QUANTITATIVE ANALYSIS OF SOCIAL DATA

Instructor: Susan J. Thompson

105 Silsby Hall
646-2541
BlitzMail: susan.j.thompson@dartmouth.edu

X-hour classes will be held in the Kiewit Instructional Center. X-hours will be used as tutorial hours for students having difficulties with their data exercises. X-hour attendance is at the discretion of each student.

Course Description:
This course introduces students to the quantitative tools of data analysis in the social sciences. The course covers the conceptual and applied aspects of the research process, secondary data and its limitations, as well as the basic statistics of quantitative analysis. Topics include deriving hypotheses from theories and conceptual models, operationalizing concepts, experimental and quasi-experimental designs, sampling, data management, and statistical analysis. The emphasis of the course is on the application of quantitative research methods to sociological issues. Students will learn how to design and implement research projects using the 1990 U.S. Census of Population and Housing PUMS 5% Sample and a statistical/analytical software program (SPSS 6.1 for Macintosh). The course does not require a background in statistical analysis nor more mathematical background than high school algebra. The primary goal of the course is to enable students to be critical users of quantitative analytical methods. Students will gain both a familiarity with the strengths and weaknesses of these methods and become reasonably proficient with using a statistical package to analyze and derive meaningful conclusions about social phenomena.

Required Texts:

R. Mark Sirkin, Statistics for the Social Sciences, Thousand Oaks, CA: Sage, Publications, 1995.

Charles C. Ragin, Constructing Social Research: The Unity and Diversity of Method. Thousand Oaks, CA: Pine Forge Press, 1994.

Poverty: A Reader. (Available at the Dartmouth Bookstore)

Recommended Texts:

Marija J. Norusis, SPSS: SPSS 6.1 Guide to Data Analysis. Englewood Cliffs, NJ: Prentice Hall, n.d.

Mark H. Maier, The Data Game: Controversies in Social Science Statistics. 2nd Edition. Armonk, NY: M. E. Sharpe, 1995.

Course Requirements:

I. Students will complete nine data exercises based on the readings and class lectures. These data exercises of approximately 3-5 pages each will illustrate the main concepts and statistical techniques of quantitative social analysis using data provided by the Inter-University Consortium for Political and Social Research (ICPSR) from the 1990 U.S. Census of Population and Housing PUMS 5% Sample and SPSS 6.1 for Macintosh. The due date for these data exercises will be one week after each exercise is distributed in class. The nine data exercises will constitute 45% of your final grade.

II. Students will write a final paper based on the data exercises. This assignment will be described in detail at a later date. The final paper is due 9 December. This paper will constitute 45% of your final grade.

III. The class format will be lecture/discussion. You are expected to attend all classes and be prepared to participate in class discussion with questions and comments on the day's readings or on the data exercises. Class attendance and participation will constitute 10% of your final grade.

IV. You are encouraged to discuss your work with others, but the final product is your own. Paraphrasing of other students' work is a violation of the Honor Principle as is Plagiarism.

Grading:

The grade for this course will be based on the data exercises, final paper, and class participation. The data exercises and final paper will be evaluated in terms of (1) how well you understand and are able to ³reason with² the methodological principles discussed in class and presented in the readings, and (2) how proficiently you can apply these principles to an evaluation of the results obtained in analyzing the data.

Data Exercises	45%
Final Paper	45%
Class Attendance and Participation	10%

Outline of Topics:

Section 1:	Social Research and Social Research Data
	Data Exercise #1: Data Presentation
Section 2:	Research Design
	Data Exercise #2: The Research Question
Section 3:	Measurement
	Data Exercise #3: Concepts, Variables & Measures
Section 4:	Measures of Central Tendency and Dispersion
	Data Exercise #4: Descriptive Statistics
Section 5:	Contingency Tables and Statistical Inference
	Data Exercise #5: Contingency Tables & Causal Models
Section 6:	Inferential Statistics
	Data Exercise #6: Sampling
Section 7:	Probability Distributions and Differences Between Means
	Data Exercise #7: Bivariate Statistics
Section 8:	One-Way and Two-Way Analysis of Variance (ANOVA)
	Data Exercise #8: One-Way ANOVA
Section 9:	Measures of Association and the Chi-Square Test
	Data Exercise #9: Partial Tables & Measures of Association
Section 10:	Correlation and Regression
	Data Exercise #10: Correlation & Regression Analysis

Week 1 (25 September - 30 September) Social Research and Social Research Data

25 September

Introduction to Quantitative Analysis

27 September

Ragin, Chapter 1, "What is Social Research?" and Chapter 2, "Goals of Social Research"

30 September (Kiewit Instructional Center)

Zeisel, Say It With Figures, Chapter 2, "Presentation Problems," and Chapter 5, "Tables of More than Two Dimensions" (Class handout)

Recommended: Norusis, Chapter 3, "An Introductory Tour: SPSS for the Macintosh," and Chapter 4, pp. 50-52

Week 2 (2 October - 7 October) Research Design

2 October

Ragin,and Chapter 3, "Processes of Social Research: Ideas and Evidence," and Chapter 4, "Using Qualitative Methods to Study Commonalities"

Sirkin, Chapter 1, "How We Reason"

4 October

Ragin, Chapter 5, "Using Comparative Methods to Study Diversity," and Chapter 6, "Using Quantitative Methods to Study Co-Variation"

Singleton, et al., Approaches to Social Research, Chapter 16, "Research Ethics" (Class handout)

7 October (Kiewit Instructional Center)

Maier, Chapter 8, "Wealth, Income, and Poverty"

Cautley and Slesinger, "Labor Force Participation and Poverty Status among Rural and Urban Women Who Head Families" (Socy 15 Reader)

Week 3 (9 October - 14 October) Measurement

9 October

Sirkin, Chapter 2, "Levels of Measurement and Forms of Data"

11 October

Sirkin, Chapter 3, "Defining Variables"

14 October (Kiewit Instructional Center)

Maier, Chapter 3, "Housing," and Chapter 9, "Labor Statistics"

Recommended: Norusis, Chapter 4, "Counting Responses"

Week 4 (16 October - 21 October) Measures of Central Tendency and Dispersion

16 October

Sirkin, Chapter 4, "Measuring Central Tendency"

18 October

Sirkin, Chapter 5, "Measuring Dispersion"

21 October (Kiewit Instructional Center)

Recommended: Norusis, Chapter 5, "Computing Descriptive Statistics," Chapter 6, "Comparing Groups," and Chapter 7, "Looking at Distributions"

Week 5 (23 October - 28 October) Contingency Tables and Statistical Inference

23 October

Sirkin, Chapter 6, "Constructing and Interpreting Contingency Tables"

Recommended: Norusis, Chapter 8, "Counting Responses for Combinations of Variables"

25 October

Sirkin, Chapter 7, "Statistical Inference and Tests of Significance," pp. 176-180

28 October (Kiewit Instructional Center)

Maier, Chapter 2, "Demography"

Week 6 (30 October - 4 November) Inferential Statistics

30 October

Sirkin, Chapter 7, "Statistical Inference and Tests of Significance," pp. 180-196

1 November (Special Day of Classes--No Class)

4 November (Kiewit Instructional Center)

Recommended: Norusis, Chapter 10, "Evaluating Results of Samples"

Week 7 (6 November - 11 November) Probability Distributions and Differences Between Means

6 November

Sirkin, Chapter 8 "Probability Distributions and One-Sample z and t-Tests"

Recommended: Norusis, Chapter 11, "The Normal Distribution," and Chapter 12, "Testing a Hypothesis about a Single Mean"

8 November

Sirkin, Chapter 9 "Two-Sample t-Tests"

11 November (Kiewit Instructional Center)

Recommended: Norusis, Chapter 13, "Testing a Hypothesis about Two Related Means," and Chapter 14, "Testing a Hypothesis about Two Independent Means"

Week 8 (13 November - 18 November) One-Way and Two-Way ANOVA

13 November

Sirkin, Chapter 10, "One-Way Analysis of Variance"

15 November

Recommended: Norusis, Chapter 15, "One-Way Analysis of Variance"

18 November (Kiewit Instructional Center)

Recommended: Norusis, Chapter 16, "Two-Way Analysis of Variance"

Week 9 (20 November - 25 November) Measures of Association and the Chi-Square Test

20 November

Sirkin, Chapter 11, "Measuring Association in Contingency Tables"

22 November

Sirkin, Chapter 12, "The Chi-Square Test"

25 November (Kiewit Instructional Center)

Recommended: Norusis, Chapter 17, "Comparing Observed and Expected Counts," Chapter 19, "Measuring Association"

Week 10 (27 November - 2 December) Correlation and Regression

27 November (Special Day of Classes--Regular Class Schedule)

Sirkin, Chapter 13, "Correlation-Regression Analysis" and Chapter 14, "Additional Aspects of Correlation-Regression Analysis"

29 November (Thanksgiving Recess-No Classes)

2 December (Kiewit Instructional Center)

Recommended: Norusis, Chapter 9, "Plotting Data" and Chapter 20, "Linear Regression Correlation"

Week 11 (4 December - 9 December) Correlation and Regression (continued)

4 December

Recommended: Norusis, Chapter 21, "Testing Regression Hypotheses" and Chapter 22, "Analyzing Residuals"

6 December (Reading Period--No Classes)

9 December

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