Analyzing the Data

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Questions

Question 1

What is the primary function of descriptive statistics in data analysis?

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Question 2

Which of the following is defined as the midpoint of a distribution of scores?

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Question 3

What do measures of dispersion, such as range and standard deviation, describe?

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Question 4

According to the text, for what type of research are means and standard deviations typically computed?

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Question 5

What does a correlation coefficient of 0 indicate?

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Question 6

What is the primary purpose of inferential statistics?

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Question 7

What is a statistically significant effect?

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Question 8

What is the conventional threshold researchers use to determine if a result is statistically significant?

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Question 9

What is a Type I error in the context of statistical analysis?

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Question 10

What is a Type II error in the context of statistical analysis?

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Question 11

If a researcher sets the significance threshold to 5 percent, what is the chance of making a Type I error?

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Question 12

What is the relationship between the chances of making a Type I error and a Type II error?

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Question 13

What does a negative correlation coefficient indicate about the relationship between two variables?

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Question 14

Which of the following is defined as the average distance of scores from the mean?

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Question 15

Inferential statistics are described as crucial because the effects found in a study may be due to a real effect or what other factor?

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Question 16

What is the range of possible values for a correlation coefficient?

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Question 17

According to the chapter, what is one factor that makes Type II errors more likely to occur?

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Question 18

Which of the following is an example of a measure of central tendency?

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Question 19

What must a researcher conclude if inferential statistics reveal a greater than 5 percent chance that an effect could be due to chance error alone?

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Question 20

The text provides an example of a negative correlation between stressful life events and happiness. What does this imply?

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Question 21

What is the relationship between standard deviation and variance?

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Question 22

Why is it important for researchers to keep in mind that statistics are probabilistic in nature?

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Question 23

What does the text identify as a more common method for non-experimental research than computing simple percentages?

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Question 24

What does a positive correlation coefficient indicate about the relationship between height and weight?

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Question 25

When a researcher concludes that their results are not statistically significant, but there is a real effect in the population, what has occurred?

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Question 26

Which measure of dispersion calculates the distance between the highest and lowest scores in a distribution?

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Question 27

Why might a researcher choose a lower significance threshold, such as 1 percent instead of 5 percent?

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Question 28

According to the text, once an effect is deemed statistically significant, what is it appropriate for a researcher to do?

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Question 29

What is the term for the most frequently occurring score in a distribution?

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Question 30

The text states that inferential statistics help determine if differences in means or the correlation coefficient are due to a real effect or if they 'may reflect a real relationship between variables or a real effect of an independent variable on a dependent variable'. What is the alternative explanation they test against?

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Question 31

A researcher concludes that a new therapy is effective because the results were statistically significant. In reality, the therapy has no effect. What has happened?

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Question 32

What is the collective term for statistics used to organize or summarize a set of data, such as percentages and measures of central tendency?

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Question 33

If a correlation coefficient is -1.00, what does this value represent?

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Question 34

What is being described when all scores in a data set are similar and clustered around the mean?

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Question 35

If you reduce the chance of making a Type I error from 5 percent to 1 percent, what is the consequence for the chance of making a Type II error?

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Question 36

The text explains that data are analyzed using both descriptive and inferential statistics. What is the role of inferential statistics in relation to the theory being tested?

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Question 37

Which descriptive statistic is just the standard deviation squared?

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Question 38

When is it appropriate to generalize results from a sample to the population?

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Question 39

A 'false positive' is another name for which type of statistical error?

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Question 40

In addition to a small sample size, what other factor is mentioned in the text as making a Type II error more likely?

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Question 41

What is the primary difference between descriptive and inferential statistics?

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Question 42

Which of the following statistics would be most appropriate for describing the relationship between two variables in non-experimental research?

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Question 43

If a researcher hopes that when they conclude an effect is not statistically significant, there really is no effect in the population, what are they hoping to avoid?

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Question 44

What does a correlation coefficient of -0.85 represent?

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Question 45

The average of a distribution of scores is known as the:

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Question 46

Why do researchers analyze data from a sample rather than the entire population?

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Question 47

If a result has a 4 percent chance of being due to random error, how would it typically be considered?

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Question 48

A researcher finding that an effect is statistically significant is essentially making a decision that the result is unlikely to be what?

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Question 49

Which of the following is NOT listed as an example of a descriptive statistic in the chapter?

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Question 50

If you are trying to describe the typical, average, and center of a distribution of scores, what category of descriptive statistics would you use?

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Other chapters

Methods of KnowingUnderstanding ScienceGoals of ScienceScience and Common SenseExperimental and Clinical PsychologistsKey Takeaways and ExercisesA Model of Scientific Research in PsychologyFinding a Research TopicGenerating Good Research QuestionsDeveloping a HypothesisDesigning a Research StudyDrawing Conclusions and Reporting the ResultsKey Takeaways and ExerciseMoral Foundations of Ethical ResearchFrom Moral Principles to Ethics CodesPutting Ethics Into PracticeKey Takeaways and ExercisesUnderstanding Psychological MeasurementReliability and Validity of MeasurementPractical Strategies for Psychological MeasurementKey Takeaways and ExercisesExperiment BasicsExperimental DesignExperimentation and ValidityPractical ConsiderationsKey Takeaways and ExercisesOverview of Non-Experimental ResearchCorrelational ResearchComplex CorrelationQualitative ResearchObservational ResearchKey Takeaways and ExercisesOverview of Survey ResearchConstructing SurveysConducting SurveysKey Takeaways and ExercisesOne-Group DesignsNon-Equivalent Groups DesignsKey Takeaways and ExercisesSetting Up a Factorial ExperimentInterpreting the Results of a Factorial ExperimentKey Takeaways and ExercisesOverview of Single-Subject ResearchSingle-Subject Research DesignsThe Single-Subject Versus Group “Debate”Key Takeaways and ExercisesAmerican Psychological Association (APA) StyleWriting a Research Report in American Psychological Association (APA) StyleOther Presentation FormatsKey Takeaways and ExercisesDescribing Single VariablesDescribing Statistical RelationshipsExpressing Your ResultsConducting Your AnalysesKey Takeaways and ExercisesUnderstanding Null Hypothesis TestingSome Basic Null Hypothesis TestsAdditional ConsiderationsFrom the "Replicability Crisis" to Open Science PracticesKey Takeaways and ExercisesGlossaryReferences