NATS 1500 2017W/General Information

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Table of contents


How do you know what you know? Why do you feel very confident that some things are true but you feel less sure about others? Do you feel very sure about some things that, perhaps, you shouldn’t be so sure about? And unsure about things that you should, in fact, be confident of.

Statistical reasoning is crucial for a critical understanding of the flood of data and information we face daily in modern society. Understanding the principles of statistical reasoning and being aware of some widespread errors in statistical thinking is the key to allow you to distinguish arguments that are sound from those that are fallacious.

This course stresses the logic and reasoning behind statistics. We avoid complex mathematical formulas. Statistical reasoning is applied to a critical analysis of current events reported in the media and current scientific, medical and social controversies.

By the end of course, you will have developed an understanding of the reasons why scientific evidence can appear to lead to contradictory conclusions. You will have a better understanding of the assumptions that lead to these different conclusions and you will be in a better position of have informed judgments on the quality of scientific claims.



Assignments, Tests and Grading

Dates for NATS 1500: (unless otherwise indicated all work is due at 12 noon on the date shown)
Due Weight Link
approximately weekly
individual and/or team
Announced for each assignment 25% Watch the Calendar
Team Project Monday, Jan. 30 5%
Mid-term test Saturday, March 4 25% 8 pm to 9 pm
Project (individual) Wednesday, April 5 10%
Final exam April 7 - 24 30% Date will be set by the registrar
in late February
Participation Jan. 9 - April 5 5%

Participation in the forums and in class. You should contribute at least 6 meaningful posts to the Piazza forum.
After the last class and no later than April 8, send a brief summary statement to (500 words or less) about your contributions to the class. E.g. how many posting and comments? Describe briefly some of your most significant ones. Include links to the posts you refer to in your email message.

See also: Important academic dates from the York website (


  1. Wainer, Howard (2016) Truth or Truthiness: Distinguishing Fact from Fiction by Learning to Think Like a Data Scientist, CRC Press
    Available in the bookstore and in Steacie Library Reserves.
  2. Jessica M. Utts and Robert F. Heckard, (2006) Statistical Ideas and Methods, Thomson.
    The original edition is out of print although many used copies may still be available. The edition available in the bookstore is a special reprint that includes all the material of the original text except many photographs and illustrations with a decorative function. All statistical materials including graphs are the same. The pagination is different so assigned problems will be given by chapter and section numbers so you can follow the course with the original text or with the special reprint.
    This is a very good textbook that is, unfortunately, like many other textbooks expensive. Consider options such as:
    • sharing a textbook with other students
    • using the copies on 2-hour reserve in the Steacie Science Library (QA 276 U88 2006 BOOK).
    • trying to find a used copy through the York Bookstore ( or through other sources. The book has been used for this course for five previous years at York so that used copies should be available on campus.

Official Registrar Course Description

Statistical reasoning is crucial for a critical understanding of the flood of information we face daily in modern society. This course examines the principles of statistical reasoning with an emphasis on applications to everyday decisions and turning information into understanding. Course credit exclusion: SC/MATH 1532 3.00. NCR Note: Not open to students who have passed or are taking AK/AS/SC MATH 2560 3.00, or who have received advanced standing for the equivalent.

Lectures and Tutorials

  • Class: Monday, 2:30 pm to 4:30 pm and Wednesday, 2:30 to 3:30 in Vari Hall (VH) C. The first class takes place on Monday, January 9, 2017.
  • Optional tutorials: Occasional optional tutorials will be held on Wednesdays, 3:30 pm to 4:30 pm in VH C. The purpose of the tutorials will be to help you with problems using computers and to discuss questions regarding the material of the course.

Course Policies

Late assignments
Late assignments or projects are penalized 10% of the value of the assignment for each day (or portion of a day) it is late. Unless a different time is specified, assignments and projects are due at 12 noon on the due date. Teams should plan to have a 'final draft' of the team assignments at least 2 days before the deadline so every member of the team can review and okay the draft before submission.
Missed term test
If you miss the term test with a suitably documented medical or compassionate reason, your mark for the term test will be imputed from your mark on the final exam. Otherwise you receive a grade of zero for the term test.
Use of computers in class
You are encouraged to bring your laptop to class to use it for purposes directly related to the class such as taking notes, annotating slides posted on the web or trying out commands in R. Some students think that it does not affect anyone else if you are doing your own thing in class on your laptop or other electronic device. This is wrong. People seated around you cannot help but be distracted. And the instructor gets very distracted when members of the class are clearly lost in a different dimension. Therefore, you may not use your laptop to view unrelated materials such as videos because this creates a visual distraction for students seated near you and your lack of presence in the class is distracting to the instructor.
Class demeanor
If you need to ask your neighbour a question, pass them a note very discreetly. Sometimes, the instructor is so absorbed in what he is saying that he doesn't notice people talking. However, other students, who may be struggling to remain absorbed, do notice and are very distracted by conversations near them. They will be annoyed and many will come and complain to me for my failure to enforce adequate discipline. Please don't put me in this awkward position because I hate to enforce discipline.
Academic honesty
Familiarize yourself with the York University Senate Policy on Academic Honesty ( Violations of academic honesty are treated very seriously in university.


  • Datasets and lecture notes will be posted in Since some of the material may be copyrighted, access to the files is protected and you may be prompted for a userid and password. Use 'nats' for both.
  • When you find interesting links on the web you will be able to post them to forums on Template:Nats1500-piazza and contribute to your grade for participation.

Team Assignments

One project and a number of assignments are done by semi-randomly assigned teams. Why random teams? One reason is that in almost all job interviews, you are asked about your experience working with teams. Working with a diverse team that you didn't select yourself gives you the opportunity to have experiences that will give you great anecdotes to use in your future job interviews. When you land the job, you will be much more likely to show the kind of leadership in team work that is invaluable in the modern workplace.

General comments and details
  • I will email the list of members in your team some time during the weekend of January 14. The members of your team can communicate by email, meet in person, and use the special team forum.
  • All assignments are due at 9 am on the due date. Use the tutorial hour the previous Wednesday to meet with your team and to finalize your submission for the assignment so you only need to do some proofreading and merging before the final deadline.
  • Include the names of all active participants on the first page of the assignment. Everyone who participated actively gets the same grade. Those who didn't, get zero. Note that some team members might not respond because they have dropped -- or intend to drop -- the course. If your team shrinks to 3 or fewer, let me know and I can merge your team with another small team. Exceptionally, if some members of the team consistently do considerably less work than other members, the instructor may award those members a correspondingly reduced grade.
  • The more work you do on an assignment the better prepared you are to do well on the term test and on the final exam. But you shouldn't hog the work -- let others do their part too. Everyone should make sure that they understand the whole assignment. Discuss the assignment with your team members to make sure everyone understands the key points and difficulties of each question.

Project (Individual)

Due: Wednesday, April 5 through Moodle

Find a causal question that you find interesting. It should be a real question that involves a decision perhaps for you or for someone you know or a policy decision for a government or enterprise. Clearly state the question and why it is relevant. Explain why it is a causal question and not a predictive question?

Find and study at least three sources that are relevant to the question. At least one source should be in the 'popular' media and at least one in the academic literature. The source in the academic literature can be one that is referred to in a source in the popular media.

For each source, write a synopsis of their claims. Most claims of a causal nature will be based on prior theoretical knowledge of the links between variables together with some components that are less well understood and rely on the interpretation of data.

Write a detailed and insightful critique of the claims in each source. Are they based on observational or on experimental evidence. If the evidence is observational, what attempts have been made to control for possible confounding factors? Have any moderators been considered? Have possible mediators been controlled, possibly suppressing an actual causal effect? Are the subjects used relevant for context that interests you. Comment generally on internal and external validity relative to the context of your question.

Conclude with a general assessment of the information you have found and how it answers -- or not -- your original question.

Include references and links to your sources.

Some guidelines for your report:

  • Aim for a length of 8 to 12 double-spaced pdf pages of analyses and discussion plus at approximately 2 pages of relevant figures (copied with attribution or hand-drawn).
  • Grading:
    • Clear expression of specific question and relevance: 25%
    • Choice of sources and clear references and links: 25%
    • Clarity and quality of analysis and argument: 30%
    • Clear formal academic style of writing: 5%
    • Effort: 5%
    • Structure: 5%
    • Overall appearance: 5%
    • You can get bonus marks in any category if you do an absolutely brilliant job in that category.

Class representatives

In approximately 2 weeks, we will select 3 class representatives. This is a practice in the Division of Natural Science. The class representatives meet, later in the term, with the Director of the Division of Natural Science, Professor Julie Evans, who uses their feedback to help guide the development of courses in the Division. The class representatives can also act to give feedback to the instructor as well as acting as a liaison.

Using computers for the course

Some assignments will require you to use computing software to view and analyze data. The test and exam will require you to interpret output from the same software. You can learn the computing aspects of the course in a number of ways:

  • If you have access to a computer, you can download the software for the course. We use public domain software that runs on Windows, MacOS X or Linux. If you have a laptop, you are encouraged to bring it to class and to tutorials and office hours.
  • If you don't have access to a computer, you can get an account to use computers in the Gauss Lab where the software will be available. You also need a card to access the Gauss Lab.
  • The course will show detailed examples of simple statistical analyses using R.


This is the NATS 1500 Moodle site ( link to the MOODLE site for NATS 1500. We will use Moodle for two purposes:

  • A way for you to submit some assignments.
  • A way for you to find out your grades as the course progresses.

Log in to make sure you are properly connected to Moodle.


Where can I go for help?

  • Tutorials, Most Wednesdays 3:30 to 4:30. The instructor will be present to answer questions.
  • Instructor's office hours: Fridays 8 am to 10 am or at other times by appointment.
  • NATS AID: Undergraduate students who have already taken the course and done very well volunteer to help. More information to come.
  • Statistics Learning Centre in the Department of Mathematics and Statistics at South Ross 525. Teaching Assistants who are assigned to help with introductory statistics courses are available to help. Some may be designated for NATS 1500 because, believe or not, we cover some material that many graduate students have not learned! More information to come.