Course Organization
Time & Location:
Monday, 10:15-12:00, Rigot
Professor:
Jim Morrow
Office: Rigot 22
Office hours: Tuesday 09:00-12:00
Telephone: 022 908 59 39
E-mail: morrow@hei.unige.ch
Assistant:
M. Sanjines
Office: Rigot 27
Email: sanjine7@hei.unige.ch
Course Description
This course introduces the student to statistical thinking, its application in social research, and basic statistics. Learning how to think statistically is the central goal, rather than learning statistical calculations by rote. Students should learn the logic of statistical reasoning about data, to be better consumers and producers of data analysis. The course should also provide a strong foundation for those who choose to take additional courses in statistical methods.
The textbook for the course is James B. Ramsey, The Elements of Statistics, With Applications to Economics and the Social Sciences, Duxbury Thomson Learning. We have instructed the library to buy some copies which will be on reserve. Until the books arrive, we will provide you with copies of the chapters to be read for each class. I suggest that you purchase the book for your future reference. The cheapest places I have found are Amazon UK (http://www.amazon.co.uk/) £23.09 and the publisher (http://www.thomson.edu/thomsonedu/) £34.99.
Each class period will be a combination of lecture and computer demonstrations. The lecture portion will cover the central points of each week’s readings. The demonstrations will show you graphical depiction of data and statistical analysis comparable to what you will be asked to do in the following assignment. I will send out the lecture presentations in advance of each class and the log files of the computer demonstrations afterwards. Please feel free to ask questions during lecture. You may also bring a laptop along to follow the computer demonstrations by copying the commands and running the program on your laptop.
The grading will be based on weekly assignments and a final examination. The weekly assignments will be a combination of written and computer exercises. They are due in class the week after I distribute them. Late assignments will not be accepted. Learning by doing is the only way to really learn statistics, making these assignments a necessity. You may work in groups on the assignments, but everyone must turn in their own paper. The final examination will be held in the classroom on the Monday after classes end. The weekly assignments count for two-thirds of the grade, and the final exam the other third. We will drop your lowest score on an assignment when calculating the final grades. Assignments will be returned at the class after they are due. Answer sheets will be provided, and M. Sanjines will conduct a review session for those who would like to go over them.
Course Outline
Week 1 (March 12):
Introductory Meeting
Week 2 (March 19):
Types of Data and Introduction to STATA
- Reading: Chapters 1 and 2
Week 3 (March 26):
Graphical Summary of Data
Week 4 (April 2):
Moments and the Shape of Histograms
April 9:
No class
Week 5 (April 16):
Description of Bivariate Data: Correlation
Week 6 (April 23):
Theory of Statistics
Week 7 (April 30):
Discrete Probability Theory
Week 8 (May 7):
Continuous Probability Distributions
Week 9 (May 14):
Sampling Theory
Week 10 (May 21):
Estimation of Moments and Parameters of Distributions
Week 11 (May 28):
Hypothesis Tests
Week 12 (June 4):
Conditional Probability Distributions
Week 13 (June 11):
Regression Analysis
The final exam is in class on Monday, June 18 from 1015 to 1200.
