Introduction to Statistics

for the

Social and Behavioral Sciences

 

 

Social and Behavior Science 3000

 

Telecourse

David Kiefer

e-mail: kiefer@economics.utah.edu

course website: webct.utah.edu

 

This course applies probability theory and statistical methods to the social and behavioral sciences. This is a high technology, distance-learning course combining video lessons from the Against All Odds series, plus with 8 discipline-specific videos, and a web site, webct.utah.edu. It is computer oriented, but only a basic computer skill is required. Topics include descriptive statistics, graphical methods of data analysis, basic probability theory, normal and binomial distributions, sampling, confidence intervals, hypothesis testing, regression analysis, correlation and causation.

The prerequisites for this class are Mathematics 1030, finite math, and one introductory course from one of the College’s Departments. The second prerequisite reflects an expectation that all students will have had an introduction to one of these related disciplines, so as to comprehend the application of statistical methods to the understanding of social and behavioral phenomena. This course can be used to fulfill the University's QB (statistical or logical reasoning) or QI (quantitative intensive) requirements.

Statistics is an important tool of the social and behavioral sciences. Unfortunately, students are often intimidated by this subject, and often postpone statistics courses as long as possible. This is unfortunate since statistics is a method that can greatly enhance understanding. Instead of dread, I hope this class will show both the beauty and value of statistical methods.

The course begins with an introduction of how quantitative information can be presented so that it is easily understood. This topic is called descriptive statistics. This should help you in comprehending the quantitative information that you encounter on a daily basis. It should increase your skills in communication and understanding data.

Uncertainty is all around us. We do not yet know who will win next October’s World Series. You do not know whether you will have a traffic accident on your way home tonight? The theory of probability is a rigorous way to think about uncertain events.

When reading about the latest scientific findings about, for example, the connection between the 0.08 DUI limit and traffic deaths, do you ever wonder if you should believe the researcher’s conclusion? Sometimes you probably have doubts, but rarely can you explain exactly the reason for these doubts. This course will explain the principles involved in judging the quality of such research. This topic is called inferential statistics.

The required textbooks are Introduction to the Practice of Statistics, David Moore and George McCabe, and Telecourse Study Guide, David Moore.

This course is a fully integrated distance-learning package available to university undergraduates. The videos are broadcast on KULC Channel 9. A problem faced by all distance-learning courses is student passivity and a lack of student-teacher interaction, especially for statistics that requires "hands-on" learning. This tendency will be combated with on campus discussion sessions for a more direct student-teacher interaction. Although these are optional in our distance-learning format, they are strongly recommended.

The first discussion session makes use of the University’s computer network and spreadsheets, especially Microsoft Excel. Assignments will be given and demonstrated on computer spreadsheets. Since spreadsheets are pervasive in the business world, this experience may increase your job opportunities.

The homework assignments are crucial. If you seriously attempt the assignments, your chance of doing well on the exams is much improved. You may either turn in your homework on paper at one of the five University locations (central campus, Bountiful, Cedar Park, Park City or Sandy), or you may submit it over the Internet. Internet submissions will be returned faster than paper submissions. Solutions will be discussed in the discussion sessions, and posted on the web.

The midterm and final examinations will be available at same five locations. Both the midterm and the final are closed book; sample exams are available on the web.

The grading scheme is:

·        Assignments (dropping lowest grade), 30%

·        Midterm examinations. 40%

·        Final examination, 30%

Final grades will be computed by three methods; your grade will be the highest of the three:

·        The curve: with an overall average grade of 2.7.

·        The traditional standard: according to
100%>A>93%>A->90%>B+>87%>B>83%>B-80% and so on to 60%>E.

·        The ace the final rule: you get an "A" for the course if you score an "A" on the final exam regardless of your point total.

As a general rule I do not give incomplete grades. Late assignments lose points; copies and exact duplicates are unacceptable. Exams must be taken at the scheduled time.