Syllabus

Public overview. This page describes what the course is about and how to use this site. It is not the official syllabus.

Course purpose

Introduction to Statistical Methods is a first course in reasoning with data. It is about the step between a number and the claim someone makes from it: where the number came from, what it stands in for, and how much weight it can carry.

By the end of the course, 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.

What this site provides

This public site is the course’s reading and review layer — a kind of open textbook. It holds the weekly notes and links to the open texts behind them. Everything here is readable by anyone, at any time, without signing in.

  • Notes — one page per week, and the main reading. Each page teaches a topic end to end, works through examples, names the misreading it is easiest to make, and closes with questions you can use to check yourself.
  • Schedule — the week-by-week topic map, showing the order ideas are built in and which note page goes with each week.
  • Resources — the open textbooks, tools, and reference material the notes draw on.

A good way to use it: read the week’s note page before the topic is covered, then return to it afterwards and work the self-check questions without looking back at the worked examples.

Tools

  • 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.

Where the official course lives

This site is a public reading layer and nothing more. The learning management system (LMS) and the official institutional syllabus are authoritative for everything about running the course, including:

  • section details and dates;
  • instructor and contact information;
  • assessment and grading;
  • submitted work and feedback;
  • course policies;
  • accommodations;
  • announcements.

Where this site and the official course materials ever differ, the official materials govern.