Spring 2022  STAT 203 D100
Introduction to Statistics for the Social Sciences (3)
Class Number: 6697
Delivery Method: In Person
Overview

Course Times + Location:
Mo 10:30 AM – 12:20 PM
SSCC 9002, BurnabyWe 10:30 AM – 11:20 AM
WMC 3520, Burnaby 
Exam Times + Location:
Feb 16, 2022
7:00 PM – 10:00 PM
Location: TBAApr 26, 2022
3:30 PM – 6:30 PM
RCB IMAGTH, Burnaby

Instructor:
Gamage Perera
gperera@sfu.ca
Office: SCK 10557

Prerequisites:
Recommended: 30 units including a research methods course such as SA 255, CRIM 220, POL 200W, or equivalent.
Description
CALENDAR DESCRIPTION:
Descriptive and inferential statistics aimed at students in the social sciences. Scales of measurement. Descriptive statistics. Measures of association. Hypothesis tests and confidence intervals. Students in Sociology and Anthropology are expected to take SA 255 before this course. Intended to be particularly accessible to students who are not specializing in Statistics. Students cannot obtain credit for STAT 203 if they already have credit for  or are taking concurrently  STAT 101, 201, 205, 285, or any upper division STAT course. Quantitative.
COURSE DETAILS:
This course may be applied to the Certificate in Liberal Arts
STAT Workshop Coordinators: Marie Loughin/Harsha Perera
Outline:
This course covers Chapters 19, 11, 12, 1522, and 2427 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 20%
 Midterm Exam 1 20%
 Midterm Exam 2 20%
 Final Exam 40%
NOTES:
REQUIREMENTS:
Materials
MATERIALS + SUPPLIES:
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
Book is available through the SFU Bookstore
Department Undergraduate Notes:
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 SPRING 2022
Teaching at SFU in spring 2022 will involve primarily inperson instruction, with safety plans in place. Some courses will still be offered through remote methods, and if so, this will be clearly identified in the schedule of classes. You will also know at enrollment whether remote course components will be “live” (synchronous) or at your own pace (asynchronous).
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 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 spring 2022 term.