Fall 2014  |  SOC 3811 Section 001: Basic Social Statistics (10720)

Instructor(s)
Class Component:
Lecture
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person Term Based
Class Attributes:
UMNTC Liberal Education Requirement
Delivery Medium
Times and Locations:
Regular Academic Session
 
09/02/2014 - 12/10/2014
Tue, Thu 09:45AM - 11:00AM
UMTC, West Bank
Anderson Hall 310
Also Offered:
Course Catalog Description:
Descriptive statistics. Measures of central tendency, deviation, association. Inferential statistics focusing on probability/hypothesis testing. T-tests, Chi-square tests, variance analysis, bivariate regression. Statistical software used to analyze sociological data.
Class Notes:
(Declared sociology majors have priority registration for reserved seats through 4/21/2014).
Class Description:
This course will introduce sociology majors to basic statistical measures and procedures that are used to describe and analyze quantitative data in sociological research. The topics include (1) frequency and percentage distributions, (2) central tendency and dispersion, (3) probability theory and statistical inference, (4) models of bivariate analysis, and (5) basics of multivariate analysis. Lectures on these topics will be given in class, and lab exercises are designed to help students learn statistical skills needed to analyze quantitative data provided in the class. In addition to attendance to lectures and labs, students are expected to read 15 pages of the text per week. There will be three exams. Students will need a simple calculator for assignments and exams. This course meets the CLE requirements for the Mathematical Thinking core. We explore the dual nature of social statistics as a body of knowledge with its own logic and way of thinking, and as a powerful tool for understanding and describing social reality. Students in this course are exposed to the mathematic knowledge that underlies key concepts, but they are also shown how each concept applies to real world social science issues and debates. They are asked to demonstrate their mastery of the mathematical concept and its practical application through in-class discussions, problem sets, and exam questions. Students are taught the mathematical foundations of probability and sampling theory; they are taught about sampling distributions; and they are shown the real-world implications of these ideas for how social science knowledge is gained through surveys of randomly sampled observations.
Grading:
70% Midterm Exam
30% Problem Solving
Exam Format:
multiple choice, computational problems
Class Format:
65% Lecture
35% Laboratory
Workload:
15-20 Pages Reading Per Week
3 Exam(s)
Textbooks:
https://bookstores.umn.edu/course-lookup/10720/1149
Past Syllabi:
http://classinfo.umn.edu/syllabi/bianx001_SOC3811_Spring2024.pdf (Spring 2024)
http://classinfo.umn.edu/syllabi/bianx001_SOC3811_Spring2020.pdf (Spring 2020)
http://classinfo.umn.edu/syllabi/bianx001_SOC3811_Spring2019.pdf (Spring 2019)
Instructor Supplied Information Last Updated:
3 April 2014

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