Statistics Project

Since California officially adopted Common Core standards this year, it was time to teach the new statistics standards. I’m very glad statistics was finally included in all grades. These standards are the closest to real life math we could do and I am surprised how quickly my students picked up the skills and transferred them to other problems.

The project I created has students using the US Census data for San Francisco to look at two variables to see if there is a correlation or not. Students would collect the data, find the line of best fit and explain the slope and y-intercept in the context of the problem. Students then created a poster about their findings to display to their peers.

Here’s some sample posters and data plotted on Desmos.





Directions and Resources

  • Pick two variables to look for a correlation
  • Collect data for these variables from the 25 zip codes
  • Plot the data on Desmos and find the line of best fit
  • Answer discussion questions about the slope, y-intercept, and your evaluation of the strength of the line of best fit.
  • Make a poster showing your findings

Project Packet Download Link

What I like…

I loved how much student choice there was in this project. Students were allowed to pick any two variables. Many picked a specific percentage of race (latino, black, asian, white) and looked at education, income, and home ownership to see if there was any correlation.

What was also nice was for students to see how there are vast differences in San Francisco zip codes. Some had median household incomes in the 6 figures, while others were well below the poverty line. Students saw this data and it became more real to them, not just something a teacher said or they read in a newspaper.

This was also the 4th large project of the school year. Students really took this project seriously. While a number of students procrastinated and didn’t finish in time, many students who struggled in the beginning of the year have become better at planning their time and getting the project done before the deadline.

What I don’t like and want to change…

I didn’t cover correlation enough before the project and wish I had so their arguments could be stronger. When teaching this again, I would discuss in further detail about the strength and direction of the line with respect to the r-coefficient and line of best fit.

I also would have some more support for students with IEPs. While I helped those students choose variables that were easier to see a correlation, some of the discussion questions were a challenge and would prefer to have a modified version of the packet for these students.

Final thoughts…

This is one of my favorite projects I’ve taught for many reasons. Students were more engaged in this work because the project was open ended and the data was real. Hope you find this project useful and engaging with your students!

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