Methods Toward a Science of Behavior and Experience 10th International Edition by William J. Ray – Test Bank

 

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Chapter 5 – Description of Behavior Through Numerical Representation

 

Chapter Outline

Measurement

Scales of Measurement

Nominal Measurement

Ordinal Measurement

Interval Measurement

Ratio Measurement

Identifying Scales of Measurement

Measurement and Statistics

Pictorial Description of Frequency Information

Descriptive Statistics

Measures of Central Tendency

Measures of Variability

Pictorial Presentations of Numerical Data

Transforming Data

Standard Scores

Measure of Association

 

Chapter Overview

 

Behavior is described through measurement that exists at four basic levels or scales:  nominal, ordinal, interval, and ratio.  Statistics are used to help us make sense of data.  A frequency distribution provides a pictorial representation of frequency information from an experiment.   Distributions of scores may take several shapes, such as a bimodal distribution or skewed distribution.  Mean, median, and mode are commonly used measures of central tendency.  The choice of which one to use depends on the distribution.  Variability can be measured by range and standard deviation.  Numerical data can be represented in line and bar graphs.

 

Data can be transformed from one scale to another and to meet statistical assumptions.  Standard scores such as z scores allow comparison of scores to other scores.  Association between variables can be depicted in a scatter diagram and with correlation coefficients, which may be positive or negative.  Correlation does not show causal relationships between variables, but does have value in prediction.

 

Chapter Objectives

 

1. Measurement theory requires us to ask what two questions when doing research?

 

2. Compare and contrast the different scales of measurement.

 

3. Cite two ways to display data.

 

4. What three measures of central tendency are discussed in the text and what are their characteristics?

 

5. Discuss the concept of variability. Give examples of three different measures of variability and describe their functions.

 

6. Why is it common to transform data? Relate transformation of data to the concept of z-scores.

 

7. What is correlation? How does it aid us in understanding the relationship between variables?

 

8. How would you define a positive correlation? How would you define a negative correlation?

 

9. What can you say about the effect of one variable on the other in correlational studies?

 

10. What information is derived from squaring the correlation coefficient? How does this relate to variability accounted for?

 

11. Why is it important to assess underlying distribution before calculating correlations?

 

Teaching Points

 

There are several helpful points to make regarding scales of measurement.  First, each subsequent scale builds upon the previous scale.  Second, to make reasonable conclusions, one must be sensitive to the use of statistics for a particular scale.  Third, use the acronym NOIR, the French word for black, as a cue for the scales of measurement.

 

The chapter makes the excellent point that “statistics do not know and do not care where your numbers come from.”  For instance, you could calculate a mean from nominal level data, but the result would be meaningless.  Students might recognize this as an example of “garbage in garbage out.”

 

Students often do not possess good graphing skills and have difficulty remembering what variables go on which axes.  It would be helpful to give them practice at graphing by using one or more of the activities described below.

 

Remind students that a “0” in a dataset counts in determining the number of scores in calculating the mean.

 

Many students think too much about the mean (and central tendency in general) and not enough about variability.  It is useful to demonstrate both mathematically and graphically that two or more data sets can have identical means but be very different in terms of how dispersed the values are in each set.

Another area of challenge for students is how and why skewed distributions affect the choice of a measure of central tendency, in addition to difficulty with conceptually understanding standardized scores like z-scores.

 

Students may also get hung up on the words positive and negative.  Emphasize that positive correlation does not refer to a good correlation nor does negative correlation refer to a bad correlation.

 

Teaching Activities

 

Using Students as Subjects

This chapter lends itself well to collecting and analyzing and creating distributions of data gotten from your students.  Here are some ideas:

• construct frequency distributions for height, weight, shoe size, and gender
• calculate measures of central tendency and standard deviation for height and shoe size
• transform the scores of height in z-scores
• construct a scatter diagram with height and shoe size
• calculate correlation coefficient between height and shoe size
• calculate correlation coefficient between shoe size and number of siblings

 

Dissect a Graph

Supply students with a set of graphs and ask them to label and critique every part.  It may be best to use a variety of graphs and to even include errors.  Include graphs with error bars because students often have trouble interpreting what these indicators of variability mean.

 

Tables and Graphs in the Popular Media

Locate tables and graphs used in the popular media and bring them into class.  Let students examine them and formulate conclusions.  Next compare the conclusions generated by the students to the conclusions that accompanied the table or graph.  Augment this activity with examples of poorly constructed tables and graphs that are available from the web site described below.

 

Measures of Central Tendency in the Popular Media

As the textbook suggests, we hear about these measures often in the popular media.  Bring in examples of articles and ads that refer to a measure.  Suggest that without other information, it is difficult to know if the appropriate measure was used.

Wadsworth’s Statistics Workshop

 

http://www.wadsworth.com/psychology_d/templates/student_resources/workshops/stats_wrk.html

 

 

The Wadsworth’s Statistics Workshop site contains links to several sections relevant to students after reading the chapter. For example, Scale of Measurement discusses the four levels of measurement of variables in psychological research, their abstract number properties, and the types of statistics that are permitted for each variable. The tutorial ends with a summary and students can test their knowledge in identifying scales of measurement by doing the practice exercises. Another workshop entitled Central Tendency and Variability provides information on how to summarize various kinds of data. Students are led through an example that exercises their skill in calculating measures of central tendency and variability. The workshop segment z Scores elaborates on the value of the z score and provides a step-by-step process of calculating z. Finally, the section on Correlation describes the types of correlations (positive, negative, and zero) and introduces the formula for the Pearson’s correlation coefficient.As with each segment of the workshop site, this segment concludes with a brief quiz.

 

Internet Resources

Measurement theory (ftp://ftp.sas.com/pub/neural/measurement.faq)

This site provides additional information on measurement theory, scales of measurement, and transformations.

 

The Best and Worst of Statistical Graphics  (www.math.yorku.ca/SCS/Gallery/)

This site has some interesting examples of poorly conceptualized and created attempts at representing data visually.

More resources on statistics (http://www.statsoft.com/textbook/)

Elementary statistical concepts are explained concisely and effectively.  Of particular interest is the statistical glossary.

Datasets (lib.stat.cmu.edu/datasets) (http://www.umass.edu/statdata/)

If you need real data to illustrate statistical concepts, these sites have many datasets from a variety of disciplines.  The second site groups the datasets by what statistics would be appropriate to analyze the data.

 

Statistics links (www.mccombs.utexas.edu/faculty/jonathan.koehler/links/statistics.asp)

This site contains many links to interesting articles and activities related to statistics. Some of the topics addressed by the sites include games, gambling, sports, correlation, and comprehensive statistics sites.

 

Suggested Readings

Huff, D., & Geis, I. (1994).  How to lie with statistics.  New York:  W. W. Norton.

 

       This amusing book is easy reading full of actual examples of statistical misuses.

 

Research Activities for Students

 

The goals of the research activities are to:  (1) relate Chapter 5 on an applied learning dimension, and (2) get you involved in research.

 

1. Physical Activity and Mood: A Correlational Study. For one week record the information using the following scales:

 

       Rate your level of physical activity on the following scale:

 

1. Very physically active
2. Moderately physically active
3. Somewhat physically active
4. Not very physically active
5. Very physically inactive

 

 

       Rate your level of mood on the following scale:

 

1. Very good mood
2. Relatively good mood
3. Neutral
4. Somewhat of a bad mood
5. Very bad mood

 

 

Date         Time of day    Physical Activity Rating         Mood Rating

1.

 

 

3.

 

4.

 

5.

 

6.

 

7.

 

 

 

Research Flowchart:  Fill in the following information.

 

1. State your research hypothesis.

 

1. Operationally define your variables.

 

1. State measures you controlled or held constant.

 

1. Graph data on a scatterplot. Label the axes and the graph.

 

1. Calculate by using the Pearson’s correlation coefficient.

 

1. Interpret. State the coefficient of determination.

 

 

2. Parents, Sex Information, and Risk Taking Behavior: A Correlational Study.  Administer the following survey to at least 15 individuals.

 

This survey involves information regarding sexual attitudes and behavior.  I will be using the information gathered from this survey to gain knowledge about graphing data.  No names should be indicated on the survey, and all information will be kept completely confidential.  If there are any questions that you do not wish to answer, please feel free to skip to the next question.  Thank you for your participation.

 

What is your gender?  Male  __________  Female __________

 

For the following questions please circle your response:  1, 2, 3, 4 or 5.

 

1. Did your parents discuss sex and its risks with you while you lived at home as an adolescent?

 

1                      2                      3                      4                      5

Not at all                                                                                 Very much

 

2. How knowledgeable do you believe you are regarding sexually transmitted diseases, AIDS, and the risks of pregnancy?

1                      2                      3                      4                      5

Not at all                                                                                 Very much

 

3. How much do you feel the information that your parents shared about sex and its risks has influenced your willingness to engage in safe sexual behaviors (e.g., using condoms)?

 

1                      2                      3                      4                      5

No influence                                                                           Significant

 

 

1. State your research hypotheses.
2. Organize the data obtained from questions 2 and 3 into a scatterplot. The abscissa should be labeled “Degree of Knowledge” (values 1-5).  The ordinate should be labeled “Degree of Influence” (values 1-5).
3. Calculate a Pearson product moment correlation coefficient between for the data obtained from questions 1 and 2, questions 1 and 3, and questions 2 and 3.
4. Interpret the results by explaining what type of relationships, if any, are supported by the data. Discuss inferences about causation.

 

 

3. Misleading with the Average. Entry level salary data was collected on small sample of college graduates who earned degrees in psychology and biology.  Find the mean, median, and mode for each group.  If you wanted to persuade someone that they should definitely pursue a degree in psychology, which measure of central tendency would you use?  If you wanted to emphasize that it really didn’t matter what they majored in, which measure of central tendency would you use?

 

Entry Level Salaries for Graduates in:

 

Psychology                                              Biology

 

$30,000                                                     $30,000

$36,000                                                     $36,000

$40,000                                                     $40,000

$42,000                                                     $42,000

$149,000                                                   $49,000

 

 

4. Misleading with Statistics. Use online references such as PsycINFO and PubMed to find articles about how statistics can lie.  Explain this effect. Also see the suggested reading list at the end of this chapter.

 

 

5. Assess Your Self Esteem. Complete the following questions.  Identify each item as either a nominal, ordinal, interval, or ratio number.

 

Social Security Number _____

Male (01) _____ Female (02) _____

Year of Birth _____

Age _____

Class Standing:

Freshman (1) _____ Sophomore (2) _____ Junior (3) _____ Senior (4) _____

Exact time you started this test? ______

 

 

 

Rosenberg Self Esteem Scale

 

This form asks questions about self esteem.  Answer the following questions honestly using the response scale below.  There are no right and wrong answers.

 

1          Strongly agree

2          Agree

3          Disagree

4          Strongly disagree

 

 

_____ 1.          I feel that I am a person of worth, at least on an equal basis with others.

 

_____ 2.          I feel that I have a number of good qualities.

 

_____ 3.          *All in all, I’m inclined to feel that I am a failure.

 

_____ 4.          I am able to do things as well as most other people.

 

_____ 5.          *I feel that I do not have much to be proud of.

 

_____ 6.          I take a positive attitude toward myself.

 

_____ 7.          On the whole, I am satisfied with myself.

 

_____ 8.          *I wish I could have more respect for myself.

 

_____ 9.          *I certainly feel useless at times.

 

_____10.         *At times I think I am no good at all.

 

*Reverse score these items

 

 

 

 

TESTBANK

 

MULTIPLE CHOICE

 

1. Numbers can have the properties of identity, magnitude, equal intervals, and absolute zero. These properties refer to:

a.	scales of measurement.
b.	measures of central tendency.
c.	standard scores.
d.	measures of variation.

 

 

ANS: A                   PTS:   1                    REF:  Scales of Measurement

MSC: WWW

 

2. Weight is measured on a(n) ____ scale.

a.	nominal
b.	interval
c.	ratio
d.	ordinal

 

 

ANS: C                    PTS:   1                    REF:  Scales of Measurement

 

3. An IQ score is measured on a(n) ____ scale.

a.	ratio
b.	ordinal
c.	nominal
d.	interval

 

 

ANS: D                   PTS:   1                    REF:  Scales of Measurement

 

4. Classifying patients as highly anxious, moderately anxious, or not at all anxious would be an example of the use of a(n) ____ scale of measurement.

a.	interval
b.	ratio
c.	ordinal
d.	nominal

 

 

ANS: C                    PTS:   1                    REF:  Scales of Measurement

 

5. People’s ethnic background would be measured by a(n) ____ scale.

a.	nominal
b.	interval
c.	ordinal
d.	ratio

 

 

ANS: A                   PTS:   1                    REF:  Scales of Measurement

 

 

6. If differences between categories are qualitative rather than quantitative, the measurement scale is:

a.	ordinal.
b.	nominal.
c.	ratio.
d.	interval.

 

 

ANS: B                    PTS:   1                    REF:  Scales of Measurement

 

7. If a scale has equal intervals between values and a single underlying quantitative dimension, then it is a(n) ____ scale of measurement.

a.	ordinal.
b.	nominal.
c.	ratio.
d.	interval.

 

 

ANS: D                   PTS:   1                    REF:  Scales of Measurement

MSC: WWW

 

8. Unlike the Fahrenheit and Celsius scales, the Kelvin temperature scale’s lowest possible value is zero. Hence, the Kelvin scale can be considered to be ____.

a.	ordinal.
b.	nominal.
c.	ratio.
d.	interval.

 

 

ANS: C                    PTS:   1                    REF:  Scales of Measurement

 

9. If a scale has equal intervals between values, a single underlying quantitative dimension, and an absolute zero, then it is a(n) ____ scale of measurement.

a.	ordinal.
b.	nominal.
c.	ratio.
d.	interval.

 

 

ANS: C                    PTS:   1                    REF:  Scales of Measurement

 

10. When constructing a distribution of the number of people favoring each of five different political candidates, you should use:

a.	a frequency polygon.
b.	a bar graph.
c.	a line graph.
d.	either a frequency graph or a bar graph.

 

 

ANS: B                    PTS:   1                    REF:  Pictorial Description of Frequency Information

 

 

 

11. When constructing a distribution of the number of people who obtained each score on a test, you should use:

a.	a frequency polygon.
b.	a bar graph.
c.	a line graph.
d.	either a frequency polygon or a bar graph.

 

 

ANS: D                   PTS:   1                    REF:  Pictorial Description of Frequency Information

MSC: WWW

 

12. When a variable is continuous, it is appropriate to use:

a.	a frequency polygon.
b.	a bar graph.
c.	a line graph.
d.	either a frequency polygon or a bar graph.

 

 

ANS: C                    PTS:   1                    REF:  Pictorial Description of Frequency Information

 

13. When a frequency distribution is constructed, the ____ appears on the y-axis.

a.	number of individuals who make each response
b.	responses of the participants
c.	independent variable
d.	dependent variable

 

 

ANS: A                   PTS:   1                    REF:  Pictorial Description of Frequency Information

 

14. When a frequency distribution is constructed, the ____ appears on the x-axis.

a.	number of individuals who make each response
b.	responses of the participants
c.	independent variable
d.	dependent variable

 

 

ANS: B                    PTS:   1                    REF:  Pictorial Description of Frequency Information

 

15. If most of the scores in a distribution are clustered near the middle, the distribution is:

a.	skewed.
b.	a frequency polygon.
c.	normal.
d.	bimodal.

 

 

ANS: C                    PTS:   1                    REF:  Pictorial Description of Frequency Information

 

 

16. If scores in a distribution are clustered towards the left end of the distribution, the distribution is:

a.	negatively skewed.
b.	positively skewed.
c.	not skewed.
d.	irregularly skewed.

 

 

ANS: B                    PTS:   1                    REF:  Pictorial Description of Frequency Information

 

17. A distribution with two peaks is said to be:

a.	asymmetrical.
b.	symmetrical.
c.	binormal.
d.	bimodal.

 

 

ANS: D                   PTS:   1                    REF:  Pictorial Description of Frequency Information

 

18. For a group of 60 people–50 men and 10 women–a distribution of weights would likely be:

a.	normal.
b.	positively skewed.
c.	negatively skewed.
d.	bell-shaped.

 

 

ANS: C                    PTS:   1                    REF:  Pictorial Description of Frequency Information

MSC: WWW

 

19. Which of the following is not a measure of central tendency?

a.	mean
b.	range
c.	mode
d.	median

 

 

ANS: B                    PTS:   1                    REF:  Descriptive Statistics

 

20. The middle score in a set of scores is called the:

a.	mean
b.	median
c.	mode
d.	arithmetic average

 

 

ANS: B                    PTS:   1                    REF:  Descriptive Statistics

 

 

 

 

21. The mean of the scores 3, 6, 7, 8, 1 is:

a.	5
b.	5.2
c.	6
d.	7

 

 

ANS: A                   PTS:   1                    REF:  Descriptive Statistics

 

22. The measure of central tendency that takes all the scores in a data set into account is the:

a.	mean.
b.	median.
c.	mode.
d.	range.

 

 

ANS: A                   PTS:   1                    REF:  Descriptive Statistics

 

23. The most frequently occurring score in a distribution is the:

a.	median.
b.	arithmetic average.
c.	mean.
d.	mode.

 

 

ANS: D                   PTS:   1                    REF:  Descriptive Statistics

 

24. What is the median of the following scores: 9, 5, 4, 8, 10, 12?

a.	6
b.	7
c.	8
d.	9.5

 

 

ANS: C                    PTS:   1                    REF:  Descriptive Statistics

 

25. If you were told that the median of a distribution was greater than the mean, what would that tell you about the shape of the distribution?

a.	It was negatively skewed.
b.	It was positively skewed.
c.	It was normal.
d.	It would tell you nothing about the shape of the distribution.

 

 

ANS: A                   PTS:   1                    REF:  Descriptive Statistics

MSC: WWW

 

26. Under what conditions would the median, mode, and mean be the same value?

a.	when the distribution is positively skewed
b.	when the distribution is bimodal
c.	when the distribution is normal
d.	when the distribution is negatively skewed

 

 

ANS: C                    PTS:   1                    REF:  Descriptive Statistics

27. Which of the following is not a measure of variability?

a.	frequency
b.	range
c.	variance
d.	standard deviation

 

 

ANS: A                   PTS:   1                    REF:  Descriptive Statistics

 

28. The measure of variability that reflects the difference between the largest and smallest scores in a distribution is the:

a.	standard deviation.
b.	sum of squares.
c.	variance.
d.	range.

 

 

ANS: D                   PTS:   1                    REF:  Descriptive Statistics

 

29. The average of the squared deviations from the mean is called:

a.	variance.
b.	sum of squares.
c.	range.
d.	standard deviation.

 

 

ANS: A                   PTS:   1                    REF:  Descriptive Statistics

 

30. If two sets of data have the same mean and the same range, they will also have:

a.	the same variance.
b.	the same standard deviation.
c.	the same sum of squares.
d.	none of these

 

 

ANS: D                   PTS:   1                    REF:  Descriptive Statistics

 

31. If a group of scores are tightly clustered around the mean, they will have a:

a.	small median.
b.	small variance.
c.	small N.
d.	all of these

 

 

ANS: B                    PTS:   1                    REF:  Descriptive Statistics

 

 

 

 

 

 

 

32. Professor Jones has given a statistics test to her class. After grading the tests she reports to the class that the mean score was a 99 and the standard deviation was 0. The class will be very happy because:

a.	Only a few students failed the test.
b.	Most people did moderately well on the test.
c.	Everyone got a 99.
d.	Most people scored around 99.

 

 

ANS: C                    PTS:   1                    REF:  Descriptive Statistics

MSC: WWW

 

33. SS/N is called the:

a.	sum of all squares.
b.	standard deviation.
c.	variance.
d.	mean.

 

 

ANS: C                    PTS:   1                    REF:  Descriptive Statistics

 

34. The square root of the variance is called the:

a.	squared deviation.
b.	average squared deviation.
c.	sum of the squared deviations.
d.	standard deviation.

 

 

ANS: D                   PTS:   1                    REF:  Descriptive Statistics

 

35. When graphing measures of central tendency from experimental data, you place the ____ on the x-axis.

a.	independent variable
b.	dependent variable
c.	measure of the central tendency
d.	responses of the research participants

 

 

ANS: A                   PTS:   1                    REF:  Pictorial Presentations of Numerical Data

 

36. When the independent variable represents a point on a continuum, the pictorial representation of the data should be:

a.	a bar graph.
b.	a frequency polygon.
c.	a line graph.
d.	either a bar graph or a line graph.

 

 

ANS: C                    PTS:   1                    REF:  Pictorial Presentations of Numerical Data

 

 

 

 

37. When the independent variable represents categorical information, the pictorial representation of the data should be:

a.	a bar graph.
b.	a line graph.
c.	a frequency polygon.
d.	either a line graph or a frequency polygon.

 

 

ANS: A                   PTS:   1                    REF:  Pictorial Presentations of Numerical Data

 

38. What technique can a researcher do to analyze data that is collected on different scales?

a.	linear transformation
b.	summing squares
c.	plotting data on a scatter diagram
d.	calculating the means

 

 

ANS: A                   PTS:   1                    REF:  Transforming Data

 

39. To express a score in terms of its relative position in a distribution, you use:

a.	the sum of squares.
b.	the variance.
c.	a standard score.
d.	the mean.

 

 

ANS: C                    PTS:   1                    REF:  Standard Scores

MSC: WWW

 

40. One reason to use standard scores instead of raw scores is:

a.	to calculate a correlation coefficient.
b.	to compare scores from two different distributions.
c.	to compare the standard deviation and the mean.
d.	all of these

 

 

ANS: B                    PTS:   1                    REF:  Standard Scores

 

41. The distribution of z scores has:

a.	a mean of 1 and a standard deviation of 2.
b.	a mean of 0 and a standard deviation of -1.
c.	a mean of 1 and a standard deviation of 1.
d.	a mean of 0 and a standard deviation of 1.

 

 

ANS: D                   PTS:   1                    REF:  Standard Scores

 

 

 

 

 

 

42. In a set of scores with a mean of 100 and a standard deviation of 5, what is the z score associated with a raw score of 95?

a.	-5
b.	5
c.	-1
d.	1

 

 

ANS: C                    PTS:   1                    REF:  Standard Scores

 

43. If your z score on a test is 0, your score is:

a.	the worst in the class.
b.	average.
c.	above average.
d.	below average.

 

 

ANS: B                    PTS:   1                    REF:  Standard Scores

 

44. You have a study partner who says that she has an IQ of 130. Given that the mean IQ is 100 and the standard deviation is 15, what would you conclude about your partner?

a.	She’s pretty smart.
b.	She’s above average in intelligence.
c.	Her intelligence z score is 2.00.
d.	All of these.

 

 

ANS: D                   PTS:   1                    REF:  Standard Scores

MSC: WWW

 

45. A transformation that allows all scores to be positive with a mean of 50 and a standard deviation of 10 is called a:

a.	T score.
b.	z score.
c.	F score.
d.	r score.

 

 

ANS: A                   PTS:   1                    REF:  Standard Scores

 

46. The correlation coefficient is a value between:

a.	-1.0 and +1.0.
b.	the mean and standard deviation.
c.	low score and high score.
d.	.0 and +1.0.

 

 

ANS: A                   PTS:   1                    REF:  Measure of Association

 

 

 

 

 

47. One of the most common correlation coefficients is called:

a.	range.
b.	t score.
c.	Pearson product moment correlation coefficient.
d.	standard correlation.

 

 

ANS: C                    PTS:   1                    REF:  Box 5.1

 

48. If the correlation between two variables is -.80, then:

a.	low scores on one variable are associated with high scores on the other variable.
b.	low scores one variable are associated with low scores on the other variable.
c.	high scores on one variable are associated with high scores on the other variable.
d.	there is little relation between the two variables.

 

 

ANS: A                   PTS:   1                    REF:  Measure of Association

 

49. When you construct a scatter diagram, the variable that you plot on the y-axis is:

a.	the independent variable.
b.	the dependent variable.
c.	either variable.
d.	the frequency of response.

 

 

ANS: C                    PTS:   1                    REF:  Measure of Association

 

50. The appropriate graph for a correlation is a:

a.	frequency polygon.
b.	scatter diagram.
c.	line graph.
d.	bar graph.

 

 

ANS: B                    PTS:   1                    REF:  Measure of Association

 

51. A scatter diagram that contains data points which are tightly clustered on a path that goes from the bottom left to the upper right is likely to depict a ____ correlation.

a.	weak negative
b.	strong positive
c.	weak positive
d.	strong negative

 

 

ANS: B                    PTS:   1                    REF:  Measure of Association

 

52. If the correlation between age and memory is -.30, how much of the variance in memory is accounted for by age?

a.	.09%
b.	.9%
c.	9%
d.	90%

 

 

ANS: C                    PTS:   1                    REF:  Measure of Association

53. If two variables are not related in any way, the coefficient of correlation must be:

a.	-1
b.	1
c.	0
d.	.5

 

 

ANS: C                    PTS:   1                    REF:  Measure of Association

MSC: WWW

 

54. If the correlation between practice and performance accuracy is .80, how much of the variance in performance is not accounted for by practice?

a.	6.4%
b.	20%
c.	36%
d.	64%

 

 

ANS: C                    PTS:   1                    REF:  Measure of Association

 

55. To determine the amount of variance in one measure due to the other measure you would calculate:

a.	sum of squares.
b.	z2 ´ 100/SD.
c.	r2 ´ 100.
d.	z-score.

 

 

ANS: C                    PTS:   1                    REF:  Measure of Association

TOP:  Measure of Association

 

56. The statistical technique used to predict one variable from another is called:

a.	a t-test.
b.	transformation.
c.	a z-test.
d.	regression.

 

 

ANS: D                   PTS:   1                    REF:  Measure of Association

 

57. In a particular college class, most students are around 20 years of age. But there is a retired third-grader teacher in that class and she is 73 years old. Her age lies outside the normal pattern and would be consider to be a(n):

a.	z-score.
b.	outlier.
c.	mean.
d.	variable.

 

 

ANS: B                    PTS:   1                    REF:  Measure of Association

 

58. For a correlation to be meaningful, the relation between the two variables should be:

a.	curvilinear.
b.	linear.
c.	>1.
d.	positive.

 

 

ANS: B                    PTS:   1                    REF:  Measure of Association

MSC: WWW

 

SHORT ANSWER

 

1. Contrast the four scales of measurement.

 

ANS:

Answer not provided.

 

PTS:   1                    REF:  Scales of Measurement

 

2. What does it mean to say, “statistics do not know and do not care where numbers come from”?

 

ANS:

Answer not provided.

 

PTS:   1                    REF:  Measurement and Statistics

 

3. Draw and describe a bimodal distribution, positively skewed distribution, and negatively skewed distribution.

 

ANS:

Answer not provided.

 

PTS:   1                    REF:  Pictorial Description of Frequency Information

 

4. What is the most commonly used measure of central tendency? Under what conditions is it inappropriate to use this measure? Why?

 

ANS:

Answer not provided.

 

PTS:   1                    REF:  Descriptive Statistics

 

5. Why is the variance a preferred measure of variability to the range?

 

ANS:

Answer not provided.

 

PTS:   1                    REF:  Descriptive Statistics

6. Show how two distributions with the same mean can have different measures of variability. In which of the two distributions is the mean a “better” descriptor? Why?

 

ANS:

Answer not provided.

 

PTS:   1                    REF:  Descriptive Statistics

 

7. Describe why it might be appropriate to transform data.

 

ANS:

Answer not provided.

 

PTS:   1                    REF:  Transforming Data

 

8. Graph the following results of an experiment: Mean weight loss for individuals on Diet A was 20 lbs., on Diet B was 30 lbs., and on Diet C was 40 lbs.

 

ANS:

Answer not provided.

 

PTS:   1                    REF:  Pictorial Presentations of Numerical Data

 

9. How will the shape of a frequency distribution change as variability changes?

 

ANS:

Answer not provided.

 

PTS:   1                    REF:  Pictorial Presentations of Numerical Data

 

10. What advantage do standard scores give a researcher?

 

ANS:

Answer not provided.

 

PTS:   1                    REF:  Standard Scores

 

 

 

11. Suppose that you were told that the mean score on this test was 72 with a standard deviation of 4 and that your z-score was -.5. What was your actual score on this test?

 

ANS:

Answer not provided.

 

PTS:   1                    REF:  Measure of Association

12. Suppose the correlation between depression and memory loss was -.50. Draw a rough scatter diagram of this relation. How would you interpret this correlation? How much of the variance in memory may be accounted for by depression? How much is accounted for by something other than depression?

 

ANS:

Answer not provided.

 

PTS:   1                    REF:  Measure of Association

 

13. Why would a researcher select regression to analyze data?

 

ANS:

Answer not provided.

 

PTS:   1                    REF:  Measure of Association