CHAPTER 15 Simple linear regression and correlation to accompany Introduction to business statistics fourth edition by ronald M. Weiers Presentation by Priscilla Chaffe-Stengel Donald n tenge o 2002 The Wadsworth Group
CHAPTER 15 Simple Linear Regression and Correlation to accompany Introduction to Business Statistics fourth edition, by Ronald M. Weiers Presentation by Priscilla Chaffe-Stengel Donald N. Stengel © 2002 The Wadsworth Group
l Chapter 15-Learning objectives Determine the least squares regression equation, and make point and interval estimates for the dependent variable Determine and interpret the value of the Coefficient of correlation Coefficient of determination Construct confidence intervals and carry out hypothesis tests involving the slope of the regression line o 2002 The Wadsworth Group
Chapter 15 - Learning Objectives • Determine the least squares regression equation, and make point and interval estimates for the dependent variable. • Determine and interpret the value of the: – Coefficient of correlation. – Coefficient of determination. • Construct confidence intervals and carry out hypothesis tests involving the slope of the regression line. © 2002 The Wadsworth Group
l Chapter 15-Key Terms · Direct or inverse Confidence interval relationships or the mean Least squares Prediction interval for regression mode an individual value Standard error of the Coefficient of estimate, s correlation ° Point estimate using· Coefficient of the regression model determination o 2002 The Wadsworth Group
Chapter 15 - Key Terms • Direct or inverse relationships • Least squares regression model • Standard error of the estimate, sy,x • Point estimate using the regression model • Confidence interval for the mean • Prediction interval for an individual value • Coefficient of correlation • Coefficient of determination © 2002 The Wadsworth Group
l Chapter 15-Key concep Regression analysis generates a best-fit equation that can be used in predicting the values of the dependent variable as a function of the independent variable o 2002 The Wadsworth Group
Chapter 15 - Key Concept Regression analysis generates a “best-fit” mathematical equation that can be used in predicting the values of the dependent variable as a function of the independent variable. © 2002 The Wadsworth Group
l Direct us Inverse relationships Direct relationship As x increases, y increases The graph of the model rises from left to right The slope of the linear model is positive Inverse relationship As x increases, y decreases The graph of the model falls from left to right The slope of the linear model is negative o 2002 The Wadsworth Group
Direct vs Inverse Relationships • Direct relationship: – As x increases, y increases. – The graph of the model rises from left to right. – The slope of the linear model is positive. • Inverse relationship: – As x increases, y decreases. – The graph of the model falls from left to right. – The slope of the linear model is negative. © 2002 The Wadsworth Group