SPSS for Windows Step by Step A Simple Guide and Reference Fourth Edition (11.0 update) Answers to Selected Exercises Darren George, Ph. Canadian University College with Paul Mallery, Ph. La Sierra University 2 SPSS for Windows Step by Step Answers to Selected Exercises Detailed Table of Contents Detailed Table of Contents. 5 Chapter 3: Creating and Editing a Data File.
8 Chapter 4: Managing Data. 20 Chapter 7: Descriptive Statistics. 22 SPSS for Windows Step by Step Answers to Selected Exercises 3 Chapter 8: Crosstabulation and χ Analyses. 25 Chapter 9: The Means Procedure.
28 Chapter 10: Bivariate Correlation. 30 Chapter 11: The T Test Procedure. 35 Chapter 12: The One-Way ANOVA Procedure. 39 Chapter 14: Three-Way ANOVA.
45 Chapter 15: Simple Linear Regression. 49 Chapter 16: Multiple Regression Analysis. 52 4 SPSS for Windows Step by Step Answers to Selected Exercises 16-4. 52 Chapter 18: Reliability Analysis.
55 Chapter 23: MANOVA and MANCOVA. 59 Chapter 24: Repeated-Measures MANOVA. 61 SPSS for Windows Step by Step Answers to Selected Exercises 5 General Notes The following answers are in some cases fairly complete. In other cases, only portions of the answer are included.
The data files used are available for download at http://www. Check with your instructor to find exactly what she or he wants you to turn in. We list the questions from each chapter first, followed by answers to selected exercises. 6 SPSS for Windows Step by Step Answers to Selected Exercises Chapter 3: Creating and Editing a Data File 1.
Set up the variables described above for the grades.sav file, using appropriate variable names, variable labels, and variable values. Enter the data for the first five students into the data file. Perhaps the instructor of the classes in the grades.sav dataset teaches these classes at two different schools. Create a new variable in this dataset named school, with values of 1 and 2.
Create vari- able labels, where 1 is the name of a school you like, and 2 is the name of a school you don’t like. Save your dataset with the name gradesme. Which of the following variable names will SPSS accept, and which will SPSS reject? For those that SPSS will reject, how could you change the variable name to make it “legal”? age firstname @edu sex. grade not anxeceu date iq 4.
Using the grades.sav file, make the gpa variable values (which currently have two digits after the decimal place) have no digits after the decimal point. You should be able to do this without retyping any numbers. Note that this won’t actually round the numbers, but it will change the way they are displayed and how many digits are displayed after the decimal point for statistical analyses you per- form on the numbers.sav, search for a student who got 121 on the final exam. What is his or her name? 6.
Why is each of the following variables defined with the measure listed? Is it possible for any of these variables to be defined as a different type of measure? ethnicity Nominal extrcred Ordinal quiz4 Scale grade Nominal 7. Ten people were given a test of balance while standing on level ground, and ten other people were given a test of balance while standing on a 30° slope. Their scores follow. Set up the appropriate variables, and enter the data into SPSS.
Scores of people standing on level ground: 56, 50, 41, 65, 47, 50, 64, 48, 47, 57 Scores of people standing on a slope: 30, 50, 51, 26, 37, 32, 37, 29, 52, 54 SPSS for Windows Step by Step Answers to Selected Exercises 7 8. Ten people were given two tests of balance, first while standing on level ground and then while standing on a 30° slope. Their scores follow. Set up the appropriate variables, and enter the data into SPSS.
Participant: 1 2 3 4 5 6 7 8 9 10 Score standing on level ground: 56 50 41 65 47 50 64 48 47 57 Score standing on a slope: 38 50 46 46 42 41 49 38 49 55 3-2 The variable view screen might look something like this once the new variable is set up: 3-3 Variable SPSS What could be changed? Name will… Age Accept firstname Reject Variable names can only be up to 8 characters long…maybe use “firstnam” 3-5 Dawne Rathbun received a score of 121 for the course. No one received a score of 121 on the final exam. 3-6 Variable Currently de- Could also be defined as fined as ethnicity Nominal Ethnicity will generally be defined as a nominal variable. The only exceptions might be if, for example, you were examining the relative size of different eth- nicities in a certain population.
In that case, where ethnicity has other theo- retical meaning, ethnicity could be defined as an ordinal variable. 8 SPSS for Windows Step by Step Answers to Selected Exercises 3-7 The variable view should look something like this, with one variable identifying whether the person was standing on level or sloped ground and a second variable identifying each person’s balance score: Once the data is entered, the data view should look something like this: 3-8 Note that, because each person took the balance test both on level ground and on a slope, there are ten rows (one for each person) rather than twenty rows (one for each time the balance test was given). SPSS for Windows Step by Step Answers to Selected Exercises 9 Chapter 4: Managing Data Some of the exercises that follow change the original data file. If you wish to leave the data in their original form, don’t save your changes.
Using the grades.sav file, list variables (in the original order) from id to quiz5, first 30 students con- secutive, number cases, fit on one page by editing. Using the helping3.sav file, list variables hclose, hseveret, angert, controt, sympathi, worry, obli- gat, hcopet, first 30 cases, number cases, fit on one page by editing. List the first 20 students in the grades.sav file, with the lower division students listed first, followed by the upper division students. Using the grades.sav file delete the quiz1 scores for the cases selected in exercise 3, above.
Re- place the (now) missing scores with the average score for all other students in the class. Now that you have changed the quiz1 scores (in exercise 4), recalculate total (the sum of all five quizzes and the final) and percent (100 times the total divided by the points possible, 125). Using the divorce.sav file compute a variable named spirit (spirituality) that is the mean of sp8 through sp57 (there should be 18 of them). Print out id, sex, and the new variable spirit, first 30 cases, edit to fit on one page.
Using the grades.sav file, compute a variable named quizsum that is the sum of quiz1 through quiz5. Print out variables id, lastname, firstnam, and the new variable quizsum, first 30, all on one page. Using the grades.sav file, compute a variable named grade2 according to the instructions on page 47. Print out variables id, lastname, firstnam, grade and the new variable grade2, first 30, edit to fit all on one page.
If done correctly, grade and grade2 should be identical. Recode the passfail variable so that D’s and F’s are failing, and A’s, B’s, and C’s are passing. Using the helping3.sav file, redo the coding of the ethnic variable so that Black = 1, Hispanic = 2, Asian = 3, Caucasian = 4, and Other/DTS = 5. Now change the value labels to be consistent with reality (that is the coding numbers are different but the labels are consistent with the original ethnicity).
Print out the variables id and ethnic, first 30 cases. Using the divorce.sav file select females (sex = 1); print out id and sex, first 40 subjects, num- bered, fit on one page. 10 SPSS for Windows Step by Step Answers to Selected Exercises 12. Select all of the students in the grades.sav file whose previous GPA’s are less than 2, and whose percentages for the class is greater than 85.
Using the helping3.sav file, select females (gender = 1) who give more than the average amount of help (thelplnz > 0). Print out id, gender, thelplnz, first 40 subjects, numbered, fit on one page. Alphabetize the grades.sav file by lastname, firstnam, first 40 cases. Using the grades.sav file, sort by id (ascending order).
Print out id, total, percent, and grade, first 40 subjects, fit on one page. 4-2 Case Summaries HCLOSE HSEVERET ANGERT HCONTROT SYMPATHI WORRY OBLIGAT HCOPET 1 5 4.0 SPSS for Windows Step by Step Answers to Selected Exercises 11 4-3 Case Summaries LASTNAME FIRSTNAM LOWUP 1 lower 1 VILLARRUZ ALFRED 2 OSBORNE ANN 3 LIAN JENNY 4 MISCHKE ELAINE Total N 4 4 2 upper 1 VALAZQUEZ SCOTT 2 GALVEZ JACKIE 3 GUADIZ VALERIE 4 RANGIFO TANIECE 5 TOMOSAWA DANIEL 6 BAKKEN KREG 7 LANGFORD DAWN 8 VALENZUELA NANCY 9 SWARM MARK 10 KHOURY DENNIS 11 AUSTIN DERRICK 12 POTTER MICKEY 13 LEE JONATHAN 14 DAYES ROBERT 15 STOLL GLENDON 16 N CUSTER JAMES Total 16 16 Total N 20 20 a Limited to first 20 cases. 4-5 Follow sequence steps 5c and 5c’ to complete this calculation. 12 SPSS for Windows Step by Step Answers to Selected Exercises 4-6 Case Summaries ID SEX SPIRIT 1 1 1 female 3.33 Total 30 30 30 a Limited to first 30 cases.
SPSS for Windows Step by Step Answers to Selected Exercises 13 4-8 Case Summaries ID LASTNAME FIRSTNAM GRADE GRADE2 1 106484 VILLARRUZ ALFRED D D 2 108642 VALAZQUEZ SCOTT C C 3 127285 GALVEZ JACKIE C C 4 132931 OSBORNE ANN B B 5 140219 GUADIZ VALERIE B B a Limited to first 30 cases. 4-9 Follow sequence step 5d’ but use a range of 70 to 100 for “P”, and 0 to 69. 4-11 ID SEX 1 1 1 female 2 2 1 female 3 3 1 female 4 4 1 female 5 5 1 female 4-12 Case Summaries ID LASTNAME FIRSTNAM GPA PERCENT 1 140219 GUADIZ VALERIE 1.2 Total N 2 2 2 2 2 a Limited to first 100 cases. 4-14 ID LASTNAME FIRSTNAM 1 779481 AHGHEL BRENDA 2 777683 ANDERSON ERIC 3 211239 AUSTIN DERRICK 4 420327 BADGER SUZANNA 5 157147 BAKKEN KREG 14 SPSS for Windows Step by Step Answers to Selected Exercises 4-15 ID TOTAL PERCENT GRADE 1 988808 107 85.6 C Total N 40 40 40 40 a Limited to first 40 cases.
SPSS for Windows Step by Step Answers to Selected Exercises 15 Chapter 5: Graphs All of the following exercises use the grades.sav sample data file. Using a bar chart, examine the number of students in each section of the class along with whether or not student attended the review session. Does there appear to be a relation between these variables? 2. Using a line graph, examine the relationship between attending the review session and section on the final exam score.
What does this relationship look like? 3. Create a boxplot of quiz 1 scores. What does this tell you about the distribution of the quiz scores? Create a boxplot of quiz 2 scores. How does the distribution of this quiz differ from the distribution of quiz 1? Which case number is the outlier? 4.
Create an error bar graph highlighting the 95% confidence interval of the mean for each of the three sections’ final exam scores. What does this mean? 5. Based on the examination of a histogram, does it appear that students’ previous GPA’s are normally dis- tributed? 6. Create the scatterplot described in Step 5g.
What does the relationship appear to be between gender and academic performance? Add a regression line to this scatterplot. What does this regression line tell you?