarism.

replication.

generalizability.

1 points

Question 71

Which of the following are independent events?

		chance of winning three hands of poker in a row
		drawing two cards from a deck of cards without placing either back in the deck
		opinions of two friends on the latest summer blockbuster
		sexual satisfaction of spouses who are married to each other

1 points

Question 72

Brent tosses a quarter 4 times and 3 times it comes up heads. The proportion of heads is:

3/4.

75%.

2/4.

50%.

1 points

Question 73

Dr. Baker designed an experimental study to assess potential differences between science students and art students on a math reasoning abilities test. Dr. Baker found a mean difference in math performance between science and art students. On average, art students performed higher on the math reasoning test compared to the science students. Dr. Baker’s findings support which hypothesis?

research hypothesis

null hypothesis

statistical hypothesis

experimental hypothesis

1 points

Question 74

A(n) ________ refers to the result of a(n) ________.

success; failure

failure; trial

trial; outcome

outcome; trial

1 points

Question 75

Without many trials, we cannot determine true probabilities of events. However, over the long run, and numerous trials, the expected relative-frequency of events is very clear and predictable. This is known as the:

independence of trials.

law of large numbers.

long-run probability calculation.

objective probability.

1 points

Question 76

________ refers to the occurrence of events over the long run, and _______ refers to the calculation of the number of successes divided by the number of trials.

Proportion; percentage

Percentage; proportion

Probability; percentage

Probability; proportion

1 points

Question 77

If the standard deviation for a population, as estimated from a sample, is s = 5.6, then the standard error for a sample size of N = 16 is:

s_M = 1.40.

s_M = 0.35.

s_M = 1.45.

s_M = 0.37.

1 points

Question 78

A researcher collects 15 data points that yield a mean of 9.164 and a standard deviation (based on N – 1) of 2.377. If he is comparing the sample to a population mean of 10.6 using a single-sample t test, what would he find for the effect size?

1.21

–3.44

–0.60

0.07

1 points

Question 79

A researcher studies 45 volunteer citizens from a small community and asks them about the amount of caffeine (in milligrams) they ingest before and after lunch each day. Two measures are taken from each participant for a total of 90 data points. The degrees of freedom for this paired-samples study are:

89.

90.

44.

45.

1 points

Question 80

Assume we know the following for a paired-samples t test: N = 9, M_difference = 13.19, s = 22.3. What are the critical cutoffs for a two-tailed test with alpha of 0.05?

-2.306 and 2.306

-2.306 or 2.306

-2.262 and 2.262

-2.262 or 2.262

1 points

Question 81

When conducting a paired-samples t test, we can assess the practical importance of our obtained results by calculating:

a hypothesis test.

an effect size measure.

post-hoc tests.

a confidence interval.

1 points

Question 82

When conducting a paired-samples t test, we compare our sample mean difference to:

a distribution of mean differences.

sample means.

differences between means.

the t distribution.

1 points

Question 83

Assume we know the following for a paired-samples t test: N = 19, M_difference = 13.19, s = 22.3. Calculate the effect size using Cohen’s d.

0.59

0.22

0.41

2.58

1 points

Question 84

When performing a single-sample t test, an effect size of 0.80 would be interpreted as a:

small effect.

medium effect.

large effect.

negligible effect.

1 points

Question 85

We reject the null hypothesis if the test statistic

is not beyond the critical cutoff

falls near the center of the distribution

meets the assumptions of the hypothesis test

is beyond the critical cutoff

1 points

Question 86

When attempting to find a percentage associated with a z score, the first step involves a ________ to ________ transformation.

z score; raw score

raw score; z score

standard error; z score

z score; standard error

1 points

Question 87

In one statistics course, students reported studying an average of 9.92 hours a week, with a standard deviation of 4.54. Treating this class as the population, what percent of students study more than 8 hours?

83.35

66.28

56.84

34.72

1 points

Question 88

Because of the principle of ________, when sample sizes are at least 30, the distribution will most likely resemble a normal distribution.

parametric statistics

nonparametric statistics

central limit theorem

robustness

1 points

Question 89

If the percentage of scores falling between the mean and a z score of -1.14 is 37.29, then what is the percentage of scores falling between the mean and a z score of 1.14?

12.71

37.29

52.71

87.29

1 points

Question 90

What are the consequences of succeeding in meeting all the assumptions of a parametric test when performing research?

		We can then go on to perform the appropriate nonparametric follow-up test.
		Whether we succeed in meeting all the assumptions of a parametric test really has no bearing on the results of the research study.
		A research study that meets all the assumptions of the parametric test used to analyze the data produces higher-quality results than does a research study that fails to meet some of the assumptions.
		A research study that meets all the assumptions of the parametric test used to analyze the data produces lower-quality results than does a research study that fails to meet some of the assumptions.

1 points

Question 91

The phrase “statistically significant” does not mean

		that the finding is important or meaningful.
		that we found something in our data.
		our test statistic fell in the critical cutoff region.
		the probability of our test statistic was less than alpha.

1 points

Question 92

In one statistics course, students reported studying an average of 9.92 hours a week, with a standard deviation of 4.54. Mark studies 16 hours per week. What percent of students study more than Mark?

9.01

10.89

18.02

22.64

1 points

Question 93

To determine our critical values or cutoffs for an independent-samples t test, we use:

degrees of freedom for group 1.

degrees of freedom for group 2.

N – 1.

degrees of freedom total.

1 points

Question 94

Similar to what Stella Cunliffe did at Guinness, we can “de-bias” experiments by:

		knowing the mean and standard deviation of the population.
		estimating variability using a correction in the denominator.
		using random assignment to levels of the independent variable.
		collecting data from large volunteer samples.

1 points

Question 95

To calculate a confidence interval for an independent-samples t test, we use the:

difference between means.

difference between medians.

mean of the first group only.

mean of the second group only.

1 points

Question 96

Independent-samples t tests are also called:

dependent-samples t tests.

correlational-samples t tests.

between-samples t tests.

standardized-samples t tests.

1 points

Question 97

________ is a weighted average of the two estimates of ________.

Pooled variance; variance

Variance; pooled variance

Pooled variance; standard deviation

Standard deviation; pooled variance

1 points

Question 98

An independent-samples t test was conducted to compare gas expenses of diesel truck owners to owners of regular gas trucks. Imagine the mean gas consumption in one week amounted to $68 for diesel trucks and $84 for regular gas trucks. Imagine also that values were calculated for s_difference of 6.9, 21.74 for pooled variance, and 82 for degrees of freedom total. Around which value would we center the confidence interval?

-14.01

-29.73

-2.27

-16

1 points

Question 99

Following are the results of an independent-samples t test: t(18) = –2.11, p < 0.05. In the current example, the degrees of freedom are:

–2.11.

18.

17.

0.05.

1 points

Question 100

Why is it necessary to use the pooled variance when conducting an independent-samples t test?

		We are working with two samples and an estimate of spread based on two samples is likely to be more accurate than an estimate of spread based on a single sample.
		It is necessary to estimate the standard deviation of the two samples in order to compare the two samples to one another.
		Estimating the spread of the sample using the standard deviation increases the generalizability of results.
		Using the pooled variance helps the researcher identify skewness.

1 points

		low outliers
		high outliers
		it is more accurate, factoring in all of the data
		positive skew in the data

Source	SS	df	MS	F
Residence	7.64	2
Noise		2	1.11
Residence × Noise
Within	14.36		0.319
Total	27.84

		false face validity lie.
		sneaky sample lie
		interpolation lie.
		change the interval lie.

		scatterplot or line graph.
		Pareto chart.
		histogram or frequency polygon.
		bar graph.

		histogram or frequency polygon
		frequency polygon
		bar graph or Pareto chart
		bar graph

		persuade an audience.
		tell the story of data.
		modify the data to prove the hypothesis.
		edit the data.

		preferred by researchers.
		often used in research.
		better at presenting data than other charts.
		very limited.

		increases power.
		decreases power.
		makes power 1.0.
		makes power 0.

		increases in standard error
		confidence intervals
		effect size calculations
		statistical power analyses

		Σ(M_participant – GM)²
		Σ(M_participant – X)²
		Σ(M)(n – 1)
		Σ(M_participant – GM)

		independent-samples t test
		paired-samples t test
		Tukey HSD test
		between-groups ANOVA

		median
		mode
		mean
		range

		measure of variability.
		statistic.
		parameter.
		mode.

X	Rating
6	9
5	2
4	5
3	7
2	3
1	21

		6.0.
		5.0.
		7.0.
		5.5.

		between-groups designs
		post-hoc designs
		within-groups designs
		correlational designs

		hypothesis tests.
		post-hoc tests.
		effect size statistics.
		confidence intervals.

		1-2-3 model.
		A-B-C model.
		cause-and-effect model.
		causal explanation model.

		developing high quality tests and measures.
		fixing psychological issues in people.
		studying illness and the onset of psychological illness.
		statistics and computers.

		unimodal, symmetric, and defined mathematically.
		bimodal, symmetric, and defined.
		multimodal and asymmetric.
		mathematically defined, bimodal, and symmetric.

		bell.
		skewed distribution.
		normal curve.
		standardized distribution.

		random selection
		random assignment to groups
		double-blind experiment
		quasi-experiment

		total calories consumed
		the low- and high-calorie breakfasts
		weight loss experienced in the day
		the researcher conducting the interviews

		the 4.5 aggressive behaviors.
		the 20 students the researcher observed.
		all second graders.
		all second graders who ate Pop-Tarts for breakfast.

		inferential statistic.
		sample.
		population.
		descriptive statistic.

Interval	Frequency
90–99	23
80–89	41
70–79	78
60–69	36
50–59	18
40–49	7
30–39	12
20–29	3

		scale variable.
		raw data sorter.
		inferential model.
		frequency distribution.

Interval	Frequency
6000–6999	6
5000–5999	19
4000–4999	31
3000–3999	66
2000–2999	52
1000–1999	24
0–999	13

		histogram
		grouped frequency table
		frequency polygon
		frequency table

		grounds for dismissal from most academic institutions.
		plagiarism.
		replication.
		generalizability.

		research hypothesis
		null hypothesis
		statistical hypothesis
		experimental hypothesis

		independence of trials.
		law of large numbers.
		long-run probability calculation.
		objective probability.

		Proportion; percentage
		Percentage; proportion
		Probability; percentage
		Probability; proportion

		-2.306 and 2.306
		-2.306 or 2.306
		-2.262 and 2.262
		-2.262 or 2.262

		a hypothesis test.
		an effect size measure.
		post-hoc tests.
		a confidence interval.