Linear Regression

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.

Click here to visit the CSCS website

Demand for Computer Systems Analysts with big data expertise increased 89.9% in the last twelve months , and 85.40% for Computer and Information Research Scientists.
— 2014

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