Created on: June 10, 2009

Website Address: https://library.curriki.org/oer/Topic-3--Linear-Regression

TABLE OF CONTENTS

- Waqar Test Resource
- Algebra
- Pre-Algebra
- Teaching linear equations through running a small business
- Algebra for Statistics Week 1 Lessons Plans and Activities
- intro to slope
- KS3 Mathematics: Algebraic Expression: Unit 1
- KS3 Mathematics: Algebra: Expanding Brackets
- KS3 Mathematics: Alegbra: Hot Cross Buns
- KS3 Mathematics: Algebra; Solving Equations
- Animated PowerPoint for Demonstrating How to Solve One Step Algebra Equations with Addition or Subtraction
- Algebra Games
- Conundra Math (FREE)
- Factor Race (Algebra)
- Algebra Champ (FREE)
- Algebra Genie (FREE)
- Equation Grapher from PhET
- Negative Exponents Worksheet - Customizable and Printable
- Balancing Equations Worksheet - Customizable
- Single Quadrant Graph Paper - Customizable and Printable
- Pythagorean Theorem Worksheet
- Metric Prefixes Flashcards - customizable and printable
- Conics
- MATH
- 3.1a PowerPoint
- MATH
- MATH
- Geometry Aligned to CCSS-M Standards

- Notes on pacing
- Topic 1: Introduction to Economics and to the Project
- Topic 2: Graphing 2-variable linear equations
- Topic 3: Linear Regression
- Topic 4: Solving systems of linear equations
- Topic 5: Running the business
- Topic 6: Evaluating and presenting results

In this sub-unit, students are introduced to the concept of linear regression and determining the equation of a function in 2-variables from data, using a linear model. They will develop and conduct a "market survey", in order to use the data to perform their own regression. There is a strong emphasis on the use of technology in this sub-unit.

In this lesson, students will identify key questions that they will need answers to in order to have the necessary information to plan their business. They will design an appropriate survey and administer this survey to other students at the school. Finally, they will compile the results into data sets in order to analyze them.

This lesson exposes students to the method of linear regression for determining the equation for a linear model of a data set. It progresses from a more intuitive understanding of the method to using technology to generate an equation using the least-squares method (students will not be exposed to the actual least squares method).