Dec. 11, 2020

Barbara Costelloe

study design

ages 15 - 18 years

In this lesson students experience an experiment first-hand. Students then reflect on experimental design principles in evaluating the experiment. The experiment is conducted as a comparison of two independent groups.

Aug. 31, 2020

Emma Lehrke

randomisation tests

undergraduate level

This lesson can be taught in two sessions to Year 13 statistics students or in one or two lectures to stage one statistics students. The lesson introduces four key ideas that underpin the randomisation test: the meaning of unusualness; chance acting alone behaviour; the omnipresence of chance; and evidence and argumentation. Students participate throughout the lesson with a mixture of hands-on and online interactions.

July 24, 2020

Dr Rhys C Jones

study design

undergraduate level

This lesson plan provides guidance and advice on how to integrate video clips into lectures to help facilitate the development of statistical thinking in students. Although the lesson can be applied in multiple ways, it looks specifically at nurturing students’ skills in developing good research questions applicable to a statistical investigation.

Feb. 3, 2020

Dr Marie Fitch

probability

undergraduate level

A person has been randomly chosen to be tested for diabetes and tests positive. What is the probability they actually have diabetes? Students use the Pachinkogram visual tool to explore this scenario and investigate what happens when the given probabilities change. Rather than introducing Bayes’ theorem using formulae, this lesson aims to give students an intuitive understanding of the nature and effect of given and resultant probabilities.

Sept. 25, 2019

Dr Michelle Dalrymple

informal hypothesis testing

ages 15 - 18 years

ages 11 - 14 years

In this activity, students explore the actual and expected outcomes of a six-sided “wonky” dice. Students use what they have learned about sampling variation to decide if there is any reason to think their wonky dice might not be fair.

Sept. 25, 2019

Mark Hooper

confidence intervals

ages 15 - 18 years

The lessons introduce the concept of resampling through bootstrapping, leading to the formation of a confidence interval of the difference between two means or two medians. The students experience sampling variation and bootstrapping visually through the aid of technology and manually through a physical exercise involving data cards of a sample from a very large population. A confidence interval of the difference between two population parameters is formed and interpreted. Lastly the experience using technology is formalised.

Sept. 25, 2019

Dr Pip Arnold

multivariate data investigation

ages 7 - 10 years

This lesson introduces multivariate whole number data cards for year 3-6 students through the context of pets. The use of the data cards is designed to move students away from collecting single variable data in tables with tally marks to collecting multivariate data to allow for a wider view of their investigative question. The data cards encourage multiple displays of the data as the students notice patterns in the data. This lesson allows students to engage in the entire PPDAC cycle.

Sept. 25, 2019

Dr Sashi Sharma

probability

ages 11 - 14 years

Learning about probability poses difficulties for students at all levels. In this lesson students are asked to make predictions about the fairness of a dice difference game and then test them by gathering and examining data. Student predictions and conclusions are examined and re-examined in interactions among small group members and whole class or group and teacher. This lesson also addresses some common misconceptions relating to probability of simple and compound events.

- articles (8)
- ages 11 - 14 years (2)
- ages 15 - 18 years (3)
- ages 7 - 10 years (1)
- confidence intervals (1)
- informal hypothesis testing (1)
- multivariate data investigation (1)
- probability (2)
- randomisation tests (1)
- study design (2)
- undergraduate level (3)

Peer reviewed lesson plans for teaching statistics and data science