POL 52a Basic Statistics for Social and Political Analysis Fall Dr. Hande Inanc ( Office no: Golding 118)

Size: px

Start display at page:

Download "POL 52a Basic Statistics for Social and Political Analysis Fall Dr. Hande Inanc ( Office no: Golding 118)"

Blanche Norton
5 years ago
Views:

1 POL 52a Basic Statistics for Social and Political Analysis Fall 2016 Dr. Hande Inanc ( Office no: Golding 118) Time: 10:00-10:50, Monday, Wednesday and Thursday Room: Farber 101A Office hours: 14:00-15:30, Wednesdays Course description and learning goals: This course seeks to familiarize students with the fundamentals of social science data analysis. This consists of analyzing numerical data via descriptive and inferential statistics in order to better understanding social and political phenomena. The course is composed of three parts: Part I gives an overview of fundamental ideas in statistics such as types of variables (e.g. continuous, ordinal) and data (e.g. cross-sectional, longitudinal), and principles of sampling and population. In Part II students gain knowledge on describing statistics and learn about measures of tendency, distribution, dispersion and deviation. Inferential statistics are covered in Part III, with a focus on correlation and regression, and estimation, confidence intervals, and significance tests. Handson lab sessions help students learn how to carry out basic data preparation and analysis, as well as interpret outputs. Course requirements and Evaluation: No prior knowledge of statistics or advanced mathematics is required. Note that this is Four- Credit Course with three hours of class-time per week. This means that success is based on the expectation that students will spend a minimum of 9 hours of study time per week in preparation for class (readings, papers, exam preparation, etc.). Final grades will be determined by performance on the following: Class participation: 10% Take-home assignments (4 assignments): 20% Mid-term exam: 20% Final Project: 25% Final Exam: 25% * If you are a student with a documented disability on record at Brandeis University and wish to have a reasonable accommodation made for you in this class, please see me immediately. The following text will be available for purchase at the student bookstore, or can be rented or purchased online. It is required for all students. Agresti, Alan and Barbara Finley, (2013) Statistical Methods for the Social Sciences, 4 th Edition, Prentice-Hall. All other readings listed on the syllabus will be posted on LATTE. 1

2 Academic integrity: You are expected to be honest in all of your academic work. Please consult Brandeis University Rights and Responsibilities for all policies and procedures related to academic integrity. Students may be required to submit work to TurnItIn.com software to verify originality. Allegations of alleged academic dishonesty will be forwarded to the Director of Academic Integrity. Sanctions for academic dishonesty can include failing grades and/or suspension from the university. Citation and research assistance can be found at LTS - Library guides. Communication: I will communicate any changes in the syllabus, and snow days updates via a course mailing list. Please check LATTE and your Brandeis regularly. Use of technology in the classroom: None except for Stata in lab sessions. Participation grades will be docked if phones, computers, or tablets are used during class. *If there are exceptional circumstances that require you to use a computer, come talk to me and we can see about the possibility of an exception. Class Schedule Please note that all readings should be completed by the Monday of their respective week. Additional more topical readings will be added as we move on. Week 1 Introduction Thursday, August 25 th. Course Overview Part 1: Understanding Quantitative Methodology Week 2 Quantifying information data and variables Monday, August 29 th. Why do we quantify information in sciences and in life? Wednesday, August 31 st. Data, dataset and databases: Storing quantified information Thursday, September 1 st. Variables: Properties and types Utts, J. (2005). The benefits and risks of using statistics (Chapter 1) and Reading the News (Chapter 2) in Seeing through Statistics. 3 rd Edition. Thompson-Brooks/Cole. 2

3 Week 3 Populations and Samples Monday, September 5 th. No class Wednesday, September 7 th. Populations and samples Thursday, September 8 th. Sampling Agresti and Finlay (2013). Chapter 2. Sampling and measurement. Gorard, S. (2003). Sampling: The basis of all research (Chapter 4) in Quantitative Methods in Social Science Research. (Available via LATTE) Week 4 Survey Methodology Monday, September 12 th. The quality and accuracy of measures Wednesday, September 14 th. Questionnaire design Thursday, September 15 th. Mode effects in survey context OECD (2013). Methodological considerations in the measurement of Subjective Wellbeing (Chapter 2), in OECD Guidelines on Measuring Subjective Well-Being. (Available via LATTE) Part 2: Descriptive Statistics Week 5 Measuring the center of the data 1 st assignment due on Monday, September 19 th Monday, September 19 th. Measures of central tendency: Mode, median, mean and quantiles Wednesday, September 21 st. Measures of central tendency: Graphing the center of the data Thursday, September 22 nd. Lab Session Getting to know Stata Agresti and Finlay (2013). Chapter 3. Descriptive Statistics (parts 3.1 and 3.2) Kellstedt and Whitten (2009). Using Stata with The Fundamentals of Political Science Research (Available via LATTE) Week 6 Measuring the variability of the data Monday, September 26 th. Measures of dispersion: Range, variance and standard deviation Wednesday, September 28 th. Describing bivariate statistics Thursday, September 29 th. Lab Session Using STATA to describe the data Agresti and Finlay (2013). Chapter 3. Descriptive Statistics (parts 3.3, 3.4 and 3.5) 3

4 Week 7 General overview and mid-term exam 2 nd assignment due on Monday 3 rd Monday, October 3 rd. No class. Wednesday, October 5 th. Overview session Thursday, October 6 th. Mid-term exam Part 3: Inferential Statistics Week 8 Normal probability distribution and sampling distribution Monday, October 10 th. Normal probability distribution. Wednesday, October 11 th. No class. Thursday, October 13 th. Using z values and z scores Agresti and Finlay (2013). Chapter 4. Probability distribution. Week 9 Point estimation and interval estimation Monday, October 18 th. No class. Wednesday, October 19 th. Standard error Thursday, October 20 th. Confidence intervals Agresti and Finlay (2013). Chapter 5. Statistical Inference: Estimation. Week 10 Hypothesis testing Tuesday, October 25 th (Brandeis Monday). Hypothesis testing and statistical significance Wednesday, October 26 th. Hypothesis testing with continuous variables (testing the mean) Thursday, October 27 th. Hypothesis testing with proportions Agresti and Finlay (2013). Chapter 6. Statistical inference: Significance test. Agresti and Finlay (2013). Chapter 7. Comparison of two groups. Week 11 Association between categorical variables 3 rd assignment due October 31 st Monday, October 31 st. Contingency tables Wednesday, November 2 nd. Chi Square Thursday, November 3 rd. Lab Session How to make contingency tables with STATA 4

5 Agresti and Finlay (2013). Chapter 8. Analyzing association between categorical variables. Week 12 Linear regression I Monday, November 7 th. Linear regression model Wednesday, November 9 th. Correlation and linear association Thursday, November 10 th. Lab Session - Running bivariate regression with STATA. Agresti and Finlay (2013). Chapter 9. Linear regression and correlation. Week 13 Linear regression II Monday, November 14 th. Multivariate linear regression Wednesday, November 16 th. Association and Causation Thursday, November 17 th. Lab Session - Running multiple regression with STATA. Agresti and Finlay (2013). Chapter 11. Multiple regression and correlation Agresti and Finlay (2013). Chapter 14. Model building with multiple regression Week 14 Logistic regression Monday, November 21 st. Modelling categorical responses using regression. Wednesday, November 23 rd. No class. Thursday, November 24 th. No class. Agresti and Finlay (2013). Chapter 15. Logistic regression: Modelling categorical responses. Week 15 General overview 4 th assignment due November 28 th Monday, November 28 th. Descriptive statistics Wednesday, November 30 th. Inferential statistics Thursday, December 1 st. Lab Session STATA overview Week 16 Wrap-up Final project due December 9 th Monday, December 5 th. Review of selected topics* Wednesday, December 7 th. Review of selected topics* *Students should me the topic they would like us to review no later than by Friday, December 2 nd. 5

Sociology 521: Social Statistics and Quantitative Methods I Spring Wed. 2 5, Kap 305 Computer Lab. Course Website

Sociology 521: Social Statistics and Quantitative Methods I Spring 2012 Wed. 2 5, Kap 305 Computer Lab Instructor: Tim Biblarz Office hours (Kap 352): W, 5 6pm, F, 10 11, and by appointment (213) 740 3547;