I am fortunate to have access to many resources, but in teaching in public schools for three years, I still believe that much of what I do now can be done in many schools.
a. Know your audience
a. Know your audience
b. How I started teaching MDM4U
a. Know your audience
b. How I started teaching MDM4U
a. Know your audience
b. How I started teaching MDM4U
a. Order of Units
a. Know your audience
b. How I started teaching MDM4U
a. Order of Units
b. Context with Books/Media/Podcasts
a. Know your audience
b. How I started teaching MDM4U
a. Order of Units
b. Context with Books/Media/Podcasts
c. Spiral Topics
a. Know your audience
b. How I started teaching MDM4U
a. Order of Units
b. Context with Books/Media/Podcasts
c. Spiral Topics
d. Tech/Visualization/(coding?)
a. Know your audience
b. How I started teaching MDM4U
a. Order of Units
b. Context with Books/Media/Podcasts
c. Spiral Topics
d. Tech/Visualization/(coding?)
e. Assessing with projects
“I need a grade 12 math”
“Calculus and Advanced Functions are too hard”
“I need a grade 12 math”
“Calculus and Advanced Functions are too hard”
“I’m not a math person”
“I need a grade 12 math”
“Calculus and Advanced Functions are too hard”
“I’m not a math person”
“I don’t need math…”
“I need a grade 12 math”
“Calculus and Advanced Functions are too hard”
“I’m not a math person”
“I don’t need math…”
“Guidance said this is the math class for me”
Those who...
Those who...
...can't teach calculus?
Student's were calculating the standard deviation by hand
Using a TI-83+ was considered tech
We rarely discussed data in the wild
Student's were calculating the standard deviation by hand
Using a TI-83+ was considered tech
We rarely discussed data in the wild
We are using software to perform calculations and visualization
We spend most of our time interpreting statistical outputs
and telling stories with data visualization
Always revisiting one/two variable data and looking ahead and behind
Always revisiting one/two variable data and looking ahead and behind
Data Visualization with meaningful data
Low floor; High ceiling
Always revisiting one/two variable data and looking ahead and behind
Data Visualization with meaningful data
Low floor; High ceiling
Recording class lessons
Student discussions
Always revisiting one/two variable data and looking ahead and behind
Data Visualization with meaningful data
Low floor; High ceiling
Recording class lessons
Student discussions
Free-Response Questions that will connect several course topics
Model answers and rubrics available for students
Chapter 2: Probability
Chapter 2: Probability
The Creator of Gapminder
Data is available to reproduce these plots and Hans Rosling shares with us the stories these data tell
The book describes decision making in baseball and outlines expected run probability and decision-making.
The book describes decision making in baseball and outlines expected run probability and decision-making.
What Can Uber Teach us About the Gender Pay Gap?
Study Design Principles
Exploring the Gender Pay Gap
"Explained Variance" and Modelling
Other podcasts exploring, research, statistics, economics, and social science:
The Most Diverse Cities are Often the Most Segregated (fivethirtyeight.com)
The Most Diverse Cities are Often the Most Segregated (fivethirtyeight.com)
The Most Diverse Cities are Often the Most Segregated (fivethirtyeight.com)
Let's understand a scatterplot
Let's look at a regression model
Let's discuss the meaning of an index
Let's discuss multivariate thinking
Let's discuss how statistics, data, modelling play a role in society and policy
This activity involves the following Ministry Expectations and can be used to connect these topics throughout the academic year:
A1.1, A1.3, A1.4, A2.2,
B1.1, B1.2, B1.3, B1.4, B1.7, B2.2, B2.6, B2.8,
C1.1, C1.2, C2.1, C2.4,
D1.2, D1.3, D1.4
Other Examples of Simulations include:
Brown University - Seeing Theory
This applet contains interactive visuals and an e-textbook that describes worked solutions.
I find this especially helpful for Venn diagrams and permutations/combinations.
Outstanding array of applets for every course topic. The visualizations are helpful for students to see simulations and sampling distributions and probabilities, and the apps include data.
Outstanding array of applets for every course topic. The visualizations are helpful for students to see simulations and sampling distributions and probabilities, and the apps include data.
These applets are slick and offer a look at visualizing specific features of statistics and inference and distributions.
Allan Rossman, the inspiring former chief reader of the AP Statistics Program, encourages teachers to "ask good questions" for student learning. His blog is insightful, friendly, and encouraging to all. I have done several of his activities in my class.
Allan Rossman, the inspiring former chief reader of the AP Statistics Program, encourages teachers to "ask good questions" for student learning. His blog is insightful, friendly, and encouraging to all. I have done several of his activities in my class.
This page offers all of the previous AP Free-Response Questions and Solution Rubrics.
I sometimes have students watch segments of David Robinson analyze TidyTuesday Data and explore some of it on their own.
I use the textbook OpenIntro Statistics for class and do several examples in my own RStudio during class to demonstrate Exploratory Data Analysis.
There are several resources offered through the RStudio Education Website using Rstudio cloud and the resources at R for the Rest of Us are helpful for further investigation.
Anything from Dr. Mine Çetinkaya-Rundel although she focuses on introductory college-level instruction.
The Stats Medic and Skew the Script are free and offer lesson templates and plans to follow including discussion topics.
Amy Hogan's blog on teaching statistics has several tips from an experienced statistics teacher.
The AP Statistics YouTube Playlist offers video instruction of some key topics in the AP-Statistics Curriculum.
The New York Times Learning Network features What's Going On in This Graph? which features a graph and provides lesson and discussion forums for its interpretation.
The ASA produced a Guidelines for Assessment and Instruction in Statistics Education II: A Framework for Statistics and Data Science Education report (GAISE II).
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