NATS 1500: STATISTICS AND REASONING IN MODERN SOCIETY - WINTER 2011
Statistical reasoning is crucial for a critical understanding of the flood of data and information we face daily in modern society. For example, we are frequently exposed to contradictory claims about the effectiveness of drugs or of new social policies. How can someone who is not a specialist have an informed opinion when it seems that experts do not agree? Understanding the principles of statistical reasoning and being aware of a number of widespread errors in statistical thinking is often the key for distinguishing arguments that are sound from those that are not. Above all, understanding statistical reasoning helps us distinguish between solid claims and those that are at best tentative and about which we should keep an open mind.
This course stresses the logic and reasoning behind statistics, avoiding emphasis on complex mathematical formulas. Statistical reasoning will be applied to critical analysis of current events reported in the media, as well as scientific, medical, and social controversies.
The topics covered include:
• Beyond “correlation is not causation”: randomized experiments vs. observational studies; prediction versus cause. Experimental versus statistical control.
• Statistical significance vs. practical importance.
• The difference between finding “no effect” and “no evidence of an effect”.
• Common sources of bias in surveys and experiments.
• Interpreting improbability and coincidence: why the improbable is often highly probable.
• “Confusing the inverse”: conditional probability in one direction is confused with the conditional probability in the other direction. Implications for fallacious interpretation of information and decision making.
• Understanding that variability is natural and that the average is not necessarily typical.
These concepts will be studied through classroom discussion as well as real data assignments/projects.
In addition, class tests/quizes will be used for evaluation. All concepts will be actively applied to the clarification of current scientific, medical, and social controversies.
Prerequisites: This course assumes high school algebra to the level of grade 11.
Course Credit Exclusions: SC/MATH 1532. Not open to students who have taken AK/MATH 2560, or who have received advanced standing for the equivalent.
Textbook: Jessica Utts and Robert Heckard, Statistical Ideas and Methods 2006 (required) .
Computing: Statistics means data analysis, and this requires a computer. We will make use of the statistical software Minitab in this course. The CD in the back of the text contains the datasets and detailed instructions on how to use Minitab - no special lectures will be dedicated to learning Minitab.
However, optional tutorials will be held in the Gauss lab, where you can sort out any computing questions that you may have. Minitab is available through York’s WebFAS service. See the course website for details and links.

Instructor: Hanna Jankowski
Email: hkj@mathstat.yorku.ca
(Please include [1500] in the subject heading, text only - no html, no “texting”. Always include your name and student number.)
Office: Ross N621B
Lectures: W 2:30-5:20pm in CSE B.
Optional Tutorials: W 5:30-6:20pm (January 10th to April 4th only) in Ross S110 (Gauss lab). An
AML account, a properly encoded YorkCard, and registration in an authorized class is required to use the Gauss lab.
Additional Office Hours: By appointment only. No drop-ins, please.
Course web-page: http://www.math.yorku.ca/ ∼ hkj/Teaching/1500/
Grading Scheme: Term tests (2) 15% / 15%, Assignments (3) 10% / 10% / 20%, Final Exam 30%.
COURSE POLICIES:
(1) The term tests will be written during the scheduled times. There will be no make-ups scheduled. In case of serious illness supported by medical documentation, the weight of your final exam will be increased to make up the difference. All medical documentation must be received within one week of the date of the quiz/test.
(2) The final exam will be scheduled by the office of the registrar. You are required to be present for the entire duration of the exam period. Deferrals will be granted only in the most extreme medical emergencies with supporting documentation.
(3) All assignments must be handed in on the day on which they are due.
Late homework will not be accepted.
In case of serious illness supported by medical documentation, the weight of your final exam will be increased to make up the difference. All medical documentation must be received within one week of the due date of the assignment.
(4) Graded work will be handed back during lecture or tutorial hours. If you disagree with the mark you have received, you should submit a request in writing for regrading within one week of when the work was returned.
(5) Suggested exercises (homework) will be assigned weekly. Although you are not to hand these in, you are expected to do them. If you have trouble with a concept, you should probably do even more problems than those suggested. A portion of the tests/exam material will come directly from the suggested exercises! Typically, you should expect to do two hours of additional work for each hour of lecture.
(6) Important course information will be posted on the website. It is your responsibility to check the site on a regular basis. Ignorance cannot be used as an excuse.
(7) Some class meetings may involve in-class work that will form part of a homework assignment, or I may present the material in a format/notation different than what is in the book (in which case my version is the one to learn). In addition, announcements may be made in class, such as modifications to quiz dates. It is your responsibility to be aware of such announcements.
Ignorance cannot be used as an excuse. If you miss a lecture, it is your responsibility to find out what material was covered and get the lecture notes from one of your classmates (not your instructor).
(8) Getting help: Class participation is a key component to learning. If there is something you don’t understand, ask. You can also get extra help from me during the optional tutorials.