Curated OER
Functions Made Easy
Students explore concept of functions as relationships, as machines, as equations, and as graphs.
Curated OER
Risky Business
Students view a video on AIDS, HIV and the ways in which HIV is spread. They discuss ways to avoid contracting HIV and participate in a simulation that shows the growth of a communicable disease.
Curated OER
Who Does the Lottery Benefit?
Students investigate the pros and cons of the lottery. For this algebra lesson, students use the formulas for permutation and combination to test their arguments about the lottery. They collect data about their argument and plot it on a...
Curated OER
The Kangaroo Conundrum: A Study of a Quadratic Function
Students play a game and collect data for their graph. In this algebra lesson, students solve quadratic equations and identify properties of their graph. They describe the pattern created by the graph and the game.
Curated OER
Coulomb's Law
Students solve problems involving electric charges and force. In this physics lesson, student solve word problems using addition and subtraction of vectors. They identify the direction represented by a vector as it relates to an electric...
Curated OER
A Functional Housing Market
Students access the Internet to search for housing prices in Houston, Texas,(the location can be changed to accommodate any location) and compare the prices to the number of square feet found in the living area of a house.
Curated OER
Building Paper Bridges
Learners construct a bridge that can hold 100 pennies. In this math lesson, students evaluate the strength of their bridges. They predict how much weight a bridge can hold based on its design.
Oswego City School District
Regents Exam Prep Center: Regression Analysis
A collection of lesson ideas, a practice activity, and teacher resources for exploring regression analysis.
Texas Instruments
Texas Instruments: Bacterial Growth and Regression
This activity gives students a set of data to perform a regression analysis. Students need to be able to read the data, perform a regression, and interpolate and extrapolate information.
Missouri State University
Missouri State University: Introductory Statistics: Linear Regression Models
Four examples which use the linear regression model in real-world applications. The site continues with discussion on how to correctly construct the regression model, how its results can be analyzed, and what can come from it.
University of Colorado
University of Colorado: Ph Et Interactive Simulations: Least Squares Regression
Create your own scatter plot or use real-world data and try to fit a line to it. Explore how individual data points affect the correlation coefficient and best-fit line.
Texas Education Agency
Texas Gateway: Tea Statistics: The Regression Equation
A tutorial on how to find the line of best fit or least-squares regression line for a set of data in a scatter plot using different methods and calculations.
Duke University
Duke University: Web Feats Ii: Lessons on Regression at Hessian
This site has several lessons on regression, "Designed to help students visualize topics associated with lines of regression, given a set of data points." Go to the teacher notes to find the objectives and standards which apply.
Texas Education Agency
Texas Gateway: Modeling Data With Linear Functions
Given a scatterplot where a linear function is the best fit, the student will interpret the slope and intercepts, determine an equation using two data points, identify the conditions under which the function is valid, and use the linear...
Khan Academy
Khan Academy: Linear Regression Review
Linear regression is a process of drawing a line through data in a scatter plot. The line summarizes the data, which is useful when making predictions.
Shodor Education Foundation
Shodor Interactivate: Regression
Plot a bivariate data set, determine the line of best fit for their data, and then check the accuracy of your line of best fit.
Other
Graph Pad: Data Analysis Resource Center
The GraphPad Statistics Guide is both a guide to doing statistical analyses with GraphPad Prism 7, and a concise review of statistical principles, emphasizing clear explanations with very little math. The GraphPad Curve Fitting Guide is...
Brown University
Brown University: Seeing Theory
This resource provides interactive visualizations of probability concepts. Covers basic probability, compound probability, probability distributions, frequentist inference, Bayesian inference, and regression analysis. The authors are...
National Council of Teachers of Mathematics
The Math Forum: Ask Dr. Math: Regression Method
This page goes over what regression method is and how a regression line fits in. Dr. MAth also suggests a book on regression if you are interested.
Texas Instruments
Texas Instruments: An Exploration of Direct Variation and Linear Regression
Students will use this activity for the following Algebra concepts: Review of Direct Variation; Properties of direct variations; Finding the constant of variations from data sets; Find missing values in data sets both numerically and...
Thinkport Education
Thinkport: Algebra Ii: Linear, Quadratic and Exponential Regression
Review linear regression and analyze how well this model fits the data. You will also be introduced to residuals and the correlation coefficient, and use these tools to determine whether or not a linear model is the best fit for a set of...
Texas Instruments
Texas Instruments: What Is a Linear Regression?
In this activity, students create lists of data points, plot them on a graph, and determine the regression equation of the best fitting line. They also understand exactly how the linear regression is determined.
Texas Instruments
Texas Instruments: Bivariate Data
This set contains statistics questions regarding bivariate data: scatter plots, the least-squares regression line, and their interpretation. The student is asked about the meaning of the various strengths and directions of linear...
Texas Instruments
Texas Instruments: Inference for Correlation and Regression
In this activity, students test if a significant relationship exists between a bivariate data set, and then calculate the confidence and predictive intervals. They also improve the interval-prediction capabilities by automating the process.