Summer 2022  STAT 201 D100
Statistics for the Life Sciences (3)
Class Number: 4688
Delivery Method: In Person
Overview

Course Times + Location:
Mo 10:30 AM – 12:20 PM
RCB IMAGTH, BurnabyWe 10:30 AM – 11:20 AM
RCB IMAGTH, Burnaby 
Exam Times + Location:
Jun 6, 2022
7:00 PM – 8:20 PM
Location: TBAJul 11, 2022
7:00 PM – 8:20 PM
Location: TBAAug 15, 2022
7:00 PM – 10:00 PM
AQ 3005, BurnabyAug 15, 2022
7:00 PM – 10:00 PM
SSCC 9001, Burnaby

Instructor:
Sonja Isberg
sonja_isberg@sfu.ca
1 778 7824630
Office: SCP9323

Prerequisites:
Recommended: 30 units.
Description
CALENDAR DESCRIPTION:
Research methodology and associated statistical analysis techniques for students with training in the life sciences. Intended to be particularly accessible to students who are not specializing in Statistics. Students cannot obtain credit for STAT 201 if they already have credit for  or are taking concurrently  STAT 101, 203, 205, 285, or any upper division STAT course. Quantitative.
COURSE DETAILS:
This course may be applied to the Certificate in Liberal Arts
STAT Workshop Coordinator: Harsha Perera
Outline:
Aimed at a non mathematical audience, this course discusses procedures that are most commonly used in the summary of statistical surveys and in the interpretation of experimental data. This course covers Chapters 027 (excluding Chapters 13 and 23) of the textbook. Chapters 7, 11, 19, and 24 are section reviews (and thus are optional). Details of the other chapters are as follows:
 Descriptive Statistics (Chapters 1, 2, and 4 of text) Basic graphical statistics (e.g. bar graphs, pie charts, histograms, time plots, scatterplots) and basic numerical statistics (e.g. mean, median, mode, quartiles, standard deviation, correlation) are discussed. Scales of measurement are distinguished (e.g. nominal, ordinal, ratio and interval).
 Probability (Chapters 3 and 12 of text) The normal distribution is introduced along with probability rules.
 Sampling (Chapter 8 of text) Various sampling designs such as simple random sampling are discussed. The implementation of sampling procedures is also presented.
 Experiments and Observational Studies (Chapters 8 and 9 of text) The design of experiments is introduced with an emphasis on randomization, treatments, subjects, factors, pairing and controls. Comparisons are made with observational studies.
 Inference (Chapters 15, 16, 17, 18) Concepts related to the construction of confidence intervals (e.g. sampling distributions, confidence level, width, interpretation, the effect of sample size) are discussed. Also basic concepts related to the testing of hypotheses (e.g. hypotheses, pvalues, statistical significance) are presented.
 Estimation and Testing for One Sample Problems (Chapters 20 and 22 of text) Procedures for means and proportions are discussed with an emphasis on the use of statistical software and the interpretation of results.
 Estimation and Testing for Two Sample Problems (Chapters 21 and 23 of text) Procedures for means and proportions are discussed with an emphasis on the use of statistical software and the interpretation of results.
 One Way ANOVA (Chapter 27 of text) One way analysis of variance procedures are discussed with an emphasis on implementation using statistical software and the interpretation of results.
 ChiSquare Tests (Chapters 6 and 25 of text) Procedures for testing in contingency tables are discussed with an emphasis on the use of statistical software and the interpretation of results. Measures of association are discussed.
 Regression (Chapter 5 and 26 of text) Simple linear regression is introduced with an emphasis on carrying out regression on actual data using statistical software and the interpretation of results. Related concepts including residuals, least squares fit, testing and the construction of confidence intervals is addressed.
Grading
 Assignments/Quizzes 25%
 Midterm 1  June 6th, 19:0020:20  B9201 & C9001 20%
 Midterm 2  July 11th, 19:0020:20  B9201 & C9001 20%
 Final Comprehensive Exam 35%
NOTES:
Above grading is subject to change.
There will be no makeup midterms.
Materials
MATERIALS + SUPPLIES:
iClickers will be used during this course
R can be accessed via Jupyter, an online platform, at https://sfu.syzygy.ca/. Alternatively, R Studio and R statistical software can be
downloaded free of charge from https://www.rstudio.com/ and https://cran.rproject.org/, respectively.
REQUIRED READING:
Required Textbook:
The Basic Practice of Statistics (9th ed.) by D. S. Moore, W. I. Notz, and M. A. Fligner. Publisher: W.H. Freeman Publishers
Looseleaf ISBN: 9781319344634 (available at SFU Bookstore)
Other options are available through the MacMillan Learning website.
ISBN: 9781319344634
Department Undergraduate Notes:
Students with Disabilities:
Students requiring accommodations as a result of disability must contact the Centre for Accessible Learning 7787823112 or caladmin@sfu.ca.
Tutor Requests:
Students looking for a tutor should visit https://www.sfu.ca/statactsci/allstudents/otherresources/tutoring.html. We accept no responsibility for the consequences of any actions taken related to tutors.
Registrar Notes:
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
SFU’s Academic Integrity web site http://www.sfu.ca/students/academicintegrity.html is filled with information on what is meant by academic dishonesty, where you can find resources to help with your studies and the consequences of cheating. Check out the site for more information and videos that help explain the issues in plain English.
Each student is responsible for his or her conduct as it affects the University community. Academic dishonesty, in whatever form, is ultimately destructive of the values of the University. Furthermore, it is unfair and discouraging to the majority of students who pursue their studies honestly. Scholarly integrity is required of all members of the University. http://www.sfu.ca/policies/gazette/student/s1001.html
TEACHING AT SFU IN SUMMER 2022
Teaching at SFU in summer 2022 will involve primarily inperson instruction. Some courses may be offered through alternative methods (remote, online, blended), and if so, this will be clearly identified in the schedule of classes.
Enrolling in a course acknowledges that you are able to attend in whatever format is required. You should not enroll in a course that is inperson if you are not able to return to campus, and should be aware that remote, online, or blended courses study may entail different modes of learning, interaction with your instructor, and ways of getting feedback on your work than may be the case for inperson classes.
Students with hidden or visible disabilities who may need class or exam accommodations, including in the context of remote learning, are advised to register with the SFU Centre for Accessible Learning (caladmin@sfu.ca or 7787823112) as early as possible in order to prepare for the summer 2022 term.