Quantitative Research Methods for Information Systems and Management (Info 271B) Course Introduction: Preface to Social Research and Quantitative Methods

 Coye Cheshire  Office 305A  Office Hours Thurs 3:45-5:45pm  Graduate Instruction Assistant  Andrew Fiore  Office hours: Wednesday 2-3:30 pm, Room 2 (for now)  Course Website:

 Part lecture, part skills development  Usually one major topic per week  Some time devoted to working with statistical software packages (labs)  Three major course sections  Research Methodology (weeks 1-4)  Probability and Statistics (weeks 5-10)  Bivariate and Multivariate Analyses (weeks 11-15)

 Primary Text:  Statistics (4 th Edition) Freedman, Pisani and Purves

 Course Reader  (Copy Central, Bancroft)

 All course examples will use STATA  You can purchase a STATA 10 license ($95) through the grad plan:

Bring your laptop to class if applicable. We will devote class time in many sessions to working with statistical software. If you choose not to bring a laptop to class, we encourage you to sit with anyone who has a statistical software package when we begin to use it in class.

 Four “lab assigments” (40%)  Always started in class, due following week  Some are individual assignments, others are group assignments.  Final Exam (50%)  Will cover major topics in class  Will allow you to use the dataset of your choice.  Challenging, but will be a take-home exam allowing plenty of time to complete.  Participation and Instructor Discretion (10%)

 You will have good knowledge of common research methods used in quantitative research (surveys, experiments)  You will be able to prepare, recode and error-check numeric data  You will be able to use a general purpose statistical package to conduct statistical analyses  You will understand basic univariate statistics, bivariate statistics and linear regression

Part I: Research Methods  Defining and justifying research problems for quantitative studies  Theory and Measurement  Sampling, Survey Data Collection, Questionnaires  Experimental design  Choosing methods to match research problems

Part II: Probability and Statistics  Probability and Sampling  Working with structured data (recoding, error checking)  Univariate statistics  Probability and normal distributions

Part III: Bivariate and Multivariate Analyses  Bivariate Statistics (correlation, t-test)  Chi-Square (analyzing nominal data)  Linear Regression (bivariate and multivariate)

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And, what do you want to get out of this course?

 Reader:  Bernard Chapter 2  We will begin with an intro to foundational concepts in social research methods, common terms.  Come prepared to discuss!