Syllabus

Public version. This page is the public-facing overview of MATH 21003 — Introduction to Statistical Methods, Fall 2026. The official syllabus — with section numbers, exact dates, grading rules, accommodations, and full university policies — lives in Blackboard.

Course purpose

Introduction to Statistical Methods is a first course in reasoning with data. By the end of the term, you should be able to:

  • read data — name the cases and variables, and say honestly what a dataset can and cannot tell you;
  • evaluate evidence — recognize the study design behind a number and what claims it does (and does not) license;
  • understand uncertainty — interpret variability, intervals, and p-values as strength of evidence rather than verdicts;
  • make responsible statistical claims — state a conclusion that matches its evidence and names its limits.

How this site fits

This public site is the course’s reading and review layer — a kind of open textbook. It holds the weekly notes, public exit tickets, and links to the open texts behind the course.

Blackboard is the official course system. Announcements, due dates, quizzes, homework, project submissions, grades, and the full policy details all live there. When the two ever disagree, Blackboard is authoritative.

Weekly rhythm

Each week follows a steady three-day pattern:

  • Monday — concept and reading: the week’s main idea, with the weekly notes as the anchor.
  • Wednesday — application and exit ticket: a short, hands-on check that puts the idea to work.
  • Friday — quiz, accountability, and synthesis: pulling the week together, handled through Blackboard or in class as directed.

Tools

  • Course notes — the weekly note pages on this site.
  • Introduction to Modern Statistics (IMS) — the main open textbook and source spine.
  • Introductory Statistics for the Life and Biomedical Sciences (ISLBS) — a supplement for biomedical and life-science contexts.
  • StatKey or simulation applets — used conceptually, to see sampling variability and inference.
  • A basic calculator — as needed.

No R and no coding are required for this course. The public pages do not post private assessments or answer keys.

Assessment (public overview)

Your grade is built from a mix of the following; the exact weights, point values, and due dates are in Blackboard:

  • exit tickets / participation — short weekly checks;
  • quizzes — regular accountability;
  • homework — applied practice;
  • a project or applied work — putting the course’s habits together;
  • a final review and final assessment — cumulative synthesis.

For the official grading breakdown, late-work rule, accommodations, and academic-integrity and AI-use policies, see Blackboard.