chapter12_notes3slides - Notes Introduction to Probability...

Info icon This preview shows pages 1–4. Sign up to view the full content.

View Full Document Right Arrow Icon
Introduction to Probability and Statistics II Instructor: John Snyder Office: Middlebush 35 Office hours: MW 8am - 9:30am Email: [email protected] 10 27 2015 John Snyder (MU) Stat —— 3500 — 10 27 2015 1 / 78 Multiple Linear Regression and Model Building 1 12.1 - Multiple Regression Models 2 12.2 - The First-Order Model 3 12.3 - Evaluating Overall Model Utility 4 12.4 - Using the Model for Estimation and Prediction 5 12.5 - Interaction Models 6 12.6 - Quadratic and Other Higher Order Models 7 12.7 - Qualitative (Dummy) Variable Models 8 12.8 Models w/ Quantitative and Qualitative Variables 9 12.9 Comparing Nested Models John Snyder (MU) Stat —— 3500 — 10 27 2015 2 / 78 12.1 - Multiple Regression Models Section 1 12.1 - Multiple Regression Models John Snyder (MU) Stat —— 3500 — 10 27 2015 3 / 78 Notes Notes Notes
Image of page 1

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
12.1 - Multiple Regression Models Introduction In chapter 11, we discussed simple linear regression: Introduced the straight-line regression model relating a response variable y to a predictor variable x .(section 1) Demonstrated how to estimate the parameters of the model using least squares estimation.(section 2) Explored how to test the significance of a relationship between x and y using hypothesis testing(section 4) Showed how to assess the adequacy of the model using R 2 and r .(section 5) Showed how to use the model to estimate E [ y ] and predict y for a given value of x .(section 6) John Snyder (MU) Stat —— 3500 — 10 27 2015 4 / 78 12.1 - Multiple Regression Models Multiple Linear Regression However, in most situations, simple linear regression isn’t very practical. For example, consider building a model to estimate home value. One might consider variables such as: Location. Square footage. Number of bathrooms. You can think of many more! Problems such as this motivate the need to relate multiple predictor variables to one response variable. John Snyder (MU) Stat —— 3500 — 10 27 2015 5 / 78 12.1 - Multiple Regression Models Multiple Linear Regression In this chapter, we will learn multiple regression model . Present several different multiple regression models involving both quantitative and qualitative predictor variables. Demonstrate how these models can describe many different relationships between variables. Assess how well the multiple regression model fits the sample data. John Snyder (MU) Stat —— 3500 — 10 27 2015 6 / 78 Notes Notes Notes
Image of page 2
12.1 - Multiple Regression Models Multiple Linear Regression The general form of the multiple regression model is: y = β 0 + β 1 x 1 + β 2 x 2 + . . . + β k x k + ε The value of the coefficient β i determines the contribution of the predictor variable x i . As before, β 0 is the y-intercept and ε is the random error term. John Snyder (MU) Stat —— 3500 — 10 27 2015 7 / 78 12.1 - Multiple Regression Models Multiple Linear Regression The x i variables can be the observed variables themselves or functions of the observed variables.
Image of page 3

Info icon This preview has intentionally blurred sections. Sign up to view the full version.

View Full Document Right Arrow Icon
Image of page 4
This is the end of the preview. Sign up to access the rest of the document.

{[ snackBarMessage ]}

What students are saying

  • Left Quote Icon

    As a current student on this bumpy collegiate pathway, I stumbled upon Course Hero, where I can find study resources for nearly all my courses, get online help from tutors 24/7, and even share my old projects, papers, and lecture notes with other students.

    Student Picture

    Kiran Temple University Fox School of Business ‘17, Course Hero Intern

  • Left Quote Icon

    I cannot even describe how much Course Hero helped me this summer. It’s truly become something I can always rely on and help me. In the end, I was not only able to survive summer classes, but I was able to thrive thanks to Course Hero.

    Student Picture

    Dana University of Pennsylvania ‘17, Course Hero Intern

  • Left Quote Icon

    The ability to access any university’s resources through Course Hero proved invaluable in my case. I was behind on Tulane coursework and actually used UCLA’s materials to help me move forward and get everything together on time.

    Student Picture

    Jill Tulane University ‘16, Course Hero Intern