Political Science 201
M 4-6:40 pm
R. Hofstetter AH-4116
richard.hofstetter@gmail.com
(22470)
MCN-105
594-6244
MT 6-7 p.m.
ELEMENTARY STATISTICS FOR POLITICAL SCIENCE
OBJECTIVES:
This course is introduces students to basic concepts, theories, and methods of the way in which political
scientists compute and use statistics in making decisions about political issues. The course serves as an
introduction to the use of descriptive and inferential statistical methods in political and other social
sciences.
TEXTS:
Required:
Minium, Edward W., Clarke, Robert C., & Coladarci, Theodore. (1999).
Elements of Statistical Reasoning. New York: John Wiley & Sons, Inc. 2nd
ed. Paperback.
Please make a xerox copy of the statistical tables from the back of the text
and bring them to each class. These will be used for quizzes and tests, and
students who fail to attend class without a xeroxed copy of the tables or a
working calculator will be at a disadvantage .
POLICIES AND PROCEDURES:
Students should bring an inexpensive, operating calculator to each class as well as required tables, pencils
or pens. Add, subtract, multiply, divide, and square root functions are the only functions necessary. No
need to purchase an expensive calculator just for this class. Generally, scientific calculators and hand
computers are more trouble than they are worth for this class. Use of an inexpensive, light driven calculator
is a good idea, since students do not have to worry about batteries failing and classroom lights are usually
adequate to power most such devices. Cell phones should not be used for computing.
Students are responsible for all material in the assigned portions of the text, class discussions, or on
blackboard whether I discuss it explicitly or not. Once class has begun, please enter the class as
unobtrusively as possible or wait until a break to enter the room. If you must leave the class before it is
over, it is polite to inform me before the class begins unless you suddenly become ill during the class.
Students should complete reading and graded homework problems in a manner that maintains pace
with the topics being discussed and the lectures. Students are required to attend all class meetings and to
take examinations and quizzes in class. (N ote that the purchase of airplane tickets, vacations, athletic
events, etc., in the absence of a bona fide personal emergency are not excuses for missing classes.)
Quizzes or midterms will be given at each class meeting and are closed book, and all step by step
computations must be shown neatly and legibly on what is handed in to earn full credit for a problem. If I
cannot read what you have written (because it is illegible or because it is messy or for other reasons), then I
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will not give points for the work. Points will also be deducted if intermediate steps and computations are
omitted or illegible. Students may use up to three pages of original handwritten (not typed or
photocopied) notes, the syllabus (with statistical tables), and a calculator for exams and quizzes. No final
examination or extra credit assignments will be given. No makeup examinations or quizzes will be given
except in extraordinary situations and then only at my discretion and with student documentation. It is the
student’s responsibility to bring a working calculator since I rarely have an extra one, statistical tables,
and paper and pencils/pens to class.
One to three hours credit for POLS 499 working on research under my supervision may also be
available, depending on the semester. Interested students should contact me while there is still time to add a
class early in the semester.
SDSU students should also open e-mail accounts since I will communicate with you via blackboard
on occasion. My e-mail address is available on blackboard and this syllabus to enable students to
communicate with me outside my scheduled office hours for students' convenience. I anticipate that
students will make use of this opportunity in case they wish to communicate with me, since I do not use
telephone voice mail at SDSU.
I do not allow cell phones or personal computers to be operated in this classroom. Students
should turn off cell phones and avoid bringing computers to class. Cell phones may not be used for
computation. Except in emergencies and only with prior permission from me, DO NOT look at, have
out, let ring, or talk on a cell phone in this class! I am willing to discuss exceptions to cell phones in
this class, but exceptions will not be given outside of severe medical or other reasons.
Academic dishonesty will not be tolerated. All written work must be your own original work (i.e.,
not previously submitted for credit in any other course, either at SDSU or at any other academic institution)
and also not copied from anyone else or any other source. Purchased or downloaded papers de facto
constitute cheating. Please familiarize yourself with the University Policy regarding Cheating and
Plagiarism at: http://www-rohan.sdsu.edu/dept/ senate/policy/pfacademics.html Also be aware of the
Student Grievances procedure, available on-line at: http://www.sa.sdsu.edu/srr/statement/sectionVII.html
Plagiarism not only includes a student representing the works, ideas, and writings of others as
his or her own. It also includes a student using a previous work product (published or unpublished) that
the student was involved in (e.g., as sole writer or co-writer) for any academic-related activity (e.g.,
class assignments and tests; theses; and the non-thesis options, etc.), representing it as original work
that was performed for the new academic-related activity. Unpublished works include, but are not
limited to unpublished manuscripts, grant proposals, and web-based material.
NOTICE:
Do not come into this class expecting any particular grade. I do not give grades; students
earn grades by their performance in class participation and on assignments and tests. Please do
not try to game me for a higher grade since any special consideration is grossly unfair to all
others in the class.
Except in the case of a written documented illness requiring medical attention or a death in
the immediate family, late assignments, and missed quizzes and tests will be graded 0 points.
Students who fail to turn in all assigned work by the last class meeting will fail this course with a
grade of F regardless of other performance. All work must be turned in by 4 pm, December 9,
2012, in order to avoid an F.
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GRADING:
Examinations
Quizzes
Homework
35%
35%
30%
Computation of Grades. Please read this paragraph carefully. Grades will be based on a straight
percentages with 90%-100% being an A, 80%-89% a B, 70%-79% a C, 60%-69% a D, and below 60% an
F. Note that an 89% is a B, while a 90 is an A, a 79 is a C, while an 80 is a B, and so on. Percentages will
be computed from the number of points that assignments are given based on the maximum number of
points anyone received for an examination or problem set. No one will pass this course unless all
assignments are turned in by the last day of the course, December 9, at 4 pm. If you are having
problems in this class it is imperative that you contact me during office hours as soon as the problems
occur. Although the class has comparatively little reading, the key to success in the class is to simply
spend the time studying
. Many have found study groups to be helpful.
Course grades will be based on the distributions reported above, i.e., 35% of the final grade will
be based on examinations, 35% on quizzes, and 30% on homework. Numerical scores will be entered
in blackboard to communicate scores to students, but final letter grades will not be entered in blackboard.
If mistakes occur in scoring, then it is imperative that students bring the original scored exams, quizzes, or
homework to me as soon as possible so that I can make corrections. No changes will be made in the
absence of the original graded work. All assignments must be submitted in hard copy—no electronic
submissions—and placed in my mailbox inside the department of political science during its hours or
in the drop box outside the political science office (inside an envelope with my name on it). Do not
push assignments under my door or in the container outside my office since this is likely to result in the
loss of your work. It is also prudent to make a xeroxed copy of assignments in the unlikely event that they
become misplaced.
NOTE: Again, no one will pass this course unless all assignments are turned in by the last day of this class
December 9, 2012 at 4 pm. If you do not wish to continue with the course, formally drop it to prevent
receiving an F for the semester. If you decide to drop the class, be sure to officially drop with SDSU.
Do not just “disappear.” Otherwise you will end up with an F.
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OUTLINE
The course is divided into a series of topics, described below. Approximately one week of lectures and
discussions will be allocated to each topic. Minor changes to the schedule may occur.
Week 1
Aug 26
What are statistics? What are data? What use are statistics? What is
measurement? How do we measure political phenomena? Minium et al.,
Chapter 1, pp. 1-13. Introduction. Practice homework: 1,2,3,4. Graded
problems 3, 4, p. 13 due September 9.
LAST DAY DROP CLASSES is September 10, last ADD this class is
September 12.
Week 2
Sept 2
Labor Day Holiday
Week 3
Sept 9
What is a distribution of data? How do we organize data so that they can be
interpreted? What are the costs and benefits of summarizing data? Minium
et al., Chapter 2, pp. 17-34. Frequency Distributions. Graded problems:
13, 14, pp.33, 34 due September 16.
Week 4
Sept 16
What is the utility of graphic presentation? What are the risks of graphics?
How do we minimize those risks? Minium et al., Chapter 3, pp. 35-50.
Graphic Representation. Graded problem: 12, p. 49 due September 23.
Week 5
Sept 23
How can we describe data with a single number? What are the benefits and
risks of each procedure? Which measures are used most commonly? Why?
Minium et al., Chapter 4, pp. 51-61. Central Tendency. Graded problems:
8, p. 60 due September 30.
What is variability and why is it important in describing data? What are the
common measures of variability and which is most often used? Why?
Minium et al., Chapter 5, pp. 63-77. Variability. Graded problems: 5, 15
pp. 76, 77 due September 30.
Week 6
Sept 30
What is a normal distribution? Why is such a distribution useful? How
does one use normal distributions? Minium et al., Chapter 6, pp. 79-101.
Normal distributions and Standard Scores. Graded problems: 6, 9, 10, 11
pp. 100, 101 due October 7.
Week 7
Oct 7
What is a relationship between variables? How can we describe
relationships using a single number? What does it mean to assume a model
in relationships between variables? Minium et al., Chapter 7, pp. 103-129.
Correlation. Graded problems: 3, 4, 7 p. 128 due October 14.
First Midterm Examination (weeks 1-5).
Week 8
Oct 14
How can predictions be made from data? What is the most common model
used to do this and what assumptions are made? Minium et al., Chapter 8,
pp. 131-156. Regression and Prediction. Graded problems: 3, 6, p. 153
due October 21.
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Week 9
Oct 21
What is probability and what does it mean? What is empirical probability?
What is a probability distribution? How is the probability of an event
determined. Minium et al., Chapter 9, pp. 159-175. Probability and
Probability Distributions. Graded problems: 4, 5, 7, 15 pp. 173, 174 due
October 28.
Appendix 1, attached to syllabus and on blackboard. What is the binomial
distribution? How is it applied to calculate probabilities of events?
Week 10
Oct 28
What is a sampling distribution? How are they different than other
distributions? How are sampling distributions used in determining
probabilities of outcomes? Minium et al., Chapter 10, pp. 177-197.
Sampling Distributions. Graded problems: 7, 10, 11, 15 pp. 195, 196 due
November 4.
Week 11
Nov 4
What is an hypothesis? How are hypotheses tested? What assumptions are
made in testing hypotheses? What is the “seven-step model” used in
hypothesis testing and why is it important? Minium et al., Chapter 11, pp.
199-219. Testing Statistical Hypotheses about Mu when Sigma is Known.
Graded problems: 4, 15 pp. 218-219 due November 18.
Second Midterm Examination (weeks 6-10)
Week 12
Nov 11
Veterans’ Day Holiday
Week 13
Nov 18
What is sample estimation? How is it different than hypothesis testing?
How does one estimate population characteristics from samples? Minium
et al., Chapter 12, pp. 221-232. Estimation. Graded problems: 2, 10 pp.
231-232 due November 18.
Week 14
Nov 25
Testing Statistical Hypotheses about Mu when Sigma is Not Known. How
are hypotheses tested when information about a population is limited? What
assumptions are made? Minium et al., Chapter 13, pp. 231-250. Graded
problems: 5, 6, 22 pp. 247-249, 219 December 2.
Week 15
Dec 2
How do we test whether groups are different? What are the steps? What
assumptions are required? Minium et al, Chapter 14, pp. 251-274.
Comparing Means of Two Samples. Graded problems: 2, 5, 8, 10, 16 pp.
271-273 Due December 9.
Week 15
Dec 9
Discussion. Third Midterm Examination (cumulative). All exercises
must be turned in by the beginning of class (4 pm) today to avoid
failing this course.
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Appendix 1
Probabilities (The Binomial Distribution)
When one has an a priori probability that can be assigned to the outcome of an event and is
evaluating repeated independent trials of that event, such as coin flips, the binomial distribution
can be used to evaluate the probability of discrete events.
Let us imagine that we are flipping a coin three times and wish to evaluate the probability of two
heads in 3 flips. If we have an honest coin, the probability of a head in any single flip is .5 and
the probability of 3 heads in 3 flips is computed using the multiplication rule: P(3H)=P(H) X
P(H) X P(H), or .5 X .5 X .5 = .125. There is only one way that a person can flip 3 heads in 3
trials.
However, there are several ways one can flip 2 heads in 3 trials. Let’s start with a single
outcome: P(2H)=P(H) X P(H) X P(T) is one of the ways of doing this, but only one of the ways.
The probability of this one outcome is P(2H) = .5 X .5 X .5 = .125.
The problem is that there are other ways of reaching the desired outcome and we have to include
those in the assessment of the problem. The binomial expansion is used to accomplish this. The
binomial involves two terms: 1) One states the number of ways that a single event can occur in a
specific number of trials; and 2) the other is the probability of any one of the events occurring.
The latter is given as P(2H), or .125 as shown above. The number of ways that two heads can
occur in three flips is given by:
(PxQ1-x)
n!
Where Px is the probability of a success and Q 1-x is 1- the
r!(n-r)! probability of a success, n is the total number of events and r is
the number of events that we are interested in.
x
1-x
In this case, P =.5, Q =1-.5=.5, r = 2, the number of H type outcomes, and n = 3, the total
number of flips. n! (n factorial) = 1 X 2 X 3 = 6, and r! = 1 X 2 = 2. n – r = 3 – 2 =1, so the
number of ways we can obtain two heads in three flips is 6 / 2 = 3. The probability of one of
these occurring is the number of ways it can happen times the probability of any single way, or 3
X .125 = .375. The the probability of 2H in 3 flips = .375.
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