Summer 2019  |  SOC 3811 Section 001: Social Statistics (82864)

Class Component:
Instructor Consent:
No Special Consent Required
Instruction Mode:
In Person Term Based
Class Attributes:
UMNTC Liberal Education Requirement
Times and Locations:
Summer Session 10 wk
06/10/2019 - 08/16/2019
Tue, Thu 03:30PM - 05:20PM
UMTC, West Bank
Blegen Hall 440
Enrollment Status:
Open (25 of 30 seats filled)
Also Offered:
Course Catalog Description:
This course will introduce majors and non-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 and software needed to analyze quantitative data provided in the class. prereq: Credit will not be granted if credit has been received for Soc 5811 (Soc 5811 offered Fall terms only). Undergraduates with strong math background are encouraged to register for 5811 in lieu of 3811. Soc Majors/Minors must register A-F.
Class Notes:
Click this link for more detailed course information:
Class Description:

Quantitative literacy skills refer to a set of competencies needed to accurately work with data expressed numerically. While pure mathematics includes resolving the truth or falsity of abstract numerical relationships, quantitative literacy entails working with quantitative information in various contexts. In 3811, students will develop their quantitative literacy by learning how to (1) accurately describe, interpret, and analyze numerical data from social research, (2) apply numerical data to assess and develop research hypotheses, and (3) communicate statistical information by using plain language and effective visual figures. This course also fulfills UMN's Mathematical Thinking Core.

Who Should Take This Class?:
Any student looking to dive deeper into what it takes to work with numerical data from social science research. SOC 3811 does not require prior knowledge of statistics, research methods, or any of the software used in Lab. However, this class is recommended for students with a strong interest in developing a systematic understanding of the world and a willingness to work hard during the Summer semester.
Learning Objectives:
* Organize numerical data in frequency tables and percentage distributions.
* Assess numerical data through its measures of central tendency (median, median, and mode) and measures of dispersion (such as range, mean deviation, and standard deviation).
* Inferring properties of a population using numerical data from an observed sample of that population (statistical inference)
* Understand and apply statistical techniques (multivariate analysis) for examining the relationship between two different attributes of a sample (what statisticians call ‘variables').
* Formulate a statistical hypothesis based on numerical data.
* Assess the quality of a numerical analysis (connection between research hypothesis and the numerical data) and its delivery (organization and presentation).
* Apply basic skills in Excel and Statistical Software (Stata or R).

20% Weekly In-Class Quizzes
20% Weekly Lab Exercises
20% Two Project Memos
10% Midterm 1
10% Midterm 2
20% Attendance and participation

No final exam
Exam Format:
Evaluations include: a) calculation problems, b) multiple choice questions, c) short answer responses where students will draw conclusions from statistical analyses and explain results.
Class Format:
Class time will include lecture, discussion, and exercises to practice the material. Weekly lab attendance is required and will offer time to practice and work on major assignments using university software.
SOC 3811 requires concurrent enrollment in a lab section and is a 4-credit course. Under UMN policy, the student workload per undergraduate credit is expected to be three hours per credit per week. Therefore, you should expect a workload of at least 12 hours per week (including lecture and labs). Each week there will be two 110-minute lectures and a 105-minute lab. Therefore, you should expect approximately 7 hours per week of work outside of scheduled class.
Instructor Supplied Information Last Updated:
7 March 2019

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