POLITICAL SCIENCE 515 (27790) | ||
| M 4-6:40 | SH 347 | |
| R. Hofstetter NH-119 | MT 6-7 594-6244 | |
| rhofstet@mail.sdsu.edu X |
This course is the first in a
two-semester sequence that introduces
students to the method and applied techniques of
applied empirical research in the social sciences.
Emphasis this semester will be on an
introduction to statistical analysis of behavioral
data, elementary computer literacy using one of the
major statistical packages and a data processing package,
and selected topics in conceptual analysis,
measurement, and scaling. In general, this is a class
in how to do research. It should clarify much of what
is expected in a scientific Masters' thesis project.
The syllabus is intended as a guide to the pace, assignments, and content
of the course. The class may deviate from these dates as necessary
to facilitate comprehension.
Grades will be based on quality of
responses to a series of exercises,
a comprehensive take-home final
examination, and attendance.
Late papers will not be accepted unless I approve
in advance of the due date,
so please do not ask. Rare exceptions may be made but reasons
will not include sporting events (except by SDSU policy),
vacations, or airplane reservations.
Reading should be completed in a manner which
maintains pace with the topics
being discussed and the lectures. Students are expected
to attend all lectures,
computer workshops, and discussions, complete each
exercise by the scheduled time,
and participate in class discussions.
Students may work in teams of up to four persons and
turn in a collective paper. Each student in the team
will be graded based on the team score.
If students on a team complain to me that someone is not doing
his/her share (a "free rider") of work on an exercise I will
reassign that person to a group of one for the rest of
the semester.
I encourage students to sign up for one unit credit
by taking the SPSS Windows
Workshop series (if offered) by SSRL (basement of PSFA).
Students may also wish to
enroll in 1-3 hours of POLS Individual Studies research
under my direction which may be
available depending on the specific situation at the time.
This research
has often resulted in an M.A. or senior theses and joint
publications with students.
SDSU students should obtain an e-mail account. Information
and software are available
through the bookstore at SDSU. The Social Science Research
Laboratory and similar units
on campus offer no-charge training in the use of e-mail, and other
computer procedures. I have
included my e-mail address
on this syllabus to enable students to communicate with me outside my
normal office hours. I anticipate that students will make use of this
opportunity in case they wish to communicate with me outside of office
hours, since I do not use voice mail at SDSU.
September 21 is the last day to add or drop this class.
Academic dishonesty will not be tolerated. All written work must be your original work (i.e., not
previously submitted for credit in any other course, either at SDSU or at any other academic
institution). Please familiarize yourself with the University Policy regarding Cheating and Plagiarism at:
http://www-rohan.sdsu.edu/dept/senate/policy/pfacademics.html And also be aware of the Student
Grievances procedure, available on-line at: http://www.sa.sdsu.edu/srr/statement/sectionVII.html
MATERIALS:
Required:
H. Russell Bernard, Social Research Methods:
Qualitative and Quantitative Approaches.Thousand Oaks, Ca:
Sage Publications,
Inc., 2000.
Fred Davidson, Principles of Statistical Data Handling.
Thousand Oaks, Ca: Sage Publications, Inc., 1996.
Ronald F. Kind, The Strategy of Research: Thirteen Lessons on the
Elements of Social Science, 2004, Chapters 1-4, 9, 10.
Available on line and SDSU library electronic reserve.
Xeroxed materials: Essays, selected chapters of Ronald F. King,
The Strategy of Research: Thirteen Lessons on the
Elements of Social Research. Mimeo, 2005.
Two 3.5" floppy disks formatted for PC.
Recommended but Not Ordered for this Class:
Kate L. Turabian, A Manual for
Writers of Term Papers, Theses, and Dissertations,
(Chicago:
University of Chicago Press, 5th ed., 1987).
Publications Manual of the American Psychological
Association, (Washington, D.C.:
American Psychological Association, 3rd ed., 1989).
Read the journals of your prospective profession and
of other behavioral sciences regularly.
These include but are by no means limited to: American
Political Science Review, American
Journal of Politics, Political Research Quarterly, Journal of
Politics, International Studies
Quarterly, Public Opinion Quarterly, Polity, etc.
Become familiar with SPSS Syntax Reference Guide,
Current Release. Available in SSRL
(Multiple volumes and very expensive to purchase).
REQUIREMENTS:
GRADING:
Graded Exercises 45%
(Go to Exercises)
Final Comprehensive Examination 45%
Attendance 10%
| I. Scientific Inquiry, Research Design,
Measurement, and
Data Processing
| Introductory Xerox Readings: | Sept. 12
| i. C. Richard Hofstetter, "Empirical Analysis Paper."
A concise description of
what should be included in reporting an scientific
analysis whether in a term
paper, M.A. or Senior thesis, or refereed publication.
Xerox Readings.
| ii. Paul R. Gross and Norman Levitt, "Knocking Science
for Fun and Profit,"
Skeptical Inquirer, (March/April, 1995),
pp. 38-41. Xerox Readings.
| ii. Ronald F. Kind, The Strategy of Research: Thirteen Lessons on the
Elements of Social Science, 2004, Chapters 1, 2.
| iv. Comment, "The Intellectual Free Lunch," The
New Yorker, (1994), pp. 4-5. Xerox Readings.
| v. "About Social Science," Chapter 1, H. Russell
Bernard, Social Research
Methods: Qualitative and Quantitative Approaches.
Thousand Oaks, Ca: Sage
Publications, Inc., 2000, pp. 3-26, and "Resources for
Research," Appendix F, pp.
A14-A15.
| vi. v. Ronald F. King, The Strategy of Research: Thirteen
Lessons on the Elements of Social Research.
Mimeo, 2005, Chapter 1, "Lesson 1: Introduction."
| A. Language, Methods, and Techniques
of Science | Sept. 19
| i. "About Social Science," Chapter 1, H. Russell
Bernard, Social Research
Methods: Qualitative and Quantitative Approaches.
Thousand Oaks, Ca: Sage
Publications, Inc., 2000, pp. 3-26, and "Resources
for Research," Appendix F, pp.
A14-A15.
| ii C. Richard Hofstetter, "Political Talk Radio,
Situational Involvement, and Political Mobilization,"
Social Science Quarterly, Vol. 79, No. 2,
(June, 1998), pp. 273-286.
| iii. C. Richard Hofstetter and David Barker with James T.
Smith and Gina M. Zari,
"Information, Misinformation, and Political Talk
Radio," Political Research Quarterly,
Vol. 52, No. 2, (June, 1999), pp. 353-369.
Xerox Readings.
| iv. Ronald F. Kind, The Strategy of Research: Thirteen Lessons on the
Elements of Social Science, 2004, Chapter 3.
| v. Come to class prepared to discuss: C. Richard
Hofstetter and David M. Dozier, "Useful News, Sensational News:
Quality, Sensationalism and Local TV News," Journalism
Quarterly, Vol. 63, No.
4, (Winter, 1986), pp. 815-820, 853. Xerox readings.
| NOTE: Exercise 1 Due September 26.
| B. Research Design | Sept. 26
| i. "The Foundations of Social Research," Chapter 2, H. Russell
Bernard, Social Research Methods:
Qualitative and Quantitative Approaches.
Thousand Oaks, Ca: Sage Publications,
Inc., 2000, pp. 29-64, and "Preparing
for Research," Chapter 3, pp. 65-99.
| ii. Ronald F. King, The Strategy of Research:
Thirteen Lessons on the Elements of Social Research.
Mimeo, 2005, Chapter 4, "Lesson 4: Causal Modeling
(I): Bivariate Linear Representations."
| iii. Ronald F. Kind, The Strategy of Research: Thirteen Lessons on the
Elements of Social Science, 2004, Chapter 4, 9.
| Exercise 1 due.
| Exercise 2 due September 30.
LAST DAY TO ADD OR DROP THIS CLASS: September 21, 2003.
LAST DAY TO APPLY FOR October, 2005, graduateion
| C. Research Design | Oct. 3
| i. "Research Design: Experiments and Experimental Thinking,"
Chapter 4, H.
Russell Bernard, Social Research Methods: Qualitative
and Quantitative
Approaches. Thousand Oaks, Ca: Sage Publications,
Inc., 2000, pp. 103-142.
| ii. Ronald F. Kind, The Strategy of Research: Thirteen Lessons on the
Elements of Social Science, 2004, Chapter 10.
| NOTE: Exercise 2 due October 10.
| E. Introduction to Sampling. | Oct. 10
| i. "Sampling," Chapter 5, H. Russell Bernard, Social
Research Methods: Qualitative
and Quantitative Approaches. Thousand Oaks, Ca:
Sage Publications, Inc.,
2000, pp. 143-185.
| ii. "Sampling" Xeroxed materials.
| Exercise 2 due.
Optional revision of exercise 1 due.
NOTE: Exercise 3 due October 17.
| D. Interviewing and Surveys | Oct. 17
| i. "Interviewing: Unstructured and Semistructured," Chapter 6,
H. Russell Bernard,
Social Research Methods: Qualitative and Quantitative
Approaches. Thousand
Oaks, Ca: Sage Publications, Inc., 2000, pp. 189-225,
and "Structured
Interviewing," Chapter 7, pp. 227-283.
| ii. "Interviewing Instructions" Xeroxed materials. WEB ADDRESS????
| iii. Exercise 3 due.
| E. Content Analysis
| Oct. 24
| i. "Qualitative Data Analysis I: Text Analysis,"
Chapter 12, H. Russell Bernard, Social Research
Methods: Qualitative and Quantitative Approaches.
Thousand Oaks, Ca: Sage Publications, Inc., 2000,
pp. 437-469.
| ii. Skim article for content analysis. Read later more
carefully for reliability and
validity.Paul J. Strand and C. Richard
Hofstetter, "Television News Coverage of the
1972 Election: A Convergent and Discriminant
Validation of Some Content
Indicators," Political Methodology, Vol. 3, (1976),
pp. 507-522. Xerox Readings.
NOTE: Exercise 4 due October 31.
| E. Data and Data Processing: Data Matrix
| Oct. 31
| i. "Introduction to Qualitative and Quantitative Analysis,"
Chapter 11, H. Russell
Bernard, Social Research Methods: Qualitative and
Quantitative Approaches.
Thousand Oaks, Ca: Sage Publications, Inc., 2000, pp. 417-436.
| ii. "Introduction: A Principled Approach," Fred Davidson,
Principles of Statistical
Data Handling. Thousand Oaks, Ca: Sage Publications,
Inc., 2000, pp. 1-22,
and "Data Input," Chapter 2, pp. 23-55.
| Exercise 4 due.
| NOTE: Exercise 5, 6 due November 21.
| G. SPSS: Familiarization Laboratory
| Nov. 7
| G. Analysis, Data Entry
| Nov. 14
| G. Measurement and Scaling
| Nov. 21
| i. "Scales and Scaling," Chapter 8, H. Russell
Bernard, Social Research Methods:
Qualitative and Quantitative Approaches.
Thousand Oaks, Ca: Sage Publications,
Inc., 2000, pp. 285-316.
| Exercises 5, 6 due.
NOTE: Exercise 7 due November 28.
| H. Reliability and Validity
| Nov. 28
| i. Samuel Messick, "The Once and Future Issues of
Validity: Assessing the
Meaning and Consequences of Measurement," in H.
Wainer and H. I. Braun (eds.),
Test Validity, Hillsdale, N.J.: Erlbaum, 1988.
Xeroxed Readings.
| ii. Educational Measurement: Issues and Practice,
Vol. 16, No. 2, (Summer,
1997): "Editorial: The Great Validity Debate," p. 4,
Lorrie A. Shepard, "The
Centrality of Test Use and Consequences for Test
Validity," pp. 5-8, 13, 24, W.
James Popham, "Consequential Validity: Right Concern,
Wrong Concept," pp. 9-13,
Robert L. Linn, "Evaluating the Validity of Assessments:
The Consequences of
Use," pp. 14-16, William A. Mehrens, "The Consequences of
Consequential
Validity," pp. 16-18. Xeroxed Readings.
| iii. Stuart W. Cook & Claire Selltiz, "A Multiple-Indicator
Approach to Attitude
Measurement, " Psychological Bulletin, Vol. 62,
(1964), pp. 36-55.
Xerox Readings .
| iv. Donald T. Campbell & Donald W. Fiske, "Convergent and
Discriminant
Validation by the Multitrait-Multimethod Matrix,"
Psychological Bulletin,
Vol. 56, (1959), pp. 81-105. Xerox Readings .
| v. Paul J. Strand & C. Richard Hofstetter, "Television
News Coverage of the 1972
Election: A Convergent and Discriminant Validation of
Some Content Indicators,"
Political Methodology, Vol. 3, (1976), pp. 507-522.
Xerox Readings .
| Exercise 7 due.
NOTE: Exercise 8, 9 due December 5.
| II. Data Processing, Analysis
| II. Data Manipulation and Processing
| Dec. 5
| i. "Data Manipulation," Fred Davidson, Principles of
Statistical Data Handling.
Thousand Oaks, Ca: Sage Publications, Inc., 2000,
Chapter 3, pp. 56-114, and
"Data Debugging,," Chapter 4, pp. 115-145.
| ii. Exercises 8, 9 due.
Exercise 10 due December 12.
| iii. Distribute Take Home examination. (DUE: December 12)
| B. Discussion
| Dec. 12
| Exercise 10 due.
| Take Home Examination Due.
| | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
| Instructions: Non-statistical exercises
are to be typed and
double-spaced, although diagrams may be
drawn in by hand so long as the
work is neat and orderly. Handwritten
interpretations of statistical
analyses will be accepted as long as they
are legibly written/printed.
Each exercise will be graded on a 0-10 point scale.
Exercises may be completed by teams of up to four
students working collectively. Each student in a group will receive
the grade given to the group's paper.
| EXERCISE 1
| Write a short, concise (not to exceed two double-spaced pages each using a
type font of 10 pt. or larger and one inch
margins) paper for each Reading (1.A.ii. And 1.A.iii.).
The premium in this exercise is to be concise and precise.
materials. A.ii and A.iii are available in xeroxed materials.
Focus on the 4-5 most important concepts.
The papers should include:
|
EXERCISE 2
| Write a (not to exceed) one-page paper based on
each article used to complete
Exercise 1 (Readings A.ii and A.iii). Each paper should include:
|
EXERCISE 3
| Design a sampling frame to produce a random-digit-dial (RDD)
sample of the
adult population of San Diego that can be reached by
residential telephone.
|
EXERCISE 4
| Design and execute a content analysis of the extent to
which two issues of a daily newspaper provides enlightenment about
public policy and the operation of politics. Using the same design,
execute a parallel content analysis of the extent to which two issues
of a second daily newspaper provides similar enlightenment. Sample
10 items from each newspaper (if at least 10 items are not include
in each issue, select another newspaper). Be sure to include
standard measures of length and position of items. Turn in:
|
EXERCISE 5
| Using the questionnaires at the end of the xeroxed reading, complete preliminary
processing of raw data using SPSS. The exercise requires you to:
|
| ||||||||||
Political Science
Each student will prepare one or more empirical analyses of some topic within the general field for which data from a reputable research institution are available. The paper is to be formatted like an article that would appear in any one of the following journals (the styles differ a bit by journal, but any are appropriate for the assignhment): American Journal of Sociology, American Journal of Political Science, Social Forces, American Sociological Review, Public Opinion Quarterly, and American Political Science Review. Each student should read at least one article in one of the above journals before writing his/her paper in order to be certain that the paper you read as a model includes data analysis.
In general, student papers must include at least:
1) Introduction, A presentation of hypotheses to be tested in the paper that are thoroughly grounded in empirical research related to the topic. This section should constitute a review of the literature and an explicit statement of research hypotheses. Background reading should be reviewed and cited in the introductory section of the paper.
2) Methodology. Researchers commonly devote a short section (although the length of the methodology section may vary according to the purpose of a particular paper) to outlining the type and source of date that are to be used in an analysis, and, if sampling is employed, a full discussion of the sampling procedures and the universe from which the sample has been drawn. Also, a complete discussion of exactly how key concepts are operationalized should be given in this section. It is important to include sufficient information so that another can replicate the study. If secondary analysis is employed in the analysis, it is usually sufficient to cite the source of the data (e.g., Inter-University Consortium for Social and Political Research), briefly state the nature of the sampling frame employed (e.g., multi-stage probability sample of American adults, Random-Digit-Dial sample of adults in San Diego, California) specify the date of the data collection (e.g., interviews conducted shortly before and following the 2000 presidential election), and to excuse the survey organization of errors that might appear in the analysis (e.g., I alone am responsible for errors that might appear herein).
3) Empirical Analyses. In this section, you should very briefly review your hypotheses, and systematically test them. Testing begins by analyzing your data in its simplest form, i.e., contingency tables without controls. Describe your findings from the initial texts, and relate them to the hypotheses you presented in the initial section of the paper systematically. If your data do not support your initial hypotheses, then speculate why this might be the case. If the data do not support your initial hypotheses, then speculate on how the analysis might be, i.e., what variables you might add to the analysis or control. In either instance, you should introduce control variables at this stage of the analysis. Again, fully describe the findings of the analysis that employs control variables, relate these findings to the initial hypotheses, and speculate about how further extensions of the analysis might be made. Also speculate about the probable cause of inconsistencies between your findings and your initial theory.
4) Conclusion and Summary. Briefly and concisely summarize the preceding three sections of the paper, paying particular attention to your findings. Then make a summary statement of how your analysis and findings fit into the larger body of literature in the field, and where further research on the particular topic analyzed in your paper should go.
Political Science
We are concerned with three types of variables. The dependent variable, the independent variable, and the control variable. The dependent variable is the variable we want to explain. (in the example below, whether the U.S. should send troops to invade Canada) The independent variable is the variable we are using to try to explain the dependent variable. (In this case, the respondents' ideological bias liberal or conservative). The hypothesis is that liberals will be opposed to sending troops into Canada and conservatives will be for sending troops into Canada. Classifying position on sending troops into Canada by ideological categories might produce a table of frequencies that looks like Table 1.
| Table 1 | |||
|---|---|---|---|
| Position on Sending Troops to Canada by Ideology. | |||
| Number of | |||
| Position on Issue: | Liberals | Conservatives | Respondents |
| For Sending Troops | 100 | 200 | (300) |
| Against Sending Troops | 400 | 300 | (700) |
| Number of Respondents | (500) | (500) | (1000) |
In a sample of 1,000 people, we have 500 liberals, 500 conservatives, and 300 who are for sending in troops, and 700 who are against sending in troops. (The numbers in parenthesis are the "marginal" or "univariate" distributions.) The internal numbers in the table show that 100 people are liberal and also in favor of sending troops in, 400 are liberal and against sending troops, 200 are both conservative and for sending in troops, and 300 are both conservative and against sending in troops. Since tables are rarely as balanced as this one, cell frequencies are always presented as percentages rather than raw numbers. Percentages permit one to draw precise conclusions about different rates of behavior among groups of different absolute size.
When we convert the frequencies into percentages there are two possibilities: 1) We can percentagize by the dependent variable so that the rows total up to 100 percent (Table 2); or 2) we can percentagize by the independent variable so that the columns add up to 100 percent (Table 3).
| Table 2 | ||||
|---|---|---|---|---|
| Ideology by Troop Preference. | ||||
| Number of | ||||
| Position on Issue: | Liberals | Conservatives | Total | Respondents |
| For Sending Troops | 33.3% | 66.7 | 100.0% | (300) |
| Against Sending Troops | 57.1% | 42.9 | 100.0% | (700) |
| Table 3 | ||||
|---|---|---|---|---|
| Troop Preference by Ideology. | ||||
| Position on Issue: | Liberals | Conservatives | ||
| For Sending Troops | 20.0% | 40.0% | ||
| Against Sending Troops | 80.0 | 60.0 | ||
| Total | 100.0% | 100.0% | ||
| (N) | (500) | (500) | ||
The two ways of percentagizing give different figures and are read differently. Table 2 is read: Of those who are in favor of sending troops, 33.3 percent are liberals and 66.7 percent are conservatives. Of' those who are against sending troops, 57.1 percent are liberals and 42.8 percent are conservatives.
Table 3 is read: Of the liberals, 20 percent are in favor of sending troops into Canada and 80 percent are opposed to doing so. Of the conservatives, 40 percent are for sending troops into Canada and 60 percent are opposed to it. Table 3 shows the correct way to percentagize the table because we are interested in the effect of ideology on sending "troops in Canada." We hypothesize that ideology causes issue position so that ideology is the independent variable and issue position (troops to Canada) is the dependent variable. As ideology shifts from liberal to conservative, we anticipate greater support for sending troops into Canada.
A control variable can now be introduced to increase our understanding of the original two variable relationship. Suppose, for example, we think that a conservative respondent does not favor sending in troops (the hypothesized liberal response) because he prefers the use of nuclear weapons. We can control for, or hold constant, the respondents' position on nuclear weapons and then look at the effect of this third variable on the original two. In the following tables respondents have been separated according to whether they approve (Table 4) or disapprove (Table 5) of the use of nuclear weapons.
| Table 4 | ||||
|---|---|---|---|---|
| Troop Preference by Ideology among Those Who Approve Nuclear Weapons | ||||
| Position on Issue: | Liberals | Conservatives | ||
| For Sending Troops | 100.0% | 66.7% | ||
| Against Sending Troops | 0.0 | 33.3 | ||
| Total | 100.0% | 100.0% | ||
| (N) | (50) | (150) | ||
Only those respondents who are in favor of the use of nuclear weapons.
| Table 4 | ||||
|---|---|---|---|---|
| Troop Preference by Ideology among Those Who Disapprove Nuclear Weapons | ||||
| Position on Issue: | Liberals | Conservatives | ||
| For Sending Troops | 12.5% | 28.5% | ||
| Against Sending Troops | 87.5 | 71.5 | ||
| Total | 100.0% | 100.0% | ||
| (N) | (450) | (350) | ||
Only those respondents who are oppose to the use of nuclear weapons.
The data in Table 4 show that all of the liberals who were for the use of nuclear weapons also favored sending troops into Canada while two-thirds of the pro-nuclear weapons conservatives took such a position. This lends some support to the supposition that there were conservatives who made the hypothesized liberal response for the "wrong" reason--or at least a reason that was not expected when the initial relationship between the two variables was predicted.
| COLUMNS: | |
| Nation | |
| Crude birth rate (number of births per 1000 population size) | |
| Womens economic activity (female labor force as percent of male) | |
| Female adult literacy rate |
| DATA | |||
|---|---|---|---|
| Algeria | 29.0 | 11 | 73 |
| Argentina | 19.5 | 38 | 88 |
| Australia | 14.1 | 61 | 93 |
| Brazil | 21.2 | 38 | 80 |
| Canada | 13.7 | 63 | 95 |
| China | 17.8 | 81 | 59 |
| Cuba | 14.5 | 50 | 77 |
| Denmark | 12.4 | 77 | 92 |
| Egypt | 28.7 | 12 | 61 |
| France | 13.0 | 64 | 93 |
| Germany | 11.0 | . | 92 |
| India | 27.8 | 34 | 44 |
| Iraq | 43.6 | 29 | 62 |
| Israel | 20.4 | 49 | 91 |
| Japan | 10.7 | 64 | 94 |
| Malaysia | 28.0 | 55 | 75 |
| Mexico | 26.6 | 37 | 84 |
| Nigeria | 43.3 | 51 | 41 |
| Pakistan | 41.8 | 16 | 48 |
| Philippines | 30.4 | 44 | 68 |
| Russia | 12.6 | 70 | 85 |
| South Africa | 33.4 | 54 | . |
| Spain | 11.2 | 31 | 98 |
| United Kingdom | 13.2 | 60 | 92 |
| United States | 15.2 | 65 | 94 |
| Vietnam | 26.3 | 82 | 89 |
DATA LIST FREE / State(A2) VR MR M W H P S.
BEGIN DATA
The following is abstracted from J. Scott Long, "Notes
on Writing Effective Papers for S650-2000: Categorical
Data Analysis," but is highly pertinent to this and any
other class you take in a university.
Long states and I agree that "...The care in which an idea
is presented affects the chances of an article being
accepted. Before you turn in your assignments, think
about whether you are presenting your material as effectively
as possible. This handout provides some suggestions that
can make your work for (this class...) and your later professional
work more effective. As with most rules, there are exceptions."
General Points
i. "data are" not "data is"
ii. "effect" and "affect"
iii. "Ph.D." not "PH.D.", or "Ph.d.", etc.
Organizing Your Paper
Statistical Points
In General
AK 761 9.0 41.8 75.2 86.6 9.1 14.3
AL 780 11.6 67.4 73.5 66.9 17.4 11.5
AR 593 10.2 44.7 82.9 66.3 20.0 10.7
AZ 715 8.6 84.7 88.6 78.7 15.4 12.1
CA 1078 13.1 96.7 79.3 76.2 18.2 12.5
CO 567 5.8 81.8 92.5 84.4 9.9 12.1
CT 456 6.3 95.7 89.0 79.2 8.5 10.1
DE 686 5.0 82.7 79.4 77.5 10.2 11.4
FL 1206 8.9 93.0 83.5 74.4 17.8 10.6
GA 723 11.4 67.7 70.8 70.9 13.5 13.0
HI 261 3.8 74.7 40.9 80.1 8.0 9.1
IA 326 2.3 43.8 96.6 80.1 10.3 9.0
ID 282 2.9 30.0 96.7 79.7 13.1 9.5
IL 960 11.4 84.0 81.0 76.2 13.6 11.5
IN 489 7.5 71.6 90.6 75.6 12.2 10.8
KS 496 6.4 54.6 90.9 81.3 13.1 9.9
KY 463 6.6 48.5 91.8 64.6 20.4 10.6
LA 1062 20.3 75.0 66.7 68.3 26.4 14.9
MA 805 3.9 96.2 91.1 80.0 10.7 10.9
MD 998 12.7 92.8 68.9 78.4 9.7 12.0
ME 126 1.6 35.7 98.5 78.8 10.7 10.6
MI 792 9.8 82.7 83.1 76.8 15.4 13.0
MN 327 3.4 69.3 94.0 82.4 11.6 9.9
MO 744 11.3 68.3 87.6 73.9 16.1 10.9
MS 434 13.5 30.7 63.3 64.3 24.7 14.7
MT 178 3.0 24.0 92.6 81.0 14.9 10.8
NC 679 11.3 66.3 75.2 70.0 14.4 11.1
ND 82 1.7 41.6 94.2 76.7 11.2 8.4
NE 339 3.9 50.6 94.3 81.8 10.3 9.4
NH 138 2.0 59.4 98.0 82.2 9.9 9.2
NJ 627 5.3 100.0 80.8 76.7 10.9 9.6
NM 930 8.0 56.0 87.1 75.1 17.4 13.8
NV 875 10.4 84.8 86.7 78.8 9.8 12.4
NY 1074 13.3 91.7 77.2 74.8 16.4 12.7
OH 504 6.0 81.3 87.5 75.7 13.0 11.4
OK 635 8.4 60.1 82.5 74.6 19.9 11.1
OR 503 4.6 70.0 93.2 81.5 11.8 11.3
PA 418 6.8 84.8 88.7 74.7 13.2 9.6
RI 402 3.9 93.6 92.6 72.0 11.2 10.8
SC 1023 10.3 69.8 68.6 68.3 18.7 12.3
SD 208 3.4 32.6 90.2 77.1 14.2 9.4
TN 766 10.2 67.7 82.8 67.1 19.6 11.2
TX 762 11.9 83.9 85.1 72.1 17.4 11.8
UT 301 3.1 77.5 94.8 85.1 10.7 10.0
VA 372 8.3 77.5 77.1 75.2 9.7 10.3
VT 114 3.6 27.0 98.4 80.8 10.0 11.0
WA 515 5.2 83.0 89.4 83.8 12.1 11.7
WI 264 4.4 68.1 92.1 78.6 12.6 10.4
WV 208 6.9 41.8 96.3 66.0 22.2 9.4
WY 286 3.4 29.7 95.9 83.0 13.3 10.8
DC 2922 78.5 100.0 31.8 73.1 26.4 22.1
DESCRIPTIVES VARIABLES=ALL.
END DATA.
VARIABLE LABELS VR 'Violent crime rate'/
MR 'Murder rate'/
M 'Percent in metropolitan areas'/
W 'Percent white'/
H 'Percent high school graduates'/
P 'Percent below the poverty level'/
S 'Percent of families headed by a single parent'.
EXECUTE.
Some Points on Writing a Paper