Computer Supported Collaborative Learning (CSCL) is an effort by California State University, Northridge to support science teachers in the San Fernando Valley. The concepts being developed by CSUN can be applied to all subject matter at all grade levels.

Data collection and analysis is a growing industry. Being able to pull ideas out of big data is what drives many of the newest and most successful technology companies.

Go through the steps below to collect, view, and analyze data about height and shoe size. Linear regression is one way that data can be analyzed to find patterns/relationships between two sets of data.

- Data Collection
- Complete the Google Form to add your data to our assignment
- Height vs Shoe Size Form

- View Data
- Google Sheet
- Make sure you copy this data to use in the next step

- Calculator
- desmos.com/calculator
- Follow the Regression Tutorial to find how to type a linear regression into the calculator
- Find the best linear graph that fits the data

- Analysis
- What can this line tell us about the relationship between the data?
- In regression, the R2 coefficient of determination is a statistical measure of how well the regression line approximates the real data points. An R2 of 1 indicates that the regression line perfectly fits the data.
**Use your linear equation to predict what height someone would be if they had a size 15 shoe.**

Linear regression lines can be used to help predict future results. The linear equation models what is happening in the real world. The better your R2 value, the better your equation will model the real world situation.