course introduces students to the logic and tools social scientists use to measure social phenomena in order to shed light on important research questions.

INSTRUCTIONS TO CANDIDATES

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Course Description:

This course introduces students to the logic and tools social scientists use to measure social phenomena in order to shed light on important research questions. Students will learn how to define and describe variables, develop and test the relationship between variables, and infer about the population using limited sample information. Students engage with the material on both conceptual and mechanical levels. Labs are an integral part of the course. Students will learn the basics of analyzing large data sets, like the General Social Survey, with a widely used software package, SPSS. The course draws from a variety of sociological examples – from crime to inequality to political participation to family and demography – across a variety of Canadian, American and international contexts. This class is intended to provide students with the skills needed to become an informed consumer of scientific research reported in the popular media as well as in scholarly articles and books. SOC 222 also prepares students for SOC 350 which provides a more advanced introduction to regression analysis.

Online Course Statement:

This is an online, hybrid synchronous-asynchronous course. Lectures and tutorials will be given as online narrated slides asynchronously (i.e., can be viewed at any time). Students will also have the opportunity for a one-hour synchronous online webinar class (Wednesday’s 11-12pm) in order to ask questions and discuss that week’s topics in an interactive environment as well as one-hour synchronous office hour (Wednesday’s 12-1pm) for further clarifications about lecture. Practical sections involving SPSS will use SnagIt videos downloadable from Quercus. Students absolutely require PowerPoint, Blackboard Collaborate (via Quercus) and Citrix receiver to use SPSS software remotely.

It is your responsibility to ensure that the prerequisites for this course have been met. Students without the prerequisites can be removed at any time. No waivers will be granted.

Practical Sessions (Labs):

**** You MUST register for one of the practical sections ****

In addition to weekly lectures, an important component of the course is the weekly practical sections held by the TA’s. These sections are meant to provide a brief systematic review of the week’s material. ***practical sections offered online.***

Note that four times during the term (see course schedule in the syllabus), practical sections will serve as computer labs where students will use SPSS to practice for the brief lab assignments. TA’s will go through examples of SPSS commands and output during lab time. This will help prepare students for the lab assignment (homework) which must be completed on students’ own time. Students should review the assigned chapters in the Wagner book prior to the lab. Lab preps will use a guided lecture (SnagIt) conducted by your TA that can be downloaded from Quercus****

**** You must download Citrix Receiver in order to use SPSS software remotely ****

Please visit the Information and Instructional Technology website: https://www.utm.utoronto.ca/iits/services/computer-software

All technical questions about Quercus and Citrix should be directed to the help desk: helpdesk.utm@utoronto.ca or 905-828-5344

The University of Toronto recommends for those who believe they have issues with internet connectivity to follow this link https://www.utoronto.ca/covid19-contact The student will get a response that directs them to a website with instructions on how to access VPN. Do this before test day please.

Learning Goals and Objectives:

Measurement:

• Understand the different ways in which concepts are transformed into variables as well as how operational definitions are generated, and how variables are measured.

• Write hypotheses with clear mention of dependent and independent variables and the proposed direction of their relationship.

Descriptive and Inferential Statistics

• Use and interpret descriptive statistics designed to summarize data, such as frequency distributions, graphs, and measures of central tendency and dispersion.

• Understand the concept of the normal distribution and the ways in which assumptions about normality allows us to use various methods, including standardized scores.

• Interpret p-values and understand the meaning of statistical significance.

• Understand the logic underlying basic inferential statistics, such as the estimation of population values from sample information through the use of confidence intervals and hypothesis testing.

Relationships between Categorical Variables, Bivariate/Multiple Regression

• Examine the relationship between variables through the use of cross-tabulations and scatter-plots.

• Examine the relationship between categorical variables using Gamma and Lambda, as well as Chi-Square.

• Understand the basic assumptions of bivariate OLS regression and the best fitting line.

• Understand the concept and practice of statistical controls and the methods involved in multivariate OLS regression.

• Develop the ability to interpret regression coefficients and the coefficient of determination (r2).

Research/Labs

• Interpret findings in research articles and understand the methodology used in relation to the conclusions made in those scholarly articles.

• Use SPSS to analyze data and apply concepts and techniques learned in class. We will be using the 2002 General Social Survey (GSS) Data in the lab tutorials and for the lab assignments.

Course Materials:

Frankfort-Nachmias, Chava, and Anna Leon-Guerrero. Social

Statistics for a Diverse Society. Thousand Oaks, CA: Pine Forge Press, latest edition.

Wagner, William E. Using SPSS for Social Statistics and Research Methods. Thousand Oaks, CA: Pine Forge Press, latest edition.

(Note that the bookstore usually sells the two texts as a bundled package)

GSS data (2002) is available on the lab computers in SPSS format.

Attachments:

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