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Correlation All-Star -- Sports Data Analysis - 21st Century Math Project

Rated 4.85 out of 5, based on 77 reviews
4.9 (77 ratings)
;
Clark Creative Math
17.4k Followers
Grade Levels
7th - 12th, Homeschool
Resource Type
Standards
Formats Included
  • Zip
  • Google Apps™
Pages
42 pages
$6.00
$6.00
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Clark Creative Math
17.4k Followers
Includes Google Apps™
The Teacher-Author indicated this resource includes assets from Google Workspace (e.g. docs, slides, etc.).

What educators are saying

This was a great resource for a project based math class. I love how detailed your projects are - the students are really engaged! Thank you!
I loved this way of getting my students engaged with correlation in a way that is exciting to them. I love using real life data in class when possible, but it can be hard to find data and utilize it in a way that is effective. This project is well designed and easy to use!
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  2. This is a selection of my Correlations & Advanced Stats resources all in a money saving Essential Bundle! You save significant money and time versus purchasing these separately!Essential Bundles are designed to give you everything you need to rock your unit. Warmups, Notes, Activities, Games, Ex
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  3. 12 of my best selling projects/units all in an organized money saving bundle! These engaging, student/teacher approved math projects that provide rigor, relevance, and cross-curricular content altogether. Check out the preview to see the alignment to the Common Core Standards! I have each of these p
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Description

Bring an authentic sports-based math project to your Algebra, Algebra 2 or PreCalculus classroom with Lines of Best Fit and Correlations! All in this 21st Century Math Project! Using data from the MLB, NBA, NFL and NHL students investigate correlations to some of sports most common questions like:

"Do more shots result in more goals?"

"Do hitters or pitchers have more impact on a team's wins?"

"What NFL stat is most strongly correlated with wins?"

and the grand-daddy...

"Can money buy championships?"

While students may dive into their favorite sport, they will be practicing rigorous topics Line of Best Fit (with slope and intercept) and correlation coefficients. TI-Graphing Calculator or Computer Lab with Excel required!

**NOTE -- this item now includes two version, one with older data, one with new. You have studnents see if there's been a change between the two version if you'd like**

In this product you will receive a 42 page PDF which includes:

3 different assignments, 1 project, graphs many data tables and an answer key. ***THIS PRODUCT HAS BEEN UPDATED WITH A GOOGLE SLIDES INTERACTIVE VERSION INCLUDED. REDOWNLOAD IF YOU HAVE IT ALREADY***

- In “He Shoots, He Scores!!!” students will construct scatterplots and draw lines of best fit. While using NHL shot and goal data.

- In “Offense or Defense” students will use TI Graphing Calculates to create scatterplots and determine lines of best fit and correlation coefficients using Runs Scored and Runs Allowed MLB data.

- In “Gridiron Challenge” students will look at NFL data to determine which statistics has the strongest correlation with winning.

-- AND FINALLY in “Can Money Buy Championships?” students will look at data from the four major American sports leagues to answer this inquiry question.

You may be interested in the following discounted bundles. SAVE $$$!

Correlations & Advanced Stats

21st Century Math Projects -- All the Projects

Algebra 2 - Pre-Calculus Projects Starter Bundle

Need an Entire Curriculum?

21st Century Algebra 2 / Pre-Calculus –- the Entire Curriculum

For more tips, tricks and ideas check out the Clark Creative Education Blog

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Total Pages
42 pages
Answer Key
Included
Teaching Duration
4 days
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Standards

to see state-specific standards (only available in the US).
Construct and interpret scatter plots for bivariate measurement data to investigate patterns of association between two quantities. Describe patterns such as clustering, outliers, positive or negative association, linear association, and nonlinear association.
Know that straight lines are widely used to model relationships between two quantitative variables. For scatter plots that suggest a linear association, informally fit a straight line, and informally assess the model fit by judging the closeness of the data points to the line.
Use the equation of a linear model to solve problems in the context of bivariate measurement data, interpreting the slope and intercept. For example, in a linear model for a biology experiment, interpret a slope of 1.5 cm/hr as meaning that an additional hour of sunlight each day is associated with an additional 1.5 cm in mature plant height.
Write a function that describes a relationship between two quantities.
Represent data on two quantitative variables on a scatter plot, and describe how the variables are related.

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