Econ 20150, Principles of Statistics
Syllabus, Eco 20150 (formerly Eco 29000), Spring 2012 Principles of
Statistics Tuesday and Thursday 2 – 3:15 NAC 5/101 |
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Course Description |
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This course is designed to teach you to use the simple statistical
tools that form an economist's basic toolbox.
This is a hands-on course where you will work with a lot of real
data. The aim of this course is to get a
better understanding of statistics, of how numerical evidence is used and
abused, and of how people can torture the numbers to make them appear to
support their point of view. In our
world statistics are the first choice for how someone is going to lie to
you. If you know some of the secrets
then you will be able to see through other people's lies (and perhaps create
some of your own – if you choose to embrace the dark side!)..
Textbook |
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This course will use the textbook Applied Statistics for Business and Economics, David Doane and Lori Seward, 3rd edition, McGraw Hill.
The e-book is available here, http://bit.ly/zjItnO.
Earlier editions are very close substitutes but you are
responsible for ensuring the concordance to the most recent edition, for
homework assignments. You may wish to get the accompanying study guide, but it
is not necessary.
Professor |
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Kevin R. Foster, Department of Economics, The City College of New York, kfoster@ccny.cuny.edu, w: (212) 650-6201, m: (860) 593-7674, office hours Tuesday 11-noon and 3:30-4:30 or by appointment, http://www.ccny.cuny.edu/social_science/kfoster/
Course
Requirements/Prerequisites |
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This course will assume that you've taken the prerequisites,
Principles of Micro and Macro. Calculus
is not a prerequisite although I will occasionally use it to help more advanced
students get a fuller understanding. I
will use other math freely and often.
Stats doesn't require any high-level math (occasionally we will take
derivatives or integrate, but only to illustrate a point). But stats does require a willingness to work
with algebra and plow through the applicable formulas. However, that said, the point of doing it on
a computer is so that the machine can do the donkey work while you worry about
bigger questions – so what? why? what does it mean? what else do I need to know? what other hypotheses could present the same
pattern?
Some course material will be presented in online videos: the
course is one-quarter online (since it is four credits but meets in person on a
3-credit schedule). Most homework
assignments will be submitted online; some will be entirely online.
Educational
Outcomes |
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Students will be able to apply mathematically rigorous analysis to topics such as hypothesis testing, common probability density functions, and regression analysis. More details in the document, "Skills Learned in This Course," available from the course webpage.
Grading |
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Course grades are determined by three factors: your scores on the exams, your demonstrated skill at using statistical analysis in a final project, and your scores on the homework assignments. The exams have a 50% weight, the project has a 30% weight, and homework gets 20%. There is no BS factor of effort or any other unobservable will-o-wisps – the weightings sum to 100. Your grade is determined entirely on observed performance.
Your exam grade is based on your best 2 out of 3 exams: two during the term and one final exam. If your first 2 exams are satisfactory you may choose to not take the final and concentrate on the project. Alternately if you bomb one of the exams then the final will substitute.
You have the option of forgoing the homework assignments and having your grade determined only by exams and project. This is unwise but, as an adult, you can make the choice. You must submit the online form to me early in the semester.
Grades will be posted on the course page, so that you can
check your progress and determine what grade you can expect to receive. In this
public grade posting, you will be identified only by the last 4 digits of your
ID number (if you wish to choose some other 4-digit identifier, email me).
Time Requirements |
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You should expect to spend 10-12 hours per week on this class. My simple calculation is that a student who is going to school "full time" takes 4 or 5 classes. Someone who works fulltime at a job works 40-50 hours per week. So about 10 hours per week is a good estimate (this class is 4 credits so it will take a bit more). If you don't put in that much work then you can't expect to get a good grade. (This is confirmed by research; on average a student studying one more hour per week can raise her term GPA by 0.36 – from a B to B+, for example. Stinebrickner & Stinebrickner, 2008. BE Journal of Econ Analysis & Policy, 8(1).)
Final Project |
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You will work with a small group of fellow students to write a project to analyze a question using one of the datasets that we'll be working with. Many (not necessarily all) will make a presentation about this project in class; the presentation counts as homework and then the written project has a separate grade. Attendance for the presentations of other students is also counted as a homework grade. The project will require you to use statistical analysis software with a large dataset. More details will be given later in the course.
Course
Material |
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Homework and basic course documents will be on the class page, publicly accessible from my web page (http://www.ccny.cuny.edu/social_science/kfoster/). Readings and datasets will be on InYourClass.com (login required). Some of the homeworks will be available on the Blackboard course page (login required). I will periodically send emails to the class via Blackboard so you must keep your CCNY email updated.
Computer Use |
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This course will use SPSS, data analysis software that is commonly used in business. You are not required to have previous experience with programming although that would be useful. There are online videos explaining the basics of how to use SPSS in statistical analysis.
TA Help |
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There will usually be a TA available in the economics computer lab (NAC 6150) on a schedule to be announced – look on InYourClass.com under "Economics Society" group for details. They won't do your homework for you, though!
Additional Reading |
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If you begin a love affair with Statistics and want to read
more, here are some suggestions:
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Leonard Mlodinow, The Drunkard's Walk: How Randomness Rules
Our Lives
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Edward R. Tufte The Visual Display of Quantitative
Information, Visual Explanations:
Images and Quantities, Evidence and Narrative (in library)
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Howard Wainer, Graphic Discovery: A Trout in the Milk and Other Visual Adventures
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David Salsburg, Lady Tasting Tea: How Statistics
Revolutionized Science in the Twentieth Century
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Stock & Watson,
Introduction to Econometrics and Kennedy, A Guide to Econometrics
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Jane E. Miller, The
Chicago Guide to Writing about Numbers (in library)
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John W. Tukey, Exploratory Data Analysis (in library)
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Stephen Stigler, Statistics
on the Table (in library) and The
History of Statistics: The Measurement of Uncertainty before 1900 (in
library)
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Dierdre McCloskey, Economical Writing and The Rhetoric of Economics (in library)
Weekly Topics: Principles of Statistics, Eco20150, Spring 2012 Kevin R Foster, CCNY |
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Week |
Date |
Topics |
Chapter(s) in text |
1 |
Jan 31,
Feb 2 |
Data, Descriptive
Statistics |
1, 2, 3,
4 |
2 |
Feb 7, 9 |
SPSS |
additional
online |
3 |
Feb 14,
16 |
Probability |
5 |
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Feb 21 |
No class: CUNY Monday
Schedule |
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4 |
Feb 23 |
Discrete
Probability Distributions |
6 |
5 |
Feb 28,
Mar 1 |
Continuous
Probability Distributions |
7 |
6 |
Mar 6, 8 |
Sampling
Distributions & Estimation |
8 |
7 |
Mar 13,
16 |
One-sample
Hypothesis Tests |
9 |
8 |
Mar 20,
22 |
Two-sample
Hypothesis Tests |
10 |
9 |
Mar 27,
29 |
Review; Exam 1 on 29th |
1-10 and
online |
10 |
Apr 3, 5 |
Analysis
of Variance |
11 |
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Apr 10, 12 |
No class |
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11 |
Apr 17,
19 |
Simple
Regression |
12 |
12 |
Apr 24,
26 |
Multiple
Regression |
13 |
13 |
May 1, 3 |
Review; Exam 2 on 3rd |
1-13 and
online |
14 |
May 8, 10 |
Presentations
on Final Project |
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15 |
May 15 |
Presentations
on Final Project |
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sometime May 17-24 |
Final Exam |
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May 24 |
deadline for final project |
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Chapters refer to Applied Statistics for
Business and Economics, David Doane and Lori
Seward, 3rd edition, McGraw Hill.
There will be lecture notes available online – these are important. Exams will cover material in both textbook
and lecture.
Deviations from the schedule will be announced in class.
The exam dates are given above. You must take the exams at
the scheduled times. No excuses.
Academic Integrity |
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The CCNY Faculty Senate has recommended that every
course syllabus include this notice:
CUNY Policy on Academic Integrity
As stated in the CUNY Policy
on Academic Integrity: 'Plagiarism is the act of presenting another person's
ideas, research or writings as your own. The following are some examples of
plagiarism: