Reference no: EM131242890
EXERCISES
Answers to select exercises
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 20 students into the data file.
2. 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 variable 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.sav
3. 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 -not
- firstname -anxeceu
- @edu date
- sex. iq
- grade
4. Using the grades.sav file, make the gpa variable values (which currently have two digits after the decimal point) 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 perform on the numbers.
5. Using grades.sav, search for a student with 121 total points. 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 30o Slope. Their scores follow. Set up the appropriate variable, 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 slope: 30, 50, 51, 26, 37, 32, 37, 29, 52, 54
8. Ten people were given two tests of balance, first while standing on level ground and then while standing on a 30o 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
EXERCISES
Answers to selected exercises can be downloaded at www.pearsonhighered.com/george.
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.
Case Summaries
1. Using the grades.sav file, list variables (in the original order) from id to quiz5, first 30 students consecutive, fit on one page by editing.
2. Using the helping3.sav file, list variables hclose, hseveret, angert, hcontrot, sympathi, worry, obligat, hcopet, first 30 cases, fit on one page by editing.
3. List ID, Iastname, firstname, gender for the first 30 students in the grades.sav with the lower division students listed first, followed by upper division students (lowup variable). Edit output to fit on one page.
Missing Values
4. using the grades.sav file delete the quin1 scores for the first 20 subjects. Replace the (now) missing scores with the average score for all other students in the class. Print out lastname, firstname, quiz1 for the first 30 students. Edit to fit on one page.
Computing Variables
5. Calculate total (the sum of all five quizzes and the final) and percent (100 times the total divided by possible points, 125). Since total and percent are already preset, name the new variables total 1 and percent1. Print out id, total, total 1, percent, percent1, first 30 subjects. Total and percent and percent1 should be identical.
6. 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.
7. Using the grades.sav file, compute a variable named quizsum that is the sum of quiz1 through quiz5. Print out variable id, lastname, firstname, and the new variable quizsum, first 30, all on one page.
Recode Variables
8. Using the grades.sav file, compute a variable named grade1 according to the instructions on page 55.
Print out variables id, lastname, firstname, grade and the new variable grade1, first 30, edit to fit all on one page. If done correctly, grade and grade1 should be identical.
9. Using the grades.sav file; recode a passfaill1 variable so that D's and F's are failing and A's, B's, and C's are passing. Print out variables id, grade, passfail1, first 30, edit to fit all on one page.
10. 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, (labels, not values) first 30 cases, fit on one page.
Selecting Cases
11. Using the divorce.sav file select females (sex = 1); print out id and sex, first 30 subjects, numbered, fit on one page.
12. Select all the students in the grades.sav file with previous GPA less than 2.00, and percentages for the class greater than 85. Print id, GPA, and percent on one page.
13. Using the helping3.sav file, select females (gender = 1 ) who give more than the average amount of help (thelplnz > 0). Print out id, gender, thelpInz, first 30 subjects numbered, fit on one page.
Sorting Cases
14. Alphabetize the grades.sav file by lastname, firstname, Print out lastname, firstname, first 30 cases, edit to fit on one page.
15. Using the grades.sav file, sort by id (ascending order). Print out id, total, percent" and grade, first 30 subjects, fit on one page.
EXERCISES
Answers to selected exercises can be downloaded at www.pearsonhighered.com/george.
All of the following exercises use the grades.sav sample data file.
1. Using a bar chart, examine the number of students in each section of the class along with whether or not students 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 distributed?
6. Create the scatterplot described in Step 5f (page 98). What does the relationship appear to be between gpa and academic performance (total)? Add a regression lines for both men and women to this scatterplot. What do these regression lines tell you?
7 By following all steps on pages 90 and 91, reproduce the bar graph shown on page 91.
8. By following all steps on pages 92 and 93, reproduce the line graph shown on page 93.
9. By following all steps on pages 93, reproduce the pie chart shown on page 93.
10. By following all steps on page 94, reproduce the Boxplot shown on page 95.
11. By following all steps on pages 95 and 96, reproduce the Error Bar Chart shown on page
Note that the edits are not specified on page 96. See if you can perform the edits that produce an identical chart.
12. By following all steps on pages 96 and 97, reproduce the histogram shown on page 97.
13. By following all steps on page 98, reproduce the scatterplot shown on page 98.
EXERCISES
Answers to selected exercises can be downloaded at www.pearsonhighered.com/george.
Notice that data files other than the grades.sav file are being used here. Please refer to the Data Files section starting on page 385 to acquire all necessary information about these files and the meaning of the variables. As a reminder, all data files are downloadable from the web address shown above.
1. Using the grades.sav file select all variables except lastname, firstname, grade, passfail. Compute descriptive statistics including mean, standard deviation, kurtosis, skewness. Skewness. Edit so that you eliminate "S.E. Kurt'' and "S.E. Skew" making your chart easier to interpret.
Edit the output to fit on one page.
- Draw a line through any variable for which descriptives are meaningless (either they are categorical or they are known to not be normally distributed).
- Place an "*" next to variables that are in the ideal range for both skewness and kurtosis.
- Place an X next to variables that are acceptable but not excellent.
- Place a tif next to any variables that are not acceptable for further analysis.
2. Using the divorce.sav file select all variables except the indicators (for spirituality, sp8- sp57, for cognitive coping, cc1 - cc11, for behavioral coping, bc1 - bcl2, for avoidant coping, ac1 -ac7 and for physical closeness, pc1 -pc10). Compute descriptive statistics including mean, standard deviation, kurtosis, skewness. Edit so that you eliminate "S.E. kurt" and S.E. Skew" and your chart is easier to interpret. Edit the output to it on two pages.
- Draw a line through any variable for which descriptives are meaningless (either they pages are categorical or they are known to not be normally distributed).
- Place an "*" next to variables that are in the ideal range for both skewness and kurtosis.
- Place an X next to variables that are acceptable but not excellent.
- Place a IV next to any variables that are not acceptable for further analysis.
3. Create a practice data file that contains the following variables and values:
- VAR1: 3 5 7 6 2 1 4 5 9 5
- VAR2: 9 8 7 6 2 3 3 4 3 2
- VAR3: 10 4 3 5 6 5 4 5 2 9
Compute: the mean, the standard deviation, and variance and print out on a single page.
Attachment:- Assignment.rar