Overview
Introduces descriptive and inferential statistics and data analysis strategies. Topics include experimental design, data visualization, probability, correlation/regression and analysis of variance. Online learning and weekly tutorials provide practice in computation, interpretation and communication of statistical findings, and large class sessions and individual drop in assistance ensure mastery. Applications appropriate to diverse fields of study will be explored.
Notes:
- STAM 200 is the introductory statistics course being offered online in place of STAT 263. STAM 200 does not require any Biology background, and covers the same content and is taught by the same professor as BIOL 243/3.0, GPHY 247/3.0, KNPE 251/3.0, NURS 323/3.0, POLS 385/3.0 and PSYC 202/3.0. It is also a substitution for STAT 263/3.0 in most Plans.
- On-campus students who wish to take STAM 200 Introduction to Statistics (online) as a core course in their Plan should check with their department's Undergraduate Chair first to ensure that this course will satisfy the department's requirement.
- When searching for STAM 200 in SOLUS, the "subject" needs to be "Statistics Multi Disciplines"
Learning Outcomes
After completing this course, students should have the knowledge and skills to do the following:
- Identify the study design for a given question, and define the accompanying statistical population, sample and observation unit.
- Distinguish descriptive statistics from inferential statistics, and define the role of each in quantitative analyses.
- Compute descriptive statistics for a dataset using contemporary software and create the appropriate visualizations.
- Identify and conduct the appropriate statistical test for a question and dataset using contemporary software
- Interpret the results of statistical tests and data software output to draw valid conclusions, and communicate them in written form.
- Apply knowledge of statistics and research design (e.g., sampling) to critically evaluate research findings.
Topics
Week 1 - Course Introduction
Week 2 - Anatomy of Statistical Study
Week 3 - Study Design and Sampling
Week 4 - Descriptive Statistics
Week 5 - Visualizations
Week 6 - Probability
Week 7 - Sampling Distribution
Week 8 - Hypothesis Testing: T-tests
Week 9 - Chi-square test
Week 10 - Linear Regression
Week 11 - Single-Factor ANOVA
Week 12 - Two-Factor ANOVA
Terms
Evaluation
14% - Weekly Quizzes (x12)
20% - Term Tests (x2)
12% - Software Skills Quizzes (x3) (Synchronous)
24% - Tutorial Activities (Synchronous)
30% - Unproctored Final Exam
**Evaluation Subject to change.**
Live Sessions/Synchronous Activities
This course has mandatory live sessions (e.g. webinars, synchronous activities) that include mandatory groupwork. To accommodate schedules, multiple sessions will be available to choose from, for each tutorial. Please consult the Timeline in the first week of class.
Final Exam
Students must write their exams on the day and time scheduled by the University. The start time may vary slightly depending on the off-campus exam centre. Do not schedule vacations, appointments, etc., during the exam period.
Textbook and Materials
There are two types of course materials (both required)
- The first is an ebook entitled "Taking the Anxiety out of Statistics" by Nelson & Beyer (Kendall Hunt Publishing). ¾ÅÐãÖ±²¥ students can purchase the textbook . Note that no royalties are collected on this ebook.
- Case-study videos and software guides will be available in onQ free of charge. The course uses Microsoft Excel and RStudio, both of which are free for students.
Time Commitment
Students can expect to spend, on average, about 10-12 hours per week completing relevant readings, assignments, and course activities.