'Polynomial regression models' presentation slideshows

Applications

Applications. The General Linear Model. Transformations. Transformations to Linearity. Many non-linear curves can be put into a linear form by appropriate transformations of the either the dependent variable Y or some (or all) of the independent variables X 1 , X 2 , ... , X p.

1.99k views • 154 slides

Detecting and reducing multicollinearity

Detecting and reducing multicollinearity. Detecting multicollinearity. Common methods of detection. Realized effects (changes in coefficients, changes in standard errors of coefficients, changes in sequential sums of squares) of multicollinearity.

701 views • 48 slides

Business Statistics: Communicating with Numbers By Sanjiv Jaggia and Alison Kelly

Business Statistics: Communicating with Numbers By Sanjiv Jaggia and Alison Kelly. Chapter 16 Learning Objectives (LOs). LO 16.1: Use and evaluate polynomial regression models. LO 16.2: Use and evaluate log-transformed models.

1.17k views • 38 slides

Polynomial regression models

812 views • 36 slides

CHAPTER 2

CHAPTER 2. FUNCTIONAL FORMS OF REGRESSION MODELS. LOG-LINEAR, DOUBLE LOG, OR CONSTANT ELASTICITY MODELS. The Cobb-Douglas Production Function: can be transformed into a linear model by taking natural logs of both sides: The slope coefficients can be interpreted as elasticities.

115 views • 11 slides

Introduction to Experimental and Observational Study Design

395 views • 8 slides