chapter 1 test bank questions

Chapter 1

Levels of Measurement in SPSS Statistics

Chapter Summary

There are three main functions of research: collecting, analyzing, and interpreting data. Researchers collect data in the field and enter them into SPSS Statistics. SPSS Statistics analyzes the data and outputs the results of the analysis. Researchers then interpret the results of the analysis to determine the outcome.

There are four traditional levels of measurement: nominal, ordinal, interval, and ratio. Nominal data are categorical and place participants into groups. Ordinal data are rank-ordered with unequal levels between the ranks. Interval data are also rank-ordered but have equal, definable levels between the ranks; Interval data is considered continuous, but with no absolute zero value. Ratio data are continuous data and do allow for an absolute zero value.

In SPSS Statistics, the levels of measurements are defined differently. The following table (also in the text) compares the differences.

Table 1.1

Summary and Comparison of Traditional and SPSS Statistics Terminology for Levels of Measurement

Traditional SPSS Statistics Definition Example

Categorical Categorical General term for nominal and ordinal

Nominal Nominal Naming data Sex: male-female

Ordinal Ordinal Ordered data Highest degree earned

Scale Scale (Continuous)1 General term for interval and ratio Interval Scale Equal intervals without absolute zero Multiple-choice scores

Ratio Scale Equal intervals with absolute zero Weight (in pounds)

1 SPSS Statistics uses the terms “Scale” and “Continuous” interchangeably.

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Chapter Objectives

1. Identify the major steps in conducting research. 2. Define traditional levels of measurement. 3. Define levels of measurement used by SPSS Statistics. 4. Compare traditional levels with SPSS Statistics levels. 5. Define the term variable. 6. Classify variables as categorical or scale. 7. Classify variables as nominal, ordinal, or scale.

Chapter Key Terms

Data Collect data Analyze data Interpret data Systematic Likert scale Level of measurement Nominal Ordinal Interval Ratio Categorical level Scale level Variable

Chapter Suggested Readings/Activities

1. Suggested readings/activities available online:

• Practice: https://www.msu.edu/user/sw/statrev/strvq110.htm (accessed 4/29/2015) • Practice:

http://www.psychology.emory.edu/clinical/bliwise/Tutorials/SOM/smmod/scalemea/sme x.htm (accessed 4/29/2015)

• Tutorial with video: http://stattrek.com/statistics/measurement-scales.aspx?Tutorial=AP (accessed 4/29/2015)

2. SPSS Statistics Levels of Measurement Activity (next page)

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SPSS Statistics Levels Measurement Activity

For each of the following variables, indicate the SPSS Statistics level of measurement (nominal, ordinal, scale).

Variable Scale

Gender (male, female)

Driving distance

Self-esteem measured using Likert Scale

Weight

SAT score

Rankings of students

Student satisfaction via evaluation responses

Student satisfaction via number of days attended class

Hours worked per week

Annual salary

Preferred brand of soda

Number of broken bones in a person’s lifetime

Political party affiliation

Hormone blood levels

Calories eaten per day

Calories burned per day

Type of vehicle

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SPSS Statistics Levels Measurement Activity Answer Key

For each of the following variables, indicate the SPSS Statistics level of measurement (nominal, ordinal, scale).

Variable Scale

Gender (male, female) Nominal

Driving distance Scale

Self-esteem measured using Likert Scale Scale

Weight Scale

SAT score Scale

Rankings of students Ordinal

Student satisfaction via evaluation responses Scale

Student satisfaction via number of days attended class Scale

Hours worked per week Scale

Annual salary in ranges (e.g., 0-$4,999, $5,000-9,999, etc.) Ordinal

Preferred brand of soda Nominal

Number of broken bones in a person’s lifetime Scale

Political party affiliation Nominal

Finishing place in road race Ordinal

Hormone blood levels Scale

Calories eaten per day Scale

Calories burned per day Scale

Type of vehicle Nominal

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Chapter 1 Test Bank Questions 1. Measuring political party affiliation by grouping individuals into such categories as Republican, Democrat, Libertarian, Green, and so on is at what level of measurement?

a. Nominal b. Ordinal c. Interval d. Ratio

2. Measurements of temperature (in Fahrenheit and Celsius) are at what level of measurement?

a. Nominal b. Ordinal c. Interval d. Ratio

3. Consider a variable that has no absolute zero (such as SAT scores) and has equal intervals. In SPSS Statistics, this variable is categorized as being which of the following?

a. Nominal b. Ordinal c. Scale

4. A data set of one hundred individuals’ weight (in pounds) is at what level of measurement in SPSS Statistics?


5. A researcher classified participants by the state in which they were born. The researcher has measured at what SPSS Statistics level?


6. A researcher measured a variable at the ratio level. He or she has measured at which SPSS Statistics level?


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7. A researcher rank-orders participants according to the highest level of education attained, giving the participants with high school diplomas a rank of 1, participants with associate degrees a rank of 2, and so on. The researcher has measured at what SPSS Statistics level?


8. A researcher labels one group as the control group and one group as the experimental group. What is the SPSS Statistics level of measurement for the labels?


9. A researcher measured participants’ responses to a self-esteem survey using a Likert scale (1 to 5). The researcher has measured at what level of measurement in SPSS Statistics?


10. A researcher wants to compare overall finishing place in a road race (e.g., 1st, 2nd, etc.) with the number of hours of running practice. What is the SPSS Statistics level of measurement for the finishing place?


11. Researchers often choose a statistical method for analyzing a dataset based on the purpose of the research.

a. True b. False

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12. In SPSS Statistics, ordinal and interval levels of measurement are combined into the scale level of measurement.

a. True b. False

13. The three major steps in research are: collect data, analyze data, and interpret data.

a. True b. False

14. The amount of salary a person earns per year is measured at the SPSS Statistics scale level of measurement.

a. True b. False

15. SPSS Statistics levels of measurement can be grouped into scale and nominal.

a. True b. False

Chapter 1 Test Bank Answers 1. a. Nominal 2. c. Interval 3. c. Scale 4. c. Scale 5. a. Nominal 6. c. Scale 7. b. Ordinal 8. a. Nominal 9. c. Scale 10. b. Ordinal 11. a. True 12. b. False 13. a. True 14. a. True 15. b. False

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Chapter 2

Entering and Saving a Set of Scores (Scale Variable)

Chapter Summary

The chapter covers the practical steps of entering and saving a dataset that includes on scale variables (i.e., interval, ratio). Students learn how to:

• Create a “New Dataset” in the “Welcome Dialog” window, • Enter variable information in the “Variable View”, • Enter data in the “Data View”, • Double-check entries, • Save the data file, • And close SPSS Statistics.

Chapter Objectives

1. Start SPSS Statistics. 2. Distinguish between numeric data and string data. 3. Distinguish between “Variable View” and “Data View” in the Data Editor. 4. Name a variable. 5. Give the variable a label. 6. Enter scores for a scale variable (i.e., ratio or interval). 7. Save the data file, and close SPSS Statistics.

Chapter Key Terms

Variable View Data View Data Editor Name – Variable Label – Variable


The following is a link to IBM’s SPSS Statistics 23 Brief Guide: ftp://public.dhe.ibm.com/software/analytics/spss/documentation/statistics/23.0/en/client/Manuals /IBM_SPSS_Statistics_Brief_Guide.pdf (accessed 5/4/2015).

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Chapter 2 Test Bank Questions 1. String data consists of letters that make up words; numeric data consists of:

a. Abbreviations b. Codes c. Scores d. All of the above

2. To create a new data file in SPSS Statistics, you select:

a. “Open a New Data File” b. “Type in Data” c. “New Dataset” d. “New Data File”

3. To enter a variable’s name, you select:

a. “Variable View” b. “Dataset Tab” c. “Data View” d. “Variable Tab”

4. To enter a variable’s label, you select:

a. “Variable Tab” b. “Variable View” c. “Data View” d. “Dataset Tab”

5. To enter a variable’s data, you select:

a. “Data View” b. “Dataset Tab” c. “Variable Tab” d. “Variable View”

6. The location of the “View” tabs in the “Data Editor” is:

a. Upper-right corner b. Lower-center c. Lower-left corner

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7. What is a major source of error when using SPSS Statistics? a. Variables named incorrectly b. Data entered incorrectly c. Variables labeled incorrectly d. Data named incorrectly

8. The user-interface of IBM’s SPSS Statistics 23 is similar across Windows and Mac operating systems.

a. True b. False

9. You will never need to edit information in the “Variable View” except for the name and label.

a. True b. False

10. There is no need to double-check your data entry because SPSS Statistics validates your data before you run any analyses.

a. True b. False

Chapter 2 Test Bank Answers

1. c. Scores 2. c. “New Dataset” 3. a. “Variable View” 4. b. “Variable View” 5. a. “Data View” 6. b. Lower-center 7. b. Data entered incorrectly 8. a. True 9. b. False 10. b. False

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Chapter 3

Frequency Distribution

Chapter Summary

This chapter covers organizing data into a frequency distribution, and specifically how to create a frequency distribution within SPSS Statistics. Students will use the following steps:

1) Start SPSS Statistics (a review of Chapter 2); 2) Locating and existing file; 3) Verifying the proper level of measurement is selected; 4) Analyze the frequency

distribution of data; and 5) Interpret the SPSS Statistics Frequencies display.

Chapter Objectives

1. Open a saved data file. 2. Create a frequency distribution, including percentages and cumulative percentages. 3. Save the SPSS Statistics output. 4. Print out the SPSS Statistics output. 5. Format an SPSS Statistics frequency distribution output for presentation in a research report.

Chapter Key Terms

Frequency Distribution Column Row Thumb drive Cloud storage Analyze Descriptive Statistics APA format


Suggested readings/activities available online:

• Frequency distribution examples: http://www.statcan.gc.ca/edu/powerpouvoir/ch8/5214814-eng.htm

• Frequency distribution examples (with older SPSS screenshots): http://www.psychstat.missouristate.edu/introbook/sbk07.htm

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Chapter 3 Test Bank Questions 1. A distribution is:

a. A way to organize data b. A way to disseminate data c. A way to send data d. A way to formulate data

2. You can save your data file to all the following locations except:

a. Local Hard Drive b. Thumb drive c. SETI d. Cloud Storage

3. In what view can you ensure the level of measurement is appropriate?

a. Nominal view b. Data view c. Storage view d. Variable view

4. What menu item do you select to find the “Descriptive Statistics…” selection?

a. Frequencies… b. Graphs c. Analyze d. Utilities

5. To create a frequency distribution, the variable required which level of measurement?


6. SPSS Statistics outputs the frequency distribution in a way that is formatted for publication.

a. True b. False

7. In the SPSS frequency distribution, values that have 0 frequency are not shown.

a. True b. False

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8. In the formatted frequency distribution, values that have 0 frequency are not shown.a. Trueb. False

9. On the SPSS Statistics output, the symbol “N” stands for “number of cases.”a. Trueb. False

10. In the “Frequencies” dialog box, use the arrow to move your variable of interest to “Variable(s)...”a. Trueb. False

Chapter 3 Test Bank Answers

1. a. A way to organize data 2. c. SETI 3. d. Variable view 4. c. Analyze 5. c. Scale 6. b. False 7. a. True 8. b. False 9. a. True 10. a. True

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Chapter 4

Histogram

Chapter Summary

This chapter covers displaying data in a histogram. Students will use the following steps:

1. Start SPSS Statistics;2. Locate an existing file;3. Verifying the proper level of measurement is selected; and4. Create a histogram using SPSS Statistics; 5) Superimpose a normal curve on the

histogram; and 6) Interpret the SPSS Statistics Histogram display.

The chapter also covers the difference between a histogram and a bar graph. A histogram displays scale data; a bar graph displays categorical data. The chapter also covers the difference between a graph and a figure. A graph is a common term for data display; figure is the specific term used in the social and behavioral science.

Chapter Objectives

1. Add data for a second variable to a saved data file.2. Create a histogram using SPSS Statistics.3. Distinguish between the terms histogram and bar graph.4. Examine the shape of a distribution displayed in a histogram.5. Superimpose a normal curve on a histogram.6. Format an SPSS Statistics histogram output for presentation in a research report.7. Distinguish between the terms graph and figure.

Chapter Key Terms

Histogram Bar graph Normal curve Graph Figure Chart Builder



• Interactive histogram: http://www.shodor.org/interactivate/activities/Histogram/• Histogram tool and activities: http://illuminations.nctm.org/Activity.aspx?id=4152

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Chapter 4 Test Bank Questions 1. A histogram:

a. is a statistical figure b. is similar to a bar graph c. shows bars that are separate d. cannot provide information on normality

2. The name of the tool in SPSS Statistics that creates a histogram is called:

a. Graph Builder b. Figure Builder c. Chart Builder d. GGraph Builder

3. How many variables are displayed on a histogram?

a. 0 b. 1 c. 2 d. 3

4. A figure is different from a graph in which way?

a. Figure is the term used in mass media. b. Statistical drawings are referred to as statistical graphs. c. Figure is a specific term used in the social and behavioral sciences. d. SPSS Statistics refers to histograms as figures.

5. To create a histogram, the variable requires which level of measurement?


6. SPSS Statistics outputs the histogram in a way that is formatted for publication.

a. True b. False

7. You can use SPSS Statistics Chart Builder to add a figure and caption below the histogram.

a. True b. False

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8. SPSS Statistics does not include the mean and standard deviation with the histogram GGraph. a. True b. False

9. On the SPSS Statistics output, the GGraph stands for “Geometric Graph.”

a. True b. False

10. A normal curve can be superimposed on a histogram in SPSS Statistics.

a. True b. False

Chapter 4 Test Bank Answers 1. a. is a statistical figure 2. c. Chart Builder 3. b. 1 4. c. Figure is a specific term used in the social and behavioral sciences 5. c. Scale 6. b. False 7. a. True 8. b. False 9. a. True 10. a. True

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Chapter 5

Frequency Polygon

Chapter Summary

This chapter covers displaying data in a histogram. Students will use the following steps:

1. Start SPSS Statistics; 2. Locate an existing file; 3. Verifying the proper level of measurement is selected; and 4. Create a histogram using SPSS Statistics; 5) Superimpose a normal curve on the

histogram; and 6) Interpret the SPSS Statistics Histogram display.

The chapter covers the difference between a graph and a figure with respect to a frequency polygon. A graph is a common term for data display; figure is the specific term used in the social and behavior sciences. There is also information on distinguishing a statistical figure from a statistical table. A statistical figure is a drawing that represents statistical output, such as a frequency polygon; a statistical table is an ordered set of statistical values without drawings.

Chapter Objectives

1. Create a frequency polygon using SPSS Statistics. 2. Distinguish between the terms statistical figure and statistical table. 3. Format an SPSS Statistics frequency polygon for presentation in a research report. 4. Create a polygon showing percentages instead of frequencies.

Chapter Key Terms

Polygon Frequency Statistical Table Statistical Figure Figure Graph Chart Builder

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Chapter Suggested Readings


• Frequency Polygon Simple Notes and Quiz:

http://www.cliffsnotes.com/math/statistics/graphic-displays/frequency-polygon

• Frequency polygon tutorial, activities, and relationships to histogram: http://www.icoachmath.com/math_dictionary/frequency_polygon.html

Chapter 5 Test Bank Questions 1. A frequency polygon:

a. is a statistical figure. b. is similar to a line graph. c. shows percentages that are separate data points. d. cannot provide information on normality.

2. The name of the tool in SPSS Statistics that creates a frequency polygon is called:

a. Graph Builder b. Figure Builder c. Chart Builder d. GGraph Builder

3. How many variables are displayed on a frequency polygon?

a. 0 b. 1 c. 2 d. 3

4. A statistical table is different from a statistical figure in what way?

a. A statistical table displays data in a statistical drawing. b. A statistical table displays data in an ordered set and a statistical drawing. c. A statistical figure displays data in a statistical drawing. d. A statistical figure displays data in an ordered set.

5. To create a frequency polygon, the variable requires which level of measurement?


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6. SPSS Statistics outputs the frequency polygon in a way that is formatted for publication. a. True b. False

7. You can use SPSS Statistics Chart Builder to add a figure and caption below the frequency polygon. a. True b. False

8. SPSS Statistics does not include the mean and standard deviation with the frequency polygon GGraph.

a. True b. False

9. A statistical table displays information in an ordered set of statistical values. a. True b. False

10. A normal curve can be superimposed on a frequency polygon in SPSS Statistics. a. True b. False

Chapter 5 Test Bank Answers 1. a. is a statistical figure 2. c. Chart Builder 3. b. 1 4. c. A statistical figure displays data in a statistical drawing 5. c. Scale 6. b. False 7. a. True 8. b. False 9. a. True 10. a. True

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Chapter 6

Mean, Median, and Mode: One Group, Two Scale Variables

Chapter Summary

This chapter covers measures of central tendency for one group of participants and two variables. The chapter begins with the definition and differentiation of mean, median, and mode. The mean is defined as the balancing point in a distribution of scores (calculated by summing all the scores and dividing by the number of scores). The median is defined as the middle point in a distribution of scores (calculated by arranging the scores in order from high to low and counting to the middle score). The mode is defined as the most frequently occurring score in a distribution. For instance, if more participants have a score of 10 than any other score, then 10 is the mode. Steps provided in the chapter describe how to obtain the mean and median using SPSS Statistics.

The chapter then describes when to use the mean and when to use the median. In highly skewed data, the median is less affected by outliers and so is the best representation of the central tendency of the data. In distributions that are not highly skewed, the mean presents the best representation of central tendency.

Last, the chapter clarifies how many decimal places to use when reporting data. The convention is to use two decimal places more than the raw data. Hence, if raw data is 5, then use two decimal places (e.g., 5.00) to report the calculated statistics.

Chapter Objectives

1. Define the three measures of central tendency (e.g., mean, median, and mode). 2. Identify when to use the mean, median, and mode. 3. Distinguish between the meanings of row numbers in the “Variable View” and “Data

View” modes. 4. Calculate the mean and median using SPSS Statistics. 5. Identify the mode in a frequency distribution. 6. Present the mean and median in a research report.

a. Select the appropriate symbol for the mean. b. Determine the number of decimal places to use when reporting

the mean and median.

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Chapter Key Terms

Mean Median Mode Central Tendency Skewed Explore…

Chapter Suggested Readings/Activities Suggested readings/activities available online:

Guided Activities on Mean, Median, and Mode (Khan Academy): https://www.khanacademy.org/math/probability/descriptive-statistics/central_tendency/e/mean_median_and_mode

Comprehensive Lesson Plan on Mean, Median, and Mode: http://www.beaconlearningcenter.com/documents/1652_01.pdf

Demonstration: Mean, Median, and Skew: http://onlinestatbook.com/2/summarizing_distributions/mean_median_sim.html

Chapter 6 Test Bank Questions 1. The mean is defined as:

a. The balancing point in a distribution of scores. b. The middle point in a distribution of scores. c. The most frequently occurring score in a distribution. d. None of the above.

2. The median is defined as:


3. The mode is defined as:


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4. Use the mean when the following condition(s) is/are met: a. The distribution of scores is not highly skewed. b. The scores are at the ordinal level of measurement. c. The scores are at the scale level of measurement. d. Both A and C.

5. When would you need to use the median instead of the mean?

a. The distribution of scores is not highly skewed. b. The scores are at the ordinal level of measurement. c. The scores are at the scale level of measurement. d. Both A and C.

6. Use the median when the following condition(s) is/are met:

a. The distribution of scores is highly skewed. b. The scores are at the ordinal level of measurement. c. The scores are at the scale level of measurement. d. Both A and B

7. The median is the most frequently used measure of central tendency used in published research.

a. True b. False

8. Each row in SPSS Statistics represents a participant. a. True b. False

9. In SPSS Statistics once you move your cursor to “Descriptive Statistics,” click on “Investigate…” to get the mean and median.

a. True b. False

10. There can only be one mode in a distribution. a. True b. False

11. The median is appropriate for highly skewed data. a. True b. False

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Chapter 6 Test Bank Answers 1. a. The balancing point in a distribution of scores 2. b. The middle point in a distribution of scores 3. c. The most frequently occurring score in a distribution 4. d. Both A and C 5. b. The scores are at the ordinal level of measurement 6. d. Both A and B 7. b. False 8. a. True 9. b. False 10. b. False 11. a. True

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Chapter 7

Mean and Standard Deviation: Two or More Groups, One Scale Variable

Chapter Summary

This chapter covers measures of central tendency and variance in two or more groups that are differentiated by one ordinal variable. The chapter begins with the definition of the standard deviation. The standard deviation, or sd, is defined as the number of score points out from the mean of a normal distribution that includes 34% of the cases Steps provided in the chapter describe how to obtain the means and standard deviations of two or more groups using SPSS Statistics.

When explaining the process to find the mean and standard deviation of two or more groups, the chapter introduced the concept of using labels to differentiation between different groups. In the example used in the chapter, there are three groups defined by the first, ordinal variable (Dosage Level: Low, Moderate, High).

Last, the chapter clarifies differences between an independent variable and a dependent variable. An independent variable describes group membership and is also known as the input variable or stimulus variable. A dependent variable describes the participants’ outcome related to the independent variable and is also known as the outcome variable or response variable.

Chapter Objectives

1. Review the definition of the mean. 2. Define the standard deviation. 3. Identify when to use the mean and standard deviation. 4. Identify when to use the median and interquartile range. 5. Enter data consisting of codes for group membership and scores for a scale variable. 6. Identify independent and dependent variables for analysis by SPSS Statistics. 7. Calculate the means and standard deviations separately for each group. 8. Present means and standard deviations in a research report.

a. Present means and standard deviations within a sentence. b. Present means and standard deviations in a statistical table.

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Chapter Key Terms

Standard deviation Median Variable label/code Independent variable Dependent variable



• Tutorial and Activities on Mean and Interquartile Range: http://math.tutorvista.com/statistics/interquartile-range.html

• SPSS Statistics Examples of Finding Standard Deviation: http://davidmlane.com/SPSS/standard_deviation.html

• Independent/Dependent Variables Online Quiz/Activity: http://www.quia.com/pop/184568.html

Chapter 7 Test Bank Questions 1. The standard deviation is:

a. A measure of variation that describes the center of a data set. b. The number of score points out from the mean of a normal distribution that includes 34% of the

cases. c. The number of score points out from the mean of a normal distribution that includes 13.6% of the

cases. d. A measure of central tendency that describes the range of a data set.

2. The name of the tool in SPSS Statistics that compares means and standard deviations among

groups is: a. Compare Means… b. Descriptives… c. Means… d. Standard deviations…

3. Assigning numerical codes to identify groups occurs in which column in the “Variable View”?

a. Label b. Name c. Values d. Variable

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4. The following variable defines groups: a. Outcome b. Dependent c. Response d. Independent

5. The following variable defines participant changes:

a. Input b. Dependent c. Stimulus d. Independent

6. In the Value Labels dialog box, click “OK” to add a value label.

a. True b. False

7. The Means dialog box requires a Dependent variable and an Independent Variable to calculate means. a. True b. False

8. The SPSS Statistics Report output is appropriate for use in publications. a. True b. False

9. In the “Data View,” each column is a new variable. a. True b. False

10. To assign descriptive labels to numerical data, SPSS Statistics requires data values to be coded. a. True b. False

Chapter 7 Test Bank Answers 1. b. The number of score points out from the mean of a normal distribution that includes 34% of the cases 2. c. Means… 3. c. Values 4. d. Independent 5. b. Dependent 6. b. False 7. a. True 8. b. False 9. a. True 10. a. True

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Chapter 8

Z-Scores (Standard Scores)

Chapter Summary

This chapter covers standardized scores named z-sores. Z-Scores are scores expressed in standard deviation units. The scores usually range from -3.00 to 3.00. Z-Scores may also be called standard scores or standardized values.

The chapter then explains the exact steps to calculate z-scores using SPSS Statistics. The chapter ends with a description of how to interpret z-scores that are negative, zero, and positive.

Last, the chapter clarifies differences between an independent variable and a dependent variable. An independent variable describes group membership and is also known as the input variable or stimulus variable. A dependent variable describes the participants’ outcome related to the independent variable and is also known as the outcome variable or response variable.

Chapter Objectives

1. Define the terms z-score, standard score, and standardized values. 2. Calculate z-scores for individuals in a group. 3. Interpret z-scores. 4. Identify uses for z-scores.

Chapter Key Terms

z-score Standard score Standardized values



• Z-score activities, games, and tutorials: http://www.onlinemathlearning.com/zscores.html

• YouTube tutorial on z-scores in SPSS: https://www.youtube.com/watch?v=okf2nokI_tE

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Chapter 8 Test Bank Questions 1. The following is not another term for z-score:

a. Standardized value b. Standard score c. Z-Value d. None of the above

2. The name of the tool in SPSS Statistics that calculates z-scores is:

a. Compare Means… b. Descriptives… c. Means… d. Standard deviations…

3. The z-score is related to what statistical term?

a. Standard deviation b. Mean c. Median d. Range

4. Z-Scores that are positive represent scores that are:

a. Above the mean b. Below the mean c. At the mean d. None of the above

5. Z-Scores that are zero represent scores that are:


6. Z-Scores that are negative represent scores that are:


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7. In the Descriptives dialog box, click the arrow to move variables into the Variable(s): box. a. True b. False

8. Z-Score is sometimes called the standard score. a. True b. False

9. After SPSS Statistics calculates z-scores, they display in the output window. a. True b. False

10. A z-score of zero indicates the distribution average. a. True b. False

11. A z-score of -1.00 indicates a score one standard deviation above the mean. a. True b. False

Chapter 8 Test Bank Answers 1. c. Z-Value 2. b. Descriptives… 3. a. Standard deviation 4. a. Above the mean 5. c. At the mean 6. b. Below the mean 7. a. True 8. a. True 9. b. False 10. b. False 11. b. False

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Chapter 9

Scattergram

Chapter Summary

This chapter covers scattergrams, which are statistical figures displaying the relationship between scale variables. The chapter describes specific steps for creating scattergrams in SPSS Statistics using “Chart Builder.”

The chapter also defines terminology that is related to scattergrams:

• Predictor variable: the variable used to predict possible outcomes; displayed on the x-axis.

• Criterion variable: the variable that is being predicted; displayed on the y-axis. Also known as outcome variable.

• Strength: the relationship between the variables; measured how related variables are to each other.

• Direction: indicates if the relationship between the variables is positive or negative.

• Linearity: indicates if the relationship goes only one-way (linear) or two-ways (curvilinear) as the predictor variable changes.

Chapter Objectives

1. Define the term scattergram. 2. Identify when to use a scattergram. 3. Create a scattergram using SPSS Statistics. 4. Interpret a scattergram in terms of

a. strength, b. direction, and c. linearity.

5. Format a scattergram for presentation in a research report.

Chapter Key Terms

Scattergram Predictor variable Criterion variable Outcome variable Strength Direction Positive relationship Negative (inverse) relationship Linear relationship Curvilinear relationship

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• Classroom lab using food to explore variable relationships: http://www.pitt.edu/~nancyp/chs/scatterplot.doc

• Interactive scatterplot: http://www.shodor.org/interactivate/activities/ScatterPlot/ • Online tutorial, activity, and quiz: http://study.com/academy/lesson/scatter-plot-

andcorrelation-definition-example-analysis.html

Chapter 9 Test Bank Questions 1. A scattergram is also known as a:

a. Scatterplot b. Plot diagram c. Scatter figure d. None of the above

2. What are types of directional relationships in scattergrams?

a. Positive b. Negative c. No relationship d. Only A and B e. All of the above

3. Which variable should be displayed on the x-axis?

a. Outcome variable b. Predictor variable c. Criterion variable d. Participant variable

4. When there is a positive relationship between two variables, that means:

a. As one variable increases, the other decreases. b. As one variable increases, the other increases. c. As one variable increased, the other increases and then decreases. d. None of the above.

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5. When variables share a curvilinear relationship, this relationship is also known as: a. Up and down b. Positive c. No relationship d. Non-linear

6. A scattergram is a type of statistical figure.

a. True b. False

7. Scattergrams can be interpreted in terms of strength, course, and linearity. a. True b. False

8. SPSS Statistics uses “Chart Builder…” to create scattergrams. a. True b. False

9. Use a scattergram before calculating a correlation coefficient. a. True b. False

10. In APA style, figure numbers and their captions are placed below figures. a. True b. False

Chapter 9 Test Bank Answers 1. a. Scatterplot 2. e. All of the above 3. b. Predictor variable 4. b. As one variable increases, the other increases 5. d. Non-linear 6. a. True 7. b. False 8. a. True 9. a. True 10. a. True

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Chapter 10

Correlational Coefficients: The Pearson r and Spearman’s rho

Chapter Summary

This chapter covers correlation coefficients. It explains the different situation to use either Pearson’s r or Spearman’s rho. Pearson’s r is used when the data are at the scale level, distributed symmetrically, and not curvilinear. Spearman’s rho is used when data are at the ordinal level, distributed asymmetrically, and/or not curvilinear.

The chapter describes the steps needed in SPSS Statistics to calculate both the Pearson’s r and Spearman’s rho.

The chapter ends with an explanation of how to report correlation coefficients in an APAstyled report.

Chapter Objectives

1. Define the term correlation coefficient. 2. Identify when to use the Pearson r. 3. Identify when to use Spearman’s rho. 4. Interpret a correlation coefficient in terms of its strength and direction. 5. Present a correlation coefficient in a research report.

Chapter Key Terms

Correlation coefficient Pearson’s r Spearman’s rho Bivariate



• Correlation Lesson Plans with Activities and Answers: http://www.learner.org/courses/againstallodds/pdfs/AgainstAllOdds_StudentGuide_Unit12.pdf

• Advanced Example of Spearman Rank Correlation (with SPSS Statistics screen shots): http://www.statisticssolutions.com/spearman-rank-correlation/

33

Chapter 10 Test Bank Questions 1. A correlation coefficient is also known as a:

a. Spearman’s rho. b. Pearson’s r. c. Both A and B. d. None of the above.

2. Use the Pearson’s r when:

a. The distribution is asymmetrical. b. The data are at the ordinal level. c. The data are not curvilinear. d. The data are curvilinear.

3. Use the Spearman’s rho when:

a. The distribution is symmetrical. b. The data are at the ordinal level. c. The data are curvilinear. d. The data are at the scale level.

4. Use the following SPSS Statistics tool to calculate the correlation coefficient:

a. Chart Builder… b. Descriptive Statistics… c. Bivariate… d. None of the above.

5. When variables share a curvilinear relationship, this relationship is also known as:

a. Up and down b. Positive c. No relationship d. Non-linear

6. Pearson’s r is formally known as Pearson product-moment correlation coefficient.

a. True b. False

7. Spearman’s rho is formally known as Spearman’s rank-order correlation coefficient. a. True b. False

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8. Use Pearson’s r for data at the ordinal level. a. True b. False

9. Use Spearman’s rho for data at the scale level. a. True b. False

10. Use Pearson’s r for data at the scale level. a. True b. False

Chapter 10 Test Bank 1. c. Both A and B 2. c. The data are not curvilinear 3. b. The data are at the ordinal level 4. c. Bivariate… 5. d. Non-linear 6. a. True 7. a. True 8. b. False 9. b. False 10. a. True

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Chapter 11

Simple Linear Regression

Chapter Summary

This chapter covers linear regression. Linear regression is a statistical method used to plot a line that best represents a set of data made up of pairs of values, each representing an independent variable and a dependent variable. The chapter also describes the steps needed to calculate regression values and graph the scattergram.

SPSS Statistics outputs several values when calculating a linear regression. The first section is titled “Model Summary.” In the column headed “R Square,” there is a value known as the coefficient of determination, which indicates the proportion of variance of the dependent variable that can be explained by variation that also occurs in the independent variable. The “Std. Error of the Estimate” indicates the amount of dispersion for the prediction equation.

In the output section titled “ANOVA,” it is the far-right column headed “Sig.” that is of most interest. A value less than .05 indicates a significant result.

The third section of the output, titled “Coefficients,” contains a value of the independent variable that indicates whether the relationship is direct or inverse. You can plug the coefficient values into the regression equation used to plot the line of regression. This equation is expressed as Y’ = a + bX. To determine the value of Y’ (the dependent variable), replace a with the (Constant) and b with the “Coefficients” value of the independent variable.

Chapter Objectives

1. Define the term linear regression. 2. Calculate the intercept and slope for linear regression. 3. Interpret linear regression. 4. Use SPSS Statistics to create a scattergram and plot the fit-line of regression.

Chapter Key Terms

Linear regression Intercept Slope Fit-line Regression coefficients Chart Editor R2 Linear value

36



• Interesting Regression Lab Examples: http://mathequalslove.blogspot.com/2013/10/funwith-linear-regression-labs.html

• Linear Regression and Correlation Interactive Online Activity with Lesson Plans: http://www.shodor.org/interactivate/lessons/LinearRegressionCorrelation/

• Handout with several differing activities, questions, and ideas: https://www.causeweb.org/repository/ACT/Regression_Activity.doc

Chapter 11 Test Bank Questions 1. Linear regression is a statistical method requiring the following variable types:

a. Two variables at the ordinal level. b. One variable at the ordinal level and one at the scale level. c. Two variables at the scale level. d. None of the above.

2. SPSS Statistics calculates the following outputs for a linear regression analysis:

a. Model Summary b. ANOVA c. Coefficients d. All of the above

3. Use the following statistics to determine the statistical significance of the regression:

a. ANOVA Sig. b. R2 Linear value c. Unstandardized Coefficient d. Standard Error of the Estimate

4. Use the following SPSS Statistics tool to edit graphs:

a. Chart Builder b. Descriptive Statistics c. Graph Editor d. Chart Editor

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5. The following statistics can be displayed on the scattergram: a. Regression equation b. R2 Linear value c. Data points d. All of the above

6. Linear regression requires two variables at the ordinal level.

a. True b. False

7. The SPSS Statistics tool labels the variables used in linear regression as independent and dependent. *a. True b. False

8. A significance value of less than .05 indicates a statistically significant finding for an alpha-level of 5%. a. True b. False

9. The ANOVA output box contains the coefficient of determination. a. True b. False

10. Linear regression involves predicting the outcome of one variable (dependent) based on the input of

another variable (independent). a. True b. False

Chapter 11 Test Bank Answers 1. c. Two variables at the scale level 2. d. All of the above 3. a. ANOVA Sig. 4. d. Chart Editor 5. d. All of the above 6. b. False 7. a. True 8. a. True 9. b. False 10. a. True

38

Chapter 12

The t Test for a Single Sample Mean

Chapter Summary

This chapter covers the purpose of the t test for a single sample mean and the steps required to calculate the t statistic using SPSS Statistics. The purpose of the t test for a single sample mean is to determine whether the mean for a random sample of participants differs significantly from a known value or a hypothetical value.

Chapter Objectives

1. Identify the purpose of the t test for a single sample mean. 2. Conduct a t test to determine the significance of the difference between a single sample mean

and a test value (i.e., a known value or hypothetical value). 3. Interpret the results of the t test in terms of the null hypothesis and statistical significance. 4. Present the results of the t test in a research report.

Chapter Key Terms

t test t statistic Statistically significant Statistically insignificant Null hypothesis Sample mean Test value



• Using candy to demonstrate the use of the t test: http://www.teachpsychscience.org/pdf/120201394834pm_1.pdf

• Online tutorial with exercises: http://cep932.wikispaces.com/One+Sample+T-Test

39

Chapter 12 Test Bank Questions 1. The following are all terms associated with a t test, except:

a. Significance level. b. Correlational coefficient. c. Sample mean. d. Null hypothesis.

2. SPSS Statistics displays the following outputs for a t test:

a. Model Summary b. One-Sample Statistics c. Coefficients d. ANOVA

3. Use the following statistic to determine the statistical significance of the single sample mean:

a. ANOVA Significance b. R2 Linear value c. One-Sample Test Significance d. Standard Error of the Estimate

4. Use the following SPSS Statistics tool to calculate statistical significance:

a. Linear Compare… b. Descriptive Statistics… c. Compare Means… d. Chart Editor…

5. What hypothesis is being tested when using a t test?

a. Null hypothesis b. Test hypothesis c. Data-based hypothesis d. Sample mean hypothesis

6. A t test requires one variable at the scale level.

a. True b. False

7. A t test compares the sample mean to a test value. a. True b. False

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8. A significance value of .002 indicates a statistically significant finding at the .001 level. a. True b. False

9. In research reports, you should mention information about the null hypothesis.

a. True b. False

10. A negative t statistic demonstrates greater statistical significance.

a. True b. False

Chapter 12 Test Bank Answers 1. b. Correlational coefficient 2. b. One-Sample Statistics 3. c. One-Sample Test Significance 4. c. Compare Means… 5. a. Null hypothesis 6. a. True 7. a. True 8. b. False 9. a. True 10. a. True

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Chapter 13

Paired-Samples t Test

Chapter Summary

This chapter covers the purpose of the paired-samples t test and the steps required to calculate the t statistic using SPSS Statistics. This test is appropriate when each score underlying one mean has been paired (i.e., matched) with a score underlying the other mean.

Chapter Objectives

1. Identify the purpose of the paired-samples t test. 2. Conduct a t test to determine the significance of the difference between the means of two

paired samples (i.e., dependent means). 3. Interpret the results of a t test in terms of the null hypothesis and statistical significance. 4. Present the results of the t test in a research report.

Chapter Key Terms

Paired-samples t test Dependent groups Statistically significant Statistically insignificant Null hypothesis Sample means



• Lesson plan and activity ideas: http://www.statstutor.ac.uk/resources/uploaded/coventrypairedttests.pdf

• Walk-through tutorial for paired samples: http://ictedusrv.cumbria.ac.uk/maths/SecMaths/U4/page_86.htm

• Using paper helicopters to compare paired and independent groups: http://courses.ncssm.edu/math/Stat_inst01/PDFS/helitests.pdf

42

Chapter 13 Test Bank Questions 1. The following are all terms associated with a paired-samples t test, except:

a. Pretest b. Paired-sample Fit line c. Sample means d. Posttest

2. SPSS Statistics displays the following outputs for a t test:

a. Model Summary b. One-Sample Statistics c. Paired Samples Statistics d. ANOVA

3. Use the following statistic to determine the statistical significance of the paired-sample t test:

a. ANOVA Significance b. R2 Linear value c. One-Sample Test Significance d. Sig. (2-tailed)

4. Use the following SPSS Statistics tool to calculate statistical significance:

a. Paired-Samples T Test… b. Descriptive Statistics… c. Linear Means… d. Chart Editor…

5. What key do you use to select multiple variables?

a. “Ctrl” on a Windows machine b. “Command” on an Apple machine c. Either A or B. d. Neither A nor B.

6. A paired-samples t test requires two variables at the ordinal level.

a. True b. False

7. A paired-samples t test compares a sample mean to a test value. a. True b. False

43

8. A paired-samples t test requires two variables at the scale level. a. True b. False

9. In research reports, you need to report the t statistic and degrees of freedom. a. True b. False

10. Variables in paired-sample t tests are often called pretest and posttest. a. True b. False

Chapter 13 Test Bank Answers 1. b. Paired-sample Fit line 2. c. Paired Samples Statistics 3. d. Sig. (2-tailed) 4. a. Paired-Samples T Test… 5. c. Either A or B 6. b. False 7. b. False 8. a. True 9. a. True 10. b. False

44

Chapter 14

Independent-Samples t Test

Chapter Summary

This chapter covers the purpose of the independent-samples t test and the steps required to calculate the t statistic using SPSS Statistics. The term independent indicates that there is no relationship (no matching or pairing) of scores from one sample to the other. The chapter covers the independent-samples t test for two samples that are independent of each other.

Chapter Objectives

1. Identify the purpose of the independent-samples t test. 2. Conduct a t test to determine the significance of the difference between the means of two

independent samples. 3. Interpret the results of a t test in terms of the null hypothesis and statistical significance. 4. Present the results of the t test in a research report.

Chapter Key Terms

Independent-samples t test Control group Experimental group Equal Variances Independent groups Levene’s test



• Oreo cookie activity: http://www.amstat.org/education/stew/pdfs/DoubleStuffed.pdf

• Step-by-step tutorial: http://www.nottingham.ac.uk/toolkits/play_5838

• Using paper helicopters to compare paired and independent groups: http://courses.ncssm.edu/math/Stat_inst01/PDFS/helitests.pdf

45

Chapter 14 Test Bank Questions 1. The following terms are not associated with an independent-samples t test, except:

a. Pretest b. Independent-sample Fit line. c. Sample control. d. Control group.

2. SPSS Statistics displays the following outputs for an independent-samples t test:

a. Model Summary b. One-Sample Statistics c. Group Statistics d. ANOVA

3. Use the following statistical result to determine if the variances are assumed to be equal for an

independent-samples t test: a. ANOVA Significance b. Levene’s Test c. R2 Linear value d. One-Sample Test Significance

4. Use the following SPSS Statistics tool to calculate statistical significance for an independent-samples

t test: a. Descriptive Statistics… b. Compare Means… c. Linear Means… d. Chart Editor…

5. In SPSS Statistics, the dependent variable in an independent-samples t test is known as:

a. Outcome variable. b. Test variable. c. Experimental variable. d. Control variable.

6. An independent-samples t test requires two variables at the scale level.

a. True b. False

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7. An independent-samples t test compares two independent sample means. a. True b. False

8. An independent-samples t test requires one grouping variable to define the experimental and control

groups. a. True b. False

9. In research reports, you need to report the independent-samples t statistic, but not the degrees of

freedom. a. True b. False

10. Variables in an independent-sample t tests are often called baseline and experimental group. a. True b. False

Chapter 14 Test Bank Answers 1. d. Control group 2. c. Group Statistics 3. b. Levene’s Test 4. b. Compare Means… 5. b. Test variable 6. a. True 7. a. True 8. a. True 9. b. False 10. b. False

47

Chapter 15

One-Way ANOVA

Chapter Summary

This chapter covers the purpose of ANOVA and the steps required to calculate its F statistic using SPSS Statistics. The ANOVA is similar to the independent-samples t test, which determines the significance of the difference between two means. A one-way ANOVA can perform the same type of test for a set of two or more means.

The chapter also covers interpreting output and reporting ANOVA results. For ANOVA, report the value of F, followed (in brackets) by the degrees of freedom, and indicate whether F is statistically significant.

Chapter Objectives

1. Identify the purpose of a one-way ANOVA. 2. Conduct a one-way ANOVA. 3. Interpret the results of a one-way ANOVA in terms of the null hypothesis and statistical

significance. 4. Present the results of a one-way ANOVA in a research report.

Chapter Key Terms

ANOVA Group variable Factor F statistic



• Activity using raw research data to calculate One-Way ANOVA: http://www.teachpsychscience.org/pdf/1110201011008pm_1.pdf

• Using M&M’s to Teach One-Way ANOVA: http://www.amstat.org/publications/jse/v21n1/schwartz.pdf

48

Chapter 15 Test Bank Questions 1. The following terms are not associated with ANOVA, except:

a. Factor b. Independent-sample Fit line. c. Sample control. d. Control group.

2. SPSS Statistics displays the following outputs for an ANOVA:

a. Model Summary b. One-Sample Statistics c. Group Statistics d. ANOVA

3. Use the following statistical result to determine if the ANOVA found statistical differences among groups:

a. ANOVA Sig. b. Levene’s Test c. R2 Linear value d. One-Sample Test Significance

4. Use the following SPSS Statistics tool to calculate statistical significance for ANOVA:

a. Descriptives… b. Compare Means… c. Linear Means… d. Chart Editor…

5. In SPSS Statistics, the independent variable in an ANOVA is known as:

a. Outcome. b. Test. c. Factor. d. Control.

6. An ANOVA requires two or more conditions at the scale level. a. True b. False

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7. An ANOVA compares two or more independent sample means.

a. True b. False

8. An ANOVA requires one grouping variable to define the two or more groups.

a. True b. False

9. In research reports, you need to report the degrees of freedom for the between groups and within

groups.

a. True b. False

10. The independent variable is labeled as the “Condition” in SPSS Statistics.

a. True b. False

Chapter 15: Test Bank Answers 1. a. Factor 2. d. ANOVA 3. a. ANOVA Sig. 4. b. Compare Means… 5. c. Factor 6. a. True 7. a. True 8. a. True 9. a. True 10. b. False

50

Chapter 16

Chi-Square Goodness-of-Fit Test

Chapter Summary

This chapter covers the purpose of the chi-square goodness-of-fit test and the steps required to calculate it using SPSS Statistics. The chi-square test is used with categorical data, both nominal and ordinal. In the SPSS Statistics output, the probability is indicated by the term “Asymp. Sig.”

When reporting results, report the frequencies for each nominal variable, which are indicated by the term “Observed N” in the SPSS Statistics output. Then, describe the results of the

chi-square significance test. Last, note that the symbol for chi-square is χ2, and remember to report the degrees of freedom.

Chapter Objectives

1. Identify the purpose of the chi-square goodness-of-fit test. 2. Conduct a chi-square goodness-of-fit test. 3. Interpret the results of a chi-square goodness-of-fit test in terms of the null hypothesis and

statistical significance. 4. Present the results of the chi-square goodness-of-fit test in a research report.

Chapter Key Terms

Chi-square Goodness-of-fit test Test variable Asymptotic significance

Null hypothesis Nominal level



• M&M’s Chi-square lab: http://statistics.about.com/od/Activities/a/Chi-SquareActivity.htm

• Chi-square online tutorial: https://statistics.laerd.com/spss-tutorials/chi-square-

goodnessof-fit-test-in-spss-statistics.php

51

Chapter 16 Test Bank Questions 1. The following are terms not associated with chi-square goodness-of-fit, except:

a. Factor. b. Independent-sample Fit line. c. Test variable. d. Control group.

2. SPSS Statistics displays the following outputs for a chi-square goodness-of-fit:

a. Candidate. b. One-Sample Statistics. c. Test Statistics. d. Both A and C.

3. Use the following statistical result to determine if the chi-square goodness-of-fit calculated a statistically significant difference:

a. ANOVA Sig. b. Levene’s Test c. Asymp. Sig. d. One-Sample Test Significance

4. Use the following SPSS Statistics tool to calculate statistical significance for chi-square goodness-of-fit:

a. Descriptives… b. Compare Means… c. Legacy Dialog… d. Chart Editor…

5. In SPSS Statistics, the variable in a chi-square goodness-of-fit is known as:

a. Outcome Variable. b. Test Variable. c. Factor Variable. d. Control Variable.

6. A chi-square goodness-of-fit test requires two or more variables at the nominal level.

a. True b. False

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7. A chi-square goodness-of-fit test is used with data at the scale level. a. True b. False

8. A chi-square goodness-of-fit requires a grouping variable. a. True b. False

9. In research reports, you need to report the degrees of freedom for the chi-square goodness-of-fit sample.

a. True b. False

10. The variable in chi-square goodness-of-fit is labeled as “Test Variable.” a. True b. False

Chapter 16: Test Bank Answers 1. c. Test variable 2. d. Both A and C 3. c. Asymp. Sig. 4. c. Legacy Dialog… 5. b. Test Variable 6. b. False 7. b. False 8. b. False 9. a. True 10. a. True

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Chapter 17

Chi-Square Test of Independence

Chapter Summary

This chapter covers the purpose of the chi-square test of independence and the steps required to calculate it using SPSS Statistics. The chi-square test of independence is used to test for the statistical significance of the relationship between two categorical variables. In the SPSS Statistics output, the probability is indicated by the term “Asymp. Sig.”

When reporting results, report the frequencies for each category, which are provided in the “Category * Category Crosstabulation” table in the SPSS Statistics output. Describe the results of

the chi-square significance test (χ2), and report the degrees of freedom.

Chapter Objectives

1. Identify the purpose of the chi-square test of independence. 2. Conduct a chi-square test of independence. 3. Interpret the results of a chi-square test of independence in terms of the null hypothesis and

statistical significance. 4. Present the results of the chi-square test of independence in a research report.

Chapter Key Terms

Test of Independence Cross tabulation Category Asymptotic significance Row(s) Column(s)



• Test of Independence Tutorial: http://www.ling.upenn.edu/~clight/chisquared.htm

• Two -Way Tables and Chi-Square Tutorial:

http://www.stat.yale.edu/Courses/199798/101/chisq.htm

• Lab - The Case of the Careless Zookeeper:

http://www.amstat.org/education/stew/pdfs/TheCaseoftheCarelessZookeeper.pdf

54

Chapter 17 Test Bank Questions 1. The following are associated with chi-square test of independence, except:

a. Row(s). b. Column(s). c. Test variable. d. Nominal.

2. SPSS Statistics displays the following outputs for a chi-square test of independence:

a. Descriptives. b. Case Processing Summary. c. Chi-Square Tests. d. Both B and C.

3. Use the following statistic to determine if the chi-square test of independence calculated a

statistically significant difference: a. ANOVA Sig. b. Levene’s Test c. Asymp. Sig. d. One-Sample Test Significance

4. Use the following SPSS Statistics tool to calculate statistical significance for chi-square goodness-of-

fit: a. Descriptives… b. Compare Means… c. Legacy Dialog… d. Crosstabs…

5. In SPSS Statistics, the variables in a chi-square test of independence are labeled as:

a. Row(s). b. Column(s). c. Neither A nor B. d. Both A and B.

6. A chi-square test of independence usually involves two variables at the nominal level (though it can

also use two ordinal variables). a. True b. False

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7. A chi-square test of independence can be used with data at the ordinal level. a. True b. False

8. A chi-square test of independence requires a grouping variable.

a. True b. False

9. In research reports, you need to report the degrees of freedom for the chi-square test of independence

along with the frequencies for each category. a. True b. False

10. The statistical tool used for a chi-square test of independence is Cross Tabulation.

a. True b. False

Chapter 17 Test Bank Answers 1. c. Test variable 2. d. Both B and C 3. c. Asymp. Sig. 4. d. Crosstabs… 5. d. Both A and B 6. a. True 7. a. True 8. b. False 9. a. True 10. a. True

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chapter 1 test bank questions

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