on Quantitative Applications in the Social Sciences by 3SpvANc

VIEWS: 3 PAGES: 4

									                                       UNIVERSITY OF TORONTO
                                        Department of Sociology

Statistics for Sociologists                                                        Ann Marie Sorenson
Tutorials:                                                                725 Spadina room 246
Lectures:                                                                 (416) 978 - 4266
TA:                                                                       office hours TBA
lab/office hours:

Course Description: This course is designed to provide a transition to graduate level statistics courses.
There are three required exercises that will guide you through each step of organizing a problem and working
through a strategy for analyzing the data. Each exercise begins with a research question and ends with the
presentation and interpretation of your analysis of the relevant data and a brief conclusion.

All three exercises draw on data collected annually by the International Social Survey Project (ISSP) in over 20
nations. All students will analyze data for Canada in Part 1 of each exercise. You will each analyze data for
one additional nation (Your Nation) in Part 2.

The first exercise focuses on the analysis of categorical data, starting out with two-way tables and moving to
the selection and interpretation of a preferred model from among a number of nested loglinear models. In the
second exercise we consider approaches that are more appropriate to the analysis of continuous outcome
measures, starting with correlations and bivariate regression and again moving to the selection and
nterpretation of a preferred model from among a number of nested multivariate models. In the third exercise
we consider non-linear and logistic regression, building on topics covered in Exercise 1 and Exercise 2.

Textbooks:

Exercise 1:

Aneshensel, Carol S. 2002. Theory - Based Data Analysis for the Social Sciences. Pine Forge
       Press.
Knoke, D. and P. J. Burke. 1980. Loglinear Models. Sage University Series on Quantitative
       Applications in the Social Sciences, 07-20.

Optional:        Rudas, T. 1998. Odds Ratios in the Analysis of Contingency Tables. Sage University Series
                        on Quantitative Applications in the Social Sciences, 01-119

Exercise 2:

Schroeder, L.D., Sjoquist, D.L. and P.E. Stephan. 1986. Sage University Papers Series on
       Quantitative Applications in the Social Sciences, 07-57.
Jaccard, J. and R. Turrisi. 2003. Interaction Effects in Multiple Regression (2nd. ed.) Sage
       University Series on Quantitative Applications in the Social Sciences, 07-72.

Exercise 3:

Pampel, F.C. Logistic Regression. 2000. Sage University Papers Series on Quantitative
      Applications in the Social Sciences, 07-132.

Optional:        Menard, S. 2002. Applied Logistic Regression Analysis (2nd ed.). Sage University
                        Series on Quantitative Applications in the Social Sciences, 07-106.
                 O'Connell, Ann A. 2006. Logistic Regression Models for Ordinal Response Variables.
                        Sage University Papers on Quantitative Applications in the Social Sciences, 07-146.

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OFFICE HOURS: I am in my office during scheduled office hours. If you ‘d like to come by at any
other time, please just call to be sure that I am available. Please don’t hesitate in this.

Email me anytime: sorenson@chass.utoronto.ca

MARKING: Exercises are late if they are received at any time after 12:10 on the day that they are due. The
penalty for a late exercise is the loss of 5% per weekday.

                                                     COURSE OUTLINE

----------------------------------------------------------- Week 1      -------------------------------------------------------------
Preparation for Ex. 1           Aneshensel Ch. 1 - 7
                                Knoke & Burke Ch 1 – 3 , 5

Lecture:              Sept. xx             Unit 1 / Lecture 1:

                     - Testing the Null Hypothesis in 2-way Tables
                     -What would our data look like if the Null Hypothesis were true?
                              Observed and Expected Frequencies
                     - Fit Statistics (Chi-sq and L-sq) and Degrees of Freedom
                     - Selecting a Preferred Model
                     - Describing the data: odds ratios and logged odds ratios
                     - Figures and the language of presentation

----------------------------------------------------------- Week 2 -------------------------------------------------------------
Tutorial:             Sept. xx             Exercise 1/ tutorial 1
                      - SAS basics, accessing the data

Lecture:              Sept. xx             Unit 1 / Lecture 2:

                     - Building 3-way Tables
                     - Patterns of Association
                     - Observing and Interpreting Patterns of Association in 3-way Tables

-----------------------------------------------------------   Week 3    -------------------------------------------------------------

Tutorial:            Sept. xx          Exercise 1, tutorial 2
                     - getting started on Ex. 1

Lecture:              Sept. xx              Unit 1 / Lecture 3:

                     - The Basics: Log-linear Models for 2-way Tables
                     - Expected Frequencies and Effect Parameters

-----------------------------------------------------------   Week 4    -------------------------------------------------------------

Tutorial:            Oct. x                 Exercise 1, Tutorial 3

Lecture:             Oct. x                Unit 1 / Lecture 4:

                     - Observed and Expected Frequencies
                     - Choosing a Preferred Model from among Nested Models
                     - Interpreting the Results


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-----------------------------------------------------------   Week 5   -------------------------------------------------------------

Tutorial:            Oct. x                cancelled – Thanksgiving Holiday

Preparation for Exercise 2:                Schroeder, Sjoquist and Stephan Ch. 1 – 4
                                           Jaccard & Turrisi Ch. 1 – 2

Lecture:              Oct. xx                        Unit 2 / Lecture 1:

                     - Theoretical Probability Distributions: the normal distribution and distributions of student’s t
                     - Making Inferences about Populations from Samples
                     - The Central Limit Theorem
                     - Tests for Two Means (Z scores and t scores)
                     - Sample Point Estimates

-----------------------------------------------------------   Week 6   -------------------------------------------------------------

Tutorial:            Oct. xx

Lecture:              Oct xx               Unit 2 / Lecture 2:

                     - Estimating a Linear Regression Equation
                     - Regression Parameters and Significance Tests
                     - Sample Point Estimates and Confidence Intervals
                     - Correlation and Regression

                                           EXERCISE 1 DUE (30 PTS.)
-----------------------------------------------------------   Week 7   -------------------------------------------------------------

Tutorial:            Oct. xx               Exercise 2, tutorial 2

Lecture:              Oct. xx              Unit 2 / Lecture 3:

                     - Dummy Variable Regression
                     - Equations with Interaction Terms

-----------------------------------------------------------   Week 8   -------------------------------------------------------------

Tutorial:            Oct. xx               Exercise 2, tutorial 3

Lecture:              Nov. x               Unit 2 / Lecture 4:

                     - Standardized Regression Coefficients
                     - Choosing a Preferred Model from among Nested Models
                     - Interpreting the Results

-----------------------------------------------------------   Week 9   -------------------------------------------------------------

Tutorial:            Nov. x                Exercise 2, tutorial 4

Lecture:              Nov. x               Unit 3 / Lecture 1:

                     - Comparing Linear and Non-linear Relationships
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-----------------------------------------------------------   Week 10      -------------------------------------------------------------

Tutorial:            Nov. xx               Exercise 3, tutorial 1

Lecture:             Nov. xx               Unit 3 / Lecture 2:

                     - Estimating Logistic Equations
                     - Parameter Estimates and Significance Tests
                     - Selecting a Preferred Model from Among Nested Models
                     - Interpreting the Results

                                           EXERCISE 2 DUE (30 PTS.)
-----------------------------------------------------------   Week 11      -------------------------------------------------------------

Tutorial:            Nov. xx               Exercise 3, tutorial 2

Lecture:             Nov. xx               Unit 3 / Lecture 3: More on Logistic Regression


-----------------------------------------------------------   Week 12      -------------------------------------------------------------

Tutorial:            Nov. xx               Exercise 3, tutorial 4

Lecture:             Nov. xx               Unit 3 / Lecture 4 Even More on Logistic Regression (as needed)

-----------------------------------------------------------   Week 13 -------------------------------------------------------------

Tutorial:            Dec. x

                     Dec. x                EXERCISE 3 DUE (40 PTS.)




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