Course Instructor: Matt Haynes - haynes.matt@queensu.ca
In Summary:
Please note: This is a double-coded course with HSCI190/3.0
An introduction to the analysis of data from real life situations. Covers study design, descriptive and inferential statistics. Topics include probability, t-tests, regression, Chi-square tests, analysis of variance. Emphasis is in the foundation of statistical inference and practical application of statistical methods using statistical software.
Course Highlights: 
-
Emphasis will be placed on the foundation of statistical inference and practical application of statistical methods.
-
This is a blended course that will use adaptive learning programs, weekly lectures and labs.
-
Put theory into practice. An introduction to the analysis of data from real life situations and what reasonable inferences can be made from the data.
-
A broad introduction to statistics. Topics include probability, t-tests, regression, Chi-square tests and analysis of variance.
Course Information:
Statistics is a branch of mathematics that deals with collection, organization, analysis and interpretation of data. STAM200 students will be able to contextualize core concepts of this field of study by analysing data from real life situations and its implications - for example, we may look at voting statistics in the recent US election, or compare infection rates for different countries during the recent Covid19 pandemic.
This course introduces descriptive and inferential statistics and data analysis strategies. Topics include probability, correlation/regression, experimental design and analysis of variance. Online learning and weekly laboratories provide practice in computation, interpretation and communication of statistical findings, and large class review sessions and individual drop in assistance ensure mastery. Applications appropriate to different fields of study will be explored.
Learning Outcomes:
After completing this course, successful students should have the knowledge and skills to do the following:
- Identify the features of a data set to determine how best to summarize and display it.
- Choose the appropriate statistical test and provide the rationale for selection.
- Compute basic parametric and nonparametric statistical tests to test hypotheses.
- Interpret the results of statistical tests and data software output to be able to draw valid conclusions.
- Apply knowledge of statistics and research design (e.g., sampling) to critically evaluate research findings.
Prerequisites and Exclusions:
Prerequisite None. Exclusion BIOL243; CHEE209; COMM162; ECON250; GPHY247; HSCI190; KNPE251; NURS323; PHED251; POLS385; PSYC202; SOCY211; STAT263; STAT267; STAT367. One-Way Exclusion May not be taken with or after STAT269.
Course applicable to the following Majors/Medials/Minors:
BCHM (core) / BIMA (core) / BIOL (core) / BIPS (core) / BMCO (option) / BTEC (core) / COGS (option) / COMP (option) / CSCI (option) / EBIO (core) / ETOX (core) / HLTH (option) / PSYC (option) / SOCY (option) / SODE (option)
