Course Objectives:
The purpose of this course is to teach students the
principles of research design, data collection, data analysis, and data
presentation employed in empirical social science research. By the end of
this course you will become skilled in the collection, presentation, analysis
and interpretation of numerical data relevant to a great many social
issues. In general, the course stresses research design and research
skills more than statistical calculation. Although much of the course is
devoted to quantitative statistical methods used by political scientists in
their research, these are research skills which you should find valuable in a
variety of academic and non-academic settings. Among the things student
will learn to do in this course are:
- collect and analyze social and political statistical
data available from reference and internet sources.
- assess the reliability and validity of social indicator
data and quantitative social science research.
- understand descriptive statistics: mean, mode, median,
standard deviation, percentages, and sampling error, levels of measurement and
units of analysis.
- how to present numerical data effectively using charts,
tables and graphs.
- interpret, use, and evaluate social science surveys.
- use spreadsheet software to analyze data.
- prepare a literature review on a social science
research question.
- write a research report based on statistical data.
- understand the general principles of research design:
assessing causation, spurious relationships, bivariate analysis.
Approach to this course:
More so than other social science statistics
or methodology courses, this course will stress a variety of practical
statistical and computer skills that you will find of use both in your other
coursework and future career. Most of the laboratory assignments and the
initial two-thirds of the course will teach you how to find, analyze and present
numerical information in an efficient and informative manner.
A major component of the course will be the
Data Profile Assignment,
comprising 40% of the final grade. In addition, 10% of the
assignment grade will be based on a grade given to the draft of the assignment
at the end of the fifth and tenth week of the semester. You must maintain
a link to the draft of the assignment on your course web page (as will be done
with the homework and laboratory assignments.)
There will be two examinations, a mid term and final, each
counting 20% of the grade.
The remaining 20% percent of your grade will be based on
the completion of a series in-and out of-class
homework assignments, class attendance and class participation. The
participation will include some formal in-class presentations. Most of these
assignments will be stored as Word or Excel spreadsheet files on your ISU
website drive and your home page will include links to each of the files.
They will be graded at least three times (probably more, and not at any
announced time) during the semester, the last time at the beginning of exam
week.
Each student will be responsible for maintaining a home
page with active links to each of the assignments at all times.
Your grades
are posted on the
web. Login
with your university ULID and the password.
Book for Purchase:
Gary Klass,
Just Plain Data Analysis: Finding, Presenting, and Interpreting Social
Science Data (New York: Rowman and Littlefield Publishers, 2008)
ISBN: 978-0-7425-6053-6
Amazon.com
Note: Although this book was written for this course, because there is a
potential conflict of interest in a professor assigning his or her own book
in a class, any proceeds to the author from the sale of this book (less than
$2 per book) in this class will be donated to the ISU\IWU Habitat for
Humanity Collegiate Home.
Plagiarism, Attendance and Expectations.
You are expected to show up for all classes. You are responsible for any material and assignments for classes
that you miss. Each absence after the first week of class reduces your
overall grade by 1 point, but these can be made up by doing an extra
assignment within one week after returning to class. If you miss five
classes before the week eight withdrawal date, you will be expected to withdraw
from the course.
All students in the course are expected to know what
plagiarism is, why it is wrong and how to avoid doing it. All the written work submitted for the course
must reflect each student’s own original efforts, any portion of the written
assignments, including portions that may have been prepared by other members of
the class, that is not a student’s own original effort must clearly acknowledge
the source. All instances of plagiarism will be severely penalized and reported
to the Student Judicial Office.
