ENGR132_Class7A_Amanda_Knutson

ENGR132_Class7A_Amanda_Knutson - Welcome to ENGR132 Linear...

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Click to edit Master subtitle style ENGR132 Linear Regression Prof. Amanda Knutson and GTA Ben Ahn Class 7a – Textbook pp. 378 Welcome to

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4/24/11 Milestone 4 Feedback Make sure you read the rubrics online – they have been posted since the first week of class Read the comments carefully – if we have suggested that your project is too simple, you need to increase your complexity so that you can use all the required programming structures – come and see me to discuss any issues here 22
4/24/11 At the end of this topic, you will begin to be able to: State why we do regression Manually produce the equation of a regression line Define, calculate, and explain the use of SSE sum of the squares of errors SST sum of the squares of deviations r2 coefficient of determination Learning Objectives 33

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4/24/11 Regression analysis is a method of creating a model of a system When using regression, we assume that one variable is a function of another Cause-and-Effect Distance is a function of launch angle Reaction rate is a function of temperature Changes over Time (temporal changes) Coffee (in cup) temperature is function of time Gross Domestic Product (GDP) is a function of time Spatial Profile The number of pedestrians crossing the street is a function of location along the street What is regression analysis? Why do we use it? 44
4/24/11 Verbally : describe the relationship Numerically : tabulate the data Visually : show us a graph Symbolically : use an equation as a model We’ll focus on the last two: Visually: Fit a “best” regression line to graphed data Symbolically: Find the “best” regression line Four Ways to Represent a 55

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4/24/11 Paired (x,y) data sets We’ve measured both X and Y We think that Y may depend on X So first we plot the data A regression is a method of creating a model of a system X Y How can we model this data? 66
4/24/11 With linear regression, a line is created that is a model of the data Can describe the data Can be used for prediction (best used in data range) Linear Regression X Y 77

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4/24/11 Linear regression describes the relationship between the two variables ( x and y ) as a line . y
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This note was uploaded on 04/23/2011 for the course ENGR 132 taught by Professor Kutson during the Spring '11 term at Purdue.

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ENGR132_Class7A_Amanda_Knutson - Welcome to ENGR132 Linear...

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