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# Statistics Homework

## Statistics Homework

### Question 1

1. For a sample of test scores that ranges from 42% to 93%, the median and mode are both 88%; however, the mean is 72%. What might account for the lower mean?
 low outliers high outliers it is more accurate, factoring in all of the data positive skew in the data

### Question 2

1. 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

### Question 3

1. 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.

### Question 4

1. 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.

### Question 5

1. 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.

### Question 6

1. 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 4.5 5 5.5

### Question 7

1. 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.

### Question 8

1. 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

### Question 9

1. 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

### Question 10

1. 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.

### Question 11

1. 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

### Question 12

1. 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.

### Question 13

1. 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

### Question 14

1. 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

### Question 15

1. 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

### Question 16

1. 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.

### Question 17

1. 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.

### Question 18

1. 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.

### Question 19

1. 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

### Question 20

1. 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.

### Question 21

1. 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.

### Question 22

1. According to the text, pie charts are:
 preferred by researchers. often used in research. better at presenting data than other charts. very limited.

### Question 23

1. 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

### Question 24

1. If a researcher performs a meta-analysis and finds that the mean = 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.

### Question 25

1. 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.

### Question 26

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

### Question 27

1. According to Cohen’s convention, a value of ________ is a large effect size.
 0.2 0.5 0.8 340

### Question 28

1. 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

### Question 29

1. 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

### Question 30

1. Statistical convention for the minimal acceptable power is:
 0.95. 0.75. 0.90. 0.80.

### Question 31

1. Which of the following formulas for calculating the subjects sum of squares for a within-groups ANOVA is correct?
 Σ(Mparticipant – GM)2 Σ(Mparticipant – X)2 Σ(M)(n – 1) Σ(Mparticipant – GM)

### Question 32

1. Which F statistic represents a new calculation as part of the within-groups ANOVA?
 Fbetween Fwithin Fsubjects Ftotal

### Question 33

1. 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.

### Question 34

1. 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

### Question 35

1. The ________ sum of squares is unique to the within-subjects design.
 between-groups within-groups total subjects

### Question 36

1. 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.

### Question 37

1. 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

### Question 38

1. The Bonferroni, Scheffé, and Tukey are all examples of:
 hypothesis tests. post-hoc tests. effect size statistics. confidence intervals.

### Question 39

1. 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.

### Question 40

1. 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.

### Question 41

1. 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.

### Question 42

1. 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.

### Question 43

1. Which of the following values of the correlation coefficient indicates the weakest relationship between two variables?
 0.42 –0.30 –0.87 0.03

### Question 44

1. A perfect linear relationship will yield a Pearson’s r value of:
 1.00. –1.00. 0. 1.00 or –1.00.

### Question 45

1. 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

### Question 46

1. 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.

### Question 47

1. The subscript M included in the symbols, µM and σM, 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 .

### Question 48

1. 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.

### Question 49

1. The normal curve is:
 unimodal, symmetric, and defined mathematically. bimodal, symmetric, and defined. multimodal and asymmetric. mathematically defined, bimodal, and symmetric.

### Question 50

1. 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.

### Question 51

1. The z-score distribution ________ has a mean of ________.
 always; 0 sometimes; 0 always; 1 sometimes; 1

### Question 52

1. 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.

### Question 53

1. 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.

### Question 54

1. 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

### Question 55

1. 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

### Question 56

1. 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

### Question 57

1. The outcome variable that we expect to change with changes in the independent variable is the ________ variable.
 confounding noise dependent extraneous

### Question 58

1. 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

### Question 59

1. 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.

### Question 60

1. 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.

### Question 61

1. 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.

### Question 62

1. 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

### Question 63

1. 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

### Question 64

1. 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

### Question 65

1. 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

### Question 66

1. 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.

### Question 67

1. 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

### Question 68

1. 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

### Question 69

1. 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

### Question 70

1. 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.

### Question 71

1. 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

### Question 72

1. Brent tosses a quarter 4 times and 3 times it comes up heads. The proportion of heads is:
 3/4. 75%. 2/4. 50%.

### Question 73

1. 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

### Question 74

1. A(n) ________ refers to the result of a(n) ________.
 success; failure failure; trial trial; outcome outcome; trial

### Question 75

1. 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.

### Question 76

1. ________ 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

### Question 77

1. 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:
 sM = 1.40. sM = 0.35. sM = 1.45. sM = 0.37.

### Question 78

1. 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

### Question 79

1. 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

### Question 80

1. Assume we know the following for a paired-samples t test: N = 9, Mdifference = 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

### Question 81

1. 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.

### Question 82

1. 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.

### Question 83

1. Assume we know the following for a paired-samples t test: N = 19, Mdifference = 13.19, s = 22.3. Calculate the effect size using Cohen’s d.
 0.59 0.22 0.41 2.58

### Question 84

1. 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.

### Question 85

1. 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

### Question 86

1. 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

### Question 87

1. 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

### Question 88

1. 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

### Question 89

1. 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

### Question 90

1. 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.

### Question 91

1. 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.

### Question 92

1. 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

### Question 93

1. 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.

### Question 94

1. 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.

### Question 95

1. 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.

### Question 96

1. Independent-samples t tests are also called:
 dependent-samples t tests. correlational-samples t tests. between-samples t tests. standardized-samples t tests.

### Question 97

1. ________ is a weighted average of the two estimates of ________.
 Pooled variance; variance Variance; pooled variance Pooled variance; standard deviation Standard deviation; pooled variance

### Question 98

1. 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 sdifference 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

### Question 99

1. 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.

### Question 100

1. 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.

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