Spring 2023 - STAT 203 D100
Introduction to Statistics for the Social Sciences (3)
Class Number: 5821
Delivery Method: In Person
Course Times + Location:
Mo 10:30 AM – 12:20 PM
SSCB 9201, Burnaby
We 10:30 AM – 11:20 AM
AQ 3181, Burnaby
Exam Times + Location:
Apr 22, 2023
7:00 PM – 10:00 PM
SSCB 9200, Burnaby
Prerequisites:Recommended: 30 units including a research methods course such as SA 255, CRIM 220, POL 200W, or equivalent.
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.
This course covers Chapters 1-9, 11, 12, 15-22, and 24-27 of the textbook. The order of presentation is provided below. Students will produce calculations and graphics using R, which is a free software package.
- Descriptive Statistics (Chapters 1, 2 and 4): Includes construction and interpretation of basic graphical statistics (e.g. bar graphs, pie charts, histograms, time plots, scatterplots), as well as calculation and interpretation of basic numerical statistics (e.g. mean, median, mode, quartiles, standard deviation, correlation).
- Producing Data (Chapters 8 and 9): Introduces the concepts of sampling design and sampling procedures. The difference between experiments and observational studies is emphasized. Basic experimental designs are introduced, emphasizing the concepts of randomization, treatments, subjects, factors, pairing, and controls.
- Probability (Chapters 12, 3, and 15): Introduces some basic probability rules. Also introduces the concept of sampling distributions, with emphasis on the Normal distribution.
- Intro to Inference (Chapters 16, 17 and 18): Introduces the construction and interpretation of confidence intervals. Introduces the concepts of hypothesis testing, p-values, and statistical significance.
- Inference about Means (Chapters 20, 21, and 27): Practices the comparison of means to fixed values and comparisons among two or more means. The interpretation of the comparisons is emphasized.
- Inference about Proportions (Chapters 22 and 23): Practices the comparisons of proportions to fixed values and comparisons between two proportions. The interpretation of the comparisons is emphasized.
- Chi-square tests (Chapters 6+25): Includes the construction and use of contingency tables for two categorical variables. Procedures for testing for association between two categorical variables are discussed and practiced.
- Regression (Chapters 5+26): Construction of models using simple linear regression is introduced and practiced. The fit and interpretation of the resulting models is emphasized.
- Assignments 20%
- Midterm Exam 1 20%
- Midterm Exam 2 20%
- Final Exam 40%
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.r-project.org/, respectively.
REQUIRED READING NOTES:
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Department Undergraduate Notes:
Students with Disabilities:
Students requiring accommodations as a result of disability must contact the Centre for Accessible Learning 778-782-3112 or firstname.lastname@example.org.
Students looking for a tutor should visit https://www.sfu.ca/stat-actsci/all-students/other-resources/tutoring.html. We accept no responsibility for the consequences of any actions taken related to tutors.
ACADEMIC INTEGRITY: YOUR WORK, YOUR SUCCESS
SFU’s Academic Integrity website 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/s10-01.html