Embedded Files
Skills Checklist
Skills Checklist
After completing this chapter you should be able to successfully answer the following questions......
What are bivariate data?
What are explanatory and response variables?
What are two-way frequency tables and how do we interpret them?
How do we construct and interpret segmented bar charts from two-way frequency tables?
How do we construct and interpret parallel dot plots?
How do we construct and interpret back-to-back stem plots?
How do we construct and interpret parallel boxplots?
What is a scatterplot, how is it constructed and what does it tell us?
What do we mean when we describe the association between two numerical variables in terms of direction, form and strength?
What is the difference between observation and experimentation?
What is the difference between association and causation?
Chapter 2 Resources
Chapter 2 Resources
Chapter 2 - Part 1
Chapter 2 - Part 1
Chapter 2 - Part 2
Chapter 2 - Part 2
Chapter 2- Checklist
Chapter 2 -
Skills Checklist
Lesson Notes, Videos and Instructions
Lesson Notes, Videos and Instructions
Lesson 1 - Revision of Headstart Univariate Data
Bivariate Data – Classifying the Variables
Investigating Associations Between Categorical variables
Learning Intentions
To introduce bivariate data.
To be able to classify data as categorical or numerical.
To be able to identify explanatory and response variables.
To be able to summarise data from two categorical variables using two-way frequency
tables.
To be able to appropriately percentage two-way frequency tables.
To be able to use a percentaged two-way frequency table to identify and describe an
association between two categorical variables.
Warm up
Revision Powerpoint
Tasks
Complete the class revision task, going over chapter 1 content
Complete the worked solutions to the notes on Ch 2a
Complete Ex 2a
Resources
Ex 2a Video
Homework
Complete Ex 2a
Weeks 1 and 2 Homework Task
Due Date: Wednesday 8th February
2025 univariate head start refresher.pptxGen Maths 2a Video.MP4Ex 2a Video Explanation
Lesson 2 - Investigating the Association between a numerical and a categorical variable
Learning Intentions
To be able to use parallel dot plots to identify and describe the association between a numerical variable and a categorical variable for small data sets.
To be able to use back-to-back stem plots to display and describe the association between a numerical variable and a categorical variable for small data sets.
To be able to use parallel boxplots to display the association between a numerical variable and a categorical variable which can take two or more values.
Warm up
Tasks
Complete the worked solutions to the notes on Ch 2b and 2c
Complete Ex 2b and Ex 2c
Complete the targeted exam questions
Resources
Ex 2b Video
Ex 2c Video
Targeted Exam Question Solutions
Targeted Exam Question Solutions
Homework
Complete Ex 2c
RPReplay_Final1706598979.MP4Ex 2b Video Explanation
RPReplay_Final1706646144.MP4Ex 2c Video Explanation
Lesson 3 - Investigating associations between two numerical variables &
How to interpret a scatterplot
Learning Intentions
To be able to introduce the scatterplot for displaying data from two numerical
variables.
To be able to construct a scatterplot using a CAS calculator.
To be able to use a scatterplot to identify an association between two variables.
From the the scatterplot, be able to classify an association according to:
Direction, which may be positive or negative.
Form, which may be linear or non-linear.
Strength, which may be weak, moderate or strong.
Warm up
Tasks
Complete the worked solutions to the notes on Ch 2d and 2e
Complete worked solutions and notes on Ex 2d and 2e
Resources
Ex 2d Video
Ex 2e Video
Homework
Complete Ex 2d and Ex 2e
RPReplay_Final1706834607.MP4Ex 2d Video Explanation
RPReplay_Final1707014313.MP4Ex 2e Video Explanation
Lesson 4 - Strength of a linear relationship: the correlation coefficient
Learning Intentions
To introduce Pearson’s correlation coefficient r as a measure of the strength of a linear association between two variables.
To be able to use technology to determine the value of Pearson’s correlation
coefficient r.
To be able to classify the strength of a linear association as weak, moderate or strong
based on the value of Pearson’s correlation coefficient r.
Warm up
Tasks
Complete the worked solutions to the notes on Ch 2f
Complete worked solutions and notes on Ex 2f
Resources
Ex 2f Video
Homework
Complete Ex 2f
RPReplay_Final1707014887.MP4Ex 2f Video Explanation
Lesson 5 - The coefficcient of determination
Learning Intentions
To be able to calculate the value of the coefficient of determination.
To be able to use the coefficient of determination to assess the strength of the
association in terms of the explained variation.
Warm up
Tasks
Complete the worked solutions to the notes on Ex 2g
Complete worked solutions and notes on Ex 2g
Resources
Ex 2g Video
Homework
Complete Ex 2g
RPReplay_Final1707015574.MP4Ex 2g Video Explanation
Lesson 6 - Correlation and causality & Which graph?
Learning Intentions
To be able to define and differentiate the concepts of association and causation.
To determine which graph is appropriate to use when displaying different data
Warm up
Tasks
Complete the worked solutions to the notes on Ch 2h and 2i
Complete worked solutions and notes on Ex 2h and 2i
Complete the targeted exam question
Resources
Ex 2h Video
Ex 2i Video
Targeted Exam Question
Targeted Exam Question Solutions
Homework
Complete Ex 2h and 2i
RPReplay_Final1707016636.MP4Ex 2h Video Explanation
RPReplay_Final1707017133.MP4Ex 2i Video Explanation
Lesson 6 - Univariate Data Quiz
Learning Intentions
To allow students to complete a quiz based on exam questions in order for them to recieve feedback as to their understanding of chapter 1
Tasks
Topic Test
Part 1 - Multiple Choice
Part 2 - Short Answer
Homework
Chapter 2 Revision Questions
Edrolo revision tasks:
Progress check 1: https://edrolo.com.au/s/2679850/
Progress check 2: https://edrolo.com.au/s/2679851/
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