PLSC 678 – ANALYTICAL METHODS FOR PUBLIC ADMINISTRATORS
WINTER 2015
Dr. Dave Ivers
734-667-2814 (home)
Office Hours: TBA
912 Hoyt
487-2239 (office)
jivers@emich.edu
COURSE DESCRIPTION
The goal of this course is to introduce students to the applications and methods of quantitative analysis as
used in public administration (or as they may be used in the future) as tools useful in resolving administrative
problems. Students will be expected to develop specific quantitative skills in order to facilitate their roles as
administrators, communicators, analysts, and consumers of quantitative research and information. Specific skills
required will include the use of spreadsheets, the fundamentals of data gathering, and the use of methods from
descriptives through multiple regression. The major emphasis thoughout the course will be the application of
statistical methods to practical administrative problems and situations in the public and non-profit sectors. The
course will have a laboratory/lecture/discussion format. Student discussion, participation and interaction are
expected.
Since this tends to be a very work intensive course, I suggest that all students expect to spend at least several hours
per week mastering both SPSS and the statistical usages for the first several weeks. When we get to the heavier
application of statistics you should find it takes less time if you have prepared by working hard early.
TEXTBOOKS
Required and available at campus bookstores and online are:
Nishishiba, Jones, and Kraner: Research Methods and Statistics for Public and Nonprofit Administrators. Los
Angeles, Sage Publications, Inc. ISBN: 978-1-4522-0352-2
Recommended:
Kranzler, G and J. Morsund (1999). Statistics for the Terrified (2nd ed.). Upper Saddle River, NJ, Prentice Hall.
The student version of SPSS 10.0 or above and SPSS Base 10.0 Brief Guide in SPSS Student Version for Windows
(2000). Chicago, SPSS, Inc.
Also, khanacademy.org has some excellent videos of 15 minutes or so on many of the early parts of stats. You
might find something useful there. You can also find a lot of useful direction by googling the part of SPSS you want
to use.
GRADING
Grades will be based on several (depending on how far we get) exercises presented to the students, a midterm exam and a final. The mid-term and final will each be worth 30% of your course grade with the remaining
40% divided equally between the exercises. (Thus, more exercises mean it’s easier to blow one and still get a good
grade.) The instructor reserves the right to raise by 1/3 of a letter grade the course grade of students who
demonstrate exceptional participation. This means making cogent comments, asking thoughtful questions, or
generally enhancing the learning experience of the class. It does not mean endless chattering.
EXPECTED LEARNING OUTCOMES
Students will learn to solve real-life problems using a mathematical modeling process. They will learn to:
1) Build an appropriate model.
a) Estimate an answer to the problem
b) Identify important components of the model
c) Collect or generate appropriate data
d) Analyze the situation using arithmetic, geometric, algebraic, and probabilistic or statistical methods.
2) Use the model to solve the problem.
a) Propose a solution
b) Evaluate the reasonableness of the solution.
3) Communicate the results of their analysis.
a) Share the findings in oral or written reports using appropriate mathematical language.
b) Write summaries to explain how they reached their conclusions.
c) Communicate quantitative relationships using symbols, equations, graphs, and tables.
4) Evaluate the model.
a) Draw other inferences from the model.
b) Identify the assumptions of the model
c) Discuss the limitations of the model.
PROCEDURES
Assignments are due at exactly the start of class. Unless stated otherwise in class, all assignments must be
turned in by email. See the file 'Paper Rules' on the course homepage for more full explanation. Late assignments
will be docked 1/3 of a letter grade (or the equivalent) for each day late. All days, including holidays, count.
Exceptions are rarely granted, and then only at the discretion of the instructor upon receipt of acceptable evidence.
Computer lab assignments may be done during time available in class, providing there are any, or
scheduled by arrangement or appointment with the instructor or the appropriate GA.
You should keep a copy of all the assignments you turn in.
It is recommended that students bring a calculator to each class session or know how to use the calculator
function on the lab computers.
Academic dishonesty (plagiarism, cheating, etc) will not be tolerated and will be punished to the maximum
extent allowed. In the specific case, all work presented on your exercises must be your own. Collaboration is not
permitted [that is, group preparation and reporting of assignments], although working together appropriately may be.
In other words, students may discuss how to do certain statistical manipulations, but must do the manipulations and
the write-ups by themselves.
TENTATIVE LECTURE AND READING SCHEDULE
Week 1
Introduction to 678.
Week 2
Ch. 7 & 8
Week 3
Continue Ch. 7 & 8
Week 4
Ch. 9
Week 5
Ch. 11
Week 6
Ch. 12
Week 7
Continue Ch. 12
MID-TERM EXAM
Week 8
\
Week 9
Ch. 13
Week 10
TBA
TBA
Week 11
TBA
Week 12
TBA
Rest of semester
Do stats