STAB22H3

Statistics I

University of Toronto Scarborough

This course is a basic introduction to statistical reasoning and methodology, with a minimal amount of mathematics and calculation. The course covers descriptive statistics, populations, sampling, confidence intervals, tests of significance, correlation, regression and experimental design. A computer package is used for calculations.
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24HR Notes for STAB22H3

Available 24 hours after each lecture

Caren Hasler, Mahinda Samarakoon

STAB22H3 Syllabus for Caren Hasler, Mahinda Samarakoon — Spring 2019

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UNIVERSITY OF TORONTO SCARBOROUGH
Department of Computer and Mathematical Sciences
STAB22H3 STATISTICS I Winter 2019
Course Description: Statistics is the science of collecting, organizing and in-
terpreting data. In science, society and everyday life, people use data to help
them understand the world and choose how to act, and statistical methods
help to separate sense from nonsense.
In this course, we learn about some of the most important techniques used
in statistical work. The emphasis of this course is on concepts and techniques
and will be useful to students who seek to gain an understanding of the use of
statistics in their own field. Our ultimate goal is to gain understanding from
data, going from data collection to analysis to conclusions.
Content, emphasis, etc. of the course is defined by means of the lecture ma-
terial - not only the textbook. It is important to attend all lectures, as there
is normally no simple way to make up for missed lectures (perhaps obtain
another student’s notes). There will also be many lecture examples using sta-
tistical software, which students will be using.
Important announcements, problem sets, additional examples, and other
course info will be posted on Quercus. Check it regularly.
Instructor:
Weeks 1-6: Caren Hasler
Weeks 7-12: Mahinda Samarakoon
E-mail:
caren.hasler@utoronto.ca
mahinda@utsc.utoronto.ca
Note 1: When sending e-mail to an instructor, please use your U of T e-mail
address.
Note 2: Depending on e-mail volume, we might not be able to reply to every
email received. Dr Ken Butler has prepared an FAQ page which gives answers
to some of the most frequent questions that we have received from students.
You can find this FAQ page on the course Quercus site (or just click https://
q.utoronto.ca/courses/77480/pages/faq-page?module_item_id=480674
) Before sending us emails, please check if the answer to your question is on
this FAQ page.
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Office: IC344 (Caren), IC442 (Mahinda)
Office hours: Posted on the course Quercus site in Course Information (see
https://q.utoronto.ca/courses/77480/pages/course-information)
Lectures:
LEC01: WE 10:00-11:00 in IC 130, FR 10:00-11:00 in IC 130
LEC02: MO 11:00-12:00 in AA 112, WE 11:00-12:00 in IC 130
Webpage: Course information will be posted on Quercus course page.
Textbook and Software
The text
Custom Edition for STAB22 of
Stats: Data and Models (2018). DeVeaux, Velleman, Bock, Vukov,
Wong
Third Canadian edition, publ. Pearson Canada
ISBN 9780135330302
The bookstore will have this “custom edition” with only the chap-
ters we need. The custom edition is cheaper than buying the full 3rd
edition.
Textbook (custom edition) comes with student solutions manual and
the software MyStatLab and StatCrunch
If you wish, you can buy only a MyStatLab access (instead of the
physical book). With MyStatLab access, you can access an eText of
the book.
Software
We use StatCrunch software (on web).
Requires access code (comes with text or can buy separately).
Easy to learn
We will show you what to do.
Learning StatCrunch enables you to analyze realistic data.
You will need to interpret output from StatCrunch on quizzes, tests,
and exams.
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Assessment
Item Percentage of grade
Quizzes and webwork assigns 20%
Midterm Test 30%
Final Exam 50%
How do we calculate the grade for Quizzes and webwork assigns (i.e. for item
1 above)?
For each student, we assign two grades for Quizzes and webwork assigns as
described below and choose the maximum of the two as the grade for Quizzes
and webwork assigns.
Grade 1: 15% for quizzes + 5% for webwork assigns
Grade 2: 20% for quizzes
Usually 20%-25% of the students in this course get A’s. Less than 5% of all
students who complete the course work fail.
Notes: The above calculation implies that webwork assigns are not manda-
tory. You can get the full 20% for component ‘Quizzes and webwork assigns’
from only quizzes. This online tool webwork does have problems and we may
not be able to provide solutions for some problems. If you are not comfortable
with this tool, please don’t use it. Most past students have told us that this
tool has problems, but still they like it and so we are keeping it for anyone
who wants to use it. This of course can help boost your grades for the compo-
nent ‘ Quizzes and webwork assigns’ if your quiz grades are low.
Quizzes
There will be weekly tutorials from Monday Jan 14. Enrol in a tutorial
asap if not already done.
There will be a quiz in each tutorial, starting from Monday Jan 21.
Intended to be straightforward if you are keeping up with material.
During quizzes, you can refer to your notes and/or the textbook.
We drop your worst quiz when calculating your quiz grade.
You must write quizzes in the tutorial for which you are registered. If
it is impossible to write in your tutorial, you must seek permission from
your course instructor to write in another tutorial for one week only. If
you write a quiz in a tutorial other than the one you are registered for,
without permission, you get zero.
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Your quiz grades should appear on Quercus within one week of writ-
ing the quiz (i.e. before the next quiz). TAs will distribute the marked
quizzes during the tutorial, one week after writing the quiz. Please make
sure that you collect all your quizzes and keep the marked quizzes un-
til the term is over. Please check Quercus every week and if your quiz
grade doesn’t appear, you should check with your TA. If your quiz grade
still doesn’t appear on Quercus, you may contact your course instructor.
The course instructor will ask for the marked quiz. If you do not have
the marked quiz with you, the instructor may not be able to proceed any
further.
webwork
Free web-based problem sets with instant feedback and unlimited trials
until the deadline.
Access with UTorID and password.
https://math.utsc.utoronto.ca/webwork2/STAB22H3/
Available to students in a few weeks. You will receive an email when it
is available.
Test and Exam
The midterm test and the final exam are based on multiple choice ques-
tions.
Allowed “cheat sheets”: 1 for midterm, 2 for final exam, but no other
books/notes. These sheets must be handwritten. You may use both sides
of the sheet(s).
You need a calculator for test, exam and quizzes.
Calculators
Hand calculators are cheap and useful. Any cheap one with a square root
and one memory button will do. Mean, standard deviation, sum, and sum of
squares keys may save you a bit of time on occasion, but we do not recom-
mend the purchase of expensive calculators to get keys with special statistical
calculations. Tests and exams will be designed so that those calculators give
no advantage. We emphasize the use of StatCrunch software for doing any
tedious or complex calculations. However, it is important to have a calculator
during tutorials/test/exam.
Missed Tests and quizzes
There are no make up tests or quizzes in this course. If the test is missed
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for a valid reason, you must submit appropriate documentation (e.g. UTSC
medical certificate) to the course instructor within one calendar week of the
missed test or quiz. UTSC medical certificate is available at http://www.
utsc.utoronto.ca/˜registrar/resources/pdf_general/UTSCmedicalcertificate.
pdf
Print on it your name, student number, course number, and date. If documen-
tation is not received in time, your test mark will be zero. If a test is missed
for a valid reason, its weight will be shifted to the final exam.
If a quiz is missed due to a valid reason and if the supporting documents are
provided on time, you will be excused from that quiz and your tutorial grade
will be calculated from the remaining quizzes only. If you are excused from a
quiz, we will indicate that by the code “-1” in place of your grade for that quiz
on Quercus.
Computing
Students will be using StatCrunch for computing. No previous computing ex-
perience is assumed. With this software, you will analyze the data sets posted
on Quercus or on the publisher’s web site.
Facilitated Study Groups
These weekly study sessions are open to everyone in the class.
Attendance is voluntary, but students who attend regularly often earn
higher grades.
Please be sure to fill out the survey in the first week of class to help ensure
the study groups are scheduled at optimal times.
If you have any questions, please ask your facilitator, visit the FSG web-
site at http://ctl.utsc.utoronto.ca/home/fsg, or email the FSG
Coordinator, Maggie Roberts at maggie.roberts@utoronto.ca.
Frequently asked questions
Currently living at:
https://q.utoronto.ca/courses/77480/pages/faq-page?module_
item_id=480674
Check before you ask your instructor.
Quercus
Course announcements, quiz marks etc. will be on Quercus.
You are responsible for keeping up with announcements posted on Quer-
cus by course instructors, course coordinator, etc
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Any problems with recording of marks should be brought to the atten-
tion of your TA (quizzes) or course instructor (test, exam). Contact your
instructor if you cannot resolve problems with your TA.
ACCESSABILITY STATEMENT
Students with diverse learning styles and needs are welcome in this course.
In particular, if you have a disability/health consideration that may require
accommodations, please feel free to approach me and/or the AccessAbility
Services Office as soon as possible. I will work with you and AccessAbility Ser-
vices to ensure you can achieve your learning goals in this course. Enquiries
are confidential. The UTSC AccessAbility Services staff (located in S302) are
available by appointment to assess specific needs, provide referrals and ar-
range appropriate accommodations (416) 287-7560 or ability@utsc.utoronto.ca.
ACADEMIC INTEGRITY STATEMENT
Academic integrity is essential to the pursuit of learning and scholarship in
a university, and to ensuring that a degree from the University of Toronto is a
strong signal of each student’s individual academic achievement. As a result,
the University treats cases of cheating and plagiarism very seriously. The Uni-
versity of Toronto’s Code of Behaviour on Academic Matters
(http://www.governingcouncil.utoronto.ca/policies/behaveac.
htm) outlines the behaviours that constitute academic dishonesty and the pro-
cesses for addressing academic offences. Potential offences include, but are
not limited to:
IN PAPERS AND ASSIGNMENTS: Using someone else’s ideas or words
without appropriate acknowledgement. Submitting your own work in more
than one course without the permission of the instructor. Making up sources
or facts. Obtaining or providing unauthorized assistance on any assignment.
ON TESTS AND EXAMS: Using or possessing unauthorized aids. Looking at
someone else’s answers during an exam or test. Misrepresenting your identity.
IN ACADEMIC WORK: Falsifying institutional documents or grades. Fal-
sifying or altering any documentation required by the University, including
(but not limited to) doctor’s notes. All suspected cases of academic dishon-
esty will be investigated following procedures outlined in the Code of Be-
haviour on Academic Matters. If you have questions or concerns about what
constitutes appropriate academic behaviour or appropriate research and ci-
tation methods, you are expected to seek out additional information on aca-
demic integrity from your instructor or from other institutional resources (see
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http://academicintegrity.utoronto.ca/).
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STAB22 - TENTATIVE LECTURE GUIDE
We cover chapters 1-20 of the textbook. A tentative schedule is given below:
Week 1:
1. Stats Starts Here
2. Displaying and Describing Categorical: One Categorical Variable, Two Categorical Vari-
ables, Three Categorical Variables
Week 2:
3. Displaying and Summarizing Quantitative Data: Displaying Quantitative Variables and
Describing the Distribution, Describing Quantitative Variables with Numbers
4. Understanding and Comparing Distributions
Week 3:
5. The Standard Deviation as a Ruler and the Normal Model: Standardizing, Density Curve
and the Normal Model, Normal Quantile Plots, The 68-95-99.7 rule
Week 4:
6. Scatterplots, Association, and Correlation
7. Linear Regression - Finding the Best Line
Week 5:
8. Regression Wisdom: Patterns on Residual Plots, Outliers, Leverage, and Influence, Cau-
tions
Week 6:
9. Sample surveys: Three keys of sampling, Sample Survey vs Census, Populations and Pa-
rameters, Samples and Statistics, Sampling Methods
Week 7:
10. Experiments and Observational Studies: Observational Studies, Experiments
Week 8:
11. From Randomness to Probability
12. Probability Rules
Week 9:
13. Random Variables
Week 10:
14. Sampling Distribution Models
15. Confidence Intervals for Proportions
16. Testing Hypotheses about Proportions
Weeks 11 and 12:
17. More about Tests
18. Tests and Confidence Intervals for the Population Mean
19. Comparing Two Means of Independent Samples
20. Comparing Two Means of Paired Samples
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