paco
Uploaded by
8 SLIDES
218 VUES
80LIKES

Understanding Curve Fitting with Linear Models in Algebra 2

DESCRIPTION

Welcome to Algebra 2! This section covers the essentials of curve fitting using linear models. Learn how to analyze the relationship between datasets through regression analysis, scatterplots, and correlation coefficients. We will guide you through the steps of fitting a line of best fit to your data using a graphing calculator. After identifying data points, you will input them into your calculator to derive and graph linear equations. Complete interactive assignments to apply your understanding of linear modeling in real-world examples, including predicting daily oil production.

1 / 8

Télécharger la présentation

Understanding Curve Fitting with Linear Models in Algebra 2

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript

Playing audio...

  1. Welcome to Algebra 2! • Get out your homework • Get out catalogs • Get out writing utensils • Put bags on the floor • Be quiet!!! 2-7: Curve Fitting with Linear Models

  2. Curve Fitting with Linear Models Section 2-7 2-7: Curve Fitting with Linear Models

  3. Definitions • Regression is the statistical study of the relationship between sets of data • Scatterplot is a graph that helps understand the form, direction, and strength of the relation; individual points • Correlation is the strength and direction of the linear relationship between two variables • Correlation Coefficient is the measure of how well the data set is fit by through a model; represented by r • -1 ≤ r ≤ 1 • Line of Best Fit is the line that best approximates a set of data 2-7: Curve Fitting with Linear Models

  4. Steps of Curve Fitting • Identify and list all of the data points • Put data into calculator – use STAT key • STAT  CALC  and select LinReg (ax + b) to get the equation 2-7: Curve Fitting with Linear Models

  5. Example 1 The table shows the U.S. daily oil production y (in thousands of barrels x years) after 1994. • Use the graphing calculator to find and graph the equation of the best-fitting line. • Use the equation from part (a) to predict the daily oil production in 2009. 2-7: Curve Fitting with Linear Models

  6. Your Turn Use the graphing calculator to find and graph the equation of the best-fitting line. 2-7: Curve Fitting with Linear Models

  7. Assignment A2-2 • P. 146: #1, 3, 5 + 9, 10, 11 2-7: Curve Fitting with Linear Models

  8. Assignment A2-4 A2-6 • P. 146: #1, 3, 5 2-7: Curve Fitting with Linear Models

More Related