MTH1W Unit 7: Data and Modelling

How do we collect, represent and analyse data, and use models to answer real questions? Students examine big data in apps, schools, transit and the census, learn the four-step modelling cycle, analyse data with the mean, median, quartiles and box plots, compare data sets with a ruler-drop reaction test, create scatter plots, test linear and exponential models in Desmos or a spreadsheet, and judge predictions. Python code finds the five-number summary. The unit ends by planning a question of interest and building and judging a model. All data sets are original, and class data collection is optional and anonymous.

Assessment of learning: Box Plot Showdown, comparing two paper airplane designs with box plots and a regression model, with a rubric. A unit test with full solutions is also included.

Lessons

1. Big Data in Our Lives
2. What Is a Mathematical Model?
3. Centre and Spread
4. Quartiles and Box Plots
5. Comparing Data Sets
6. Scatter Plots and Correlation
7. Testing Regression Models
8. Coding with Data
9. Asking a Good Question
10. Building and Judging a Model

Plus a unit test class.

What you get

• A teacher lesson plan for every lesson: curriculum expectations, learning goals and success criteria, a timed sequence, differentiation, look-fors and worked answer keys
• Detailed slideshows (15 to 18 slides per lesson) with speaker notes on every slide: what to say, what to ask, what to look for and how long to spend, plus warm-ups, worked examples, guided practice, quick checks and answer-key slides
• Student handouts (usually two pages) and exit tickets, with every problem worked out in the answer key
• Editable Word and PowerPoint files, plus PDFs
• A unit overview, the summative task with a four-level Growing Success rubric, a unit test, and teacher solutions for both

Built for the 2021 Ontario Grade 9 Mathematics curriculum (MTH1W, de-streamed), and easy to adapt for any Grade 9 math class.