Statistics for Six Sigma Green Belts with Minitab and JMP

Chapter 9. Simple Linear Regression

INTRODUCTION

9.1 TYPES OF REGRESSION MODELS

9.2 DETERMINING THE SIMPLE LINEAR REGRESSION EQUATION

9.3 MEASURES OF VARIATION

9.4 ASSUMPTIONS

9.5 RESIDUAL ANALYSIS

9.6 INFERENCES ABOUT THE SLOPE

9.7 ESTIMATION OF PREDICTED VALUES

9.8 PITFALLS IN REGRESSION ANALYSIS

SUMMARY

REFERENCES

APPENDIX 9.1 USING MINITAB FOR SIMPLE LINEAR REGRESSION

APPENDIX 9.2 USING JMP FOR SIMPLE LINEAR REGRESSION

Learning Objectives

After reading this chapter, you will be able to Understand how to use regression analysis to predict the value of a dependent variable (CTQ) based on an independent variable (CTP or X). Interpret the meaning of the regression coefficients b0 (Y intercept) and b1 (slope). Evaluate the assumptions of regression analysis ...