Social Statistics I

SOCI 3030 3.00

Statistical thinking will one day be as necessary for efficient citizenship as the ability to read and write.

Samuel Wilks (England, 1951)

This course introduces students to basic concepts of descriptive and inferential statistics in social sciences. It covers topics including data and variables, summary statistics, distributions, measures of association, research designs, visualization, hypothesis testing, and simple regressions.

One essential aspect of this course is to learn how to use a statistical package (e.g., SPSS, STATA, Python) to analyze data. For the purpose of this course, we will use R (www.r-project.org/), an open free and popular programming language for statistical computing and graphics. We will have lab sessions in class to demonstrate how we use R for simple data analysis. Students have opportunities to practice their R skills to finish their required research project for this course.


Basic data analysis is one of the most valuable skills you can learn, and you don’t have to be very good at math. It is my hope at the end of this course you will learn how to:

  • summarize data by using graphs, tables, measures of central tendency and variability
  • assess the strength of association between variables
  • perform basic statistical inference using appropriate techniques
  • interpret and write up your data analysis and findings
  • achieve basic competence in using the R programming language


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