This preview shows pages 1–4. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.
View Full DocumentThis preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: STAT E50  Introduction to Statistics Exploring Relationships Between Variables Correlation examines the linear association between two quantitative variables, and the strength of that relationship: Is there a linear relationship between the variables? Is it positive or negative? How strong is it? Regression describes the linear relationship between the two variables, and makes it possible to predict the value of the response variable from the value of the explanatory variable: What is the relationship? What does the slope of this linear model tell us? When is it appropriate to use this linear model to make predictions? Page 3 The data shown below was published in Consumer Reports in January 1997. It includes information about seven kinds of pizza. The serving size for each is 5 oz. Pizza calories fat (g) cost ($) Pizza Hut's Hand Tossed 305 9 1.51 Domino's Deep Dish 382 16 1.53 Pizza Hut's Pan 338 14 1.51 Domino's Hand Tossed 327 9 1.90 Little Caesar's Pan! Pan! 309 10 1.23 Little Caesar's Pizza! Pizza! 313 11 1.28 Pizza Hut's Stuffed 349 13 1.23 1. Suppose you want to see if there is a relationship between calories and fat content. Which variable is the explanatory variable? the fat content Which variable is the response variable? the number of calories. 2. Draw a scatter diagram for this data. 390 380 370 calories 360 350 340 330...
View Full
Document
 Spring '08
 WEINSTEIN
 Statistics, Correlation

Click to edit the document details