STAT20059: Statistics
Explore the fundamentals of statistics — from descriptive statistics and probability to inference and data analysis.
Introduction to Statistics
Week 1
Welcome to STAT20059! This week we'll explore the fundamentals of statistics, including key concepts and foundational methods.
Lecture Slides
Introduction to Statistics — key concepts, descriptive statistics, and foundational methods.
View SlidesPresenting Data
Week 2
This week focuses on presenting data effectively using statistical tables, charts, and visual interpretation techniques.
Lecture Slides
Week 2 lecture on presenting data, chart selection, and visual interpretation.
View SlidesDescribing Data
Week 3
This week introduces descriptive statistics for numerical data, including measures of center, spread, and distribution shape.
Lecture Slides
Week 3 lecture on summarising data with mean, median, mode, range, variance, and standard deviation.
View SlidesTutorial Work
Week 3 tutorial exercises and practice questions for descriptive statistics.
View TutorialWeek 4
Week 4
Week 4 lecture materials are now available below.
Probability Distributions
Week 5
This week introduces probability distributions for discrete random variables: probability mass functions, expected value, variance, covariance, and the binomial model—with knowledge checks along the way.
Lecture Slides
Week 5 lecture on discrete random variables, binomial probabilities, and related concepts (slides also reference Weeks 5 & 6).
View SlidesWeek 6
Coming soon
Content for Week 6 will be available soon.
Week 7
Week 7
Week 7 lecture materials are now available below.
Week 8
Coming soon
Content for Week 8 will be available soon.
Week 9
Week 9
Week 9 lecture and tutorial materials are now available below.
Week 10
Week 10
Week 10 lecture and quiz materials are now available below.
Simple Linear Regression
Week 11
Week 11 covers simple linear regression — the regression equation, coefficient interpretation, R², and residual analysis. Use the lecture slides for theory and the Excel activity for hands-on practice.
Lecture Slides
Regression model, least-squares estimation, interpreting slope and intercept, goodness of fit, and residual diagnostics.
View SlidesExcel Activity
Step-by-step Excel tutorial — trendlines, SLOPE and INTERCEPT functions, R², and residual plots.
View TutorialWeek 12
Coming soon
Content for Week 12 will be available soon.