Lecture Marketing research - Chapter 13: Bivariate correlation and regression

27 62 0
Lecture Marketing research - Chapter 13: Bivariate correlation and regression

Đang tải... (xem toàn văn)

Tài liệu hạn chế xem trước, để xem đầy đủ mời bạn chọn Tải xuống

Thông tin tài liệu

After studying this chapter you will be able to: comprehend the nature of correlation analysis, understand bivariate regression analysis, become aware of the coefficient of determination, R2. Inviting you to refer.

CHAPTER Thirteen Learning Objectives Bivariate Correlation and Regression Copyright © 2004 John Wiley & Sons, Inc Learning Objectives Learning Objectives To comprehend the nature of correlation analysis To understand bivariate regression analysis To become aware of the coefficient of determination, R2 Learning Objectives Bivariate Analysis of Association To understand bivariate regression analysis Bivariate Analysis Defined The degree of association between two variables Bivariate techniques Statistical methods of analyzing the relationship between two variables Multivariate Techniques When more than two variables are involved Independent variable Affects the value of the dependent variable Dependent variable explained or caused by the independent variable Learning Objectives Bivariate Analysis of Association To understand bivariate regression analysis Types of Bivariate Procedures • Two group t-tests • chi-square analysis of cross-tabulation or contingency tables • ANOVA (analysis of variance) for two groups • Bivariate regression • Pearson product moment correlation Learning Objectives Bivariate Regression To understand bivariate regression analysis Bivariate Regression Defined Analyzing the strength of the linear relationship between the dependent variable and the independent variable Nature of the Relationship • Plot in a scatter diagram • Dependent variable Y is plotted on the vertical axis • Independent variable X is plotted on the horizontal axis • Nonlinear relationship Learning Objectives Bivariate Regression To understand bivariate regression analysis Bivariate Regression Example Figure 13.1 Types of Relationships Found in Scatter Diagrams Y X A - Strong Positive Linear Relationship Learning Objectives Bivariate Regression To understand bivariate regression analysis Figure 13.1 Types of Relationships Found in Scatter Diagrams Y X B - Positive Linear Relationship Learning Objectives Bivariate Regression To understand bivariate regression analysis Figure 13.1 Types of Relationships Found in Scatter Diagrams Y X C - Perfect Negative Linear Relationship Learning Objectives Bivariate Regression To understand bivariate regression analysis Figure 13.1 Types of Relationships Found in Scatter Diagrams X D - Perfect Parabolic Relationship Learning Objectives Bivariate Regression To understand bivariate regression analysis Figure 13.1 Types of Relationships Found in Scatter Diagrams Y X E - Negative Curvilinear Relationship Learning Objectives Bivariate Regression To understand bivariate regression analysis Values for a and b can be calculated as follows: b= XiYi - nXY X2i - n(X)2 a = Y - bX X = mean of value X Y = mean of value y n = sample size Learning Objectives Bivariate Regression To become aware of the coefficient of determination, R2 The Regression Line Predicted values for Y, based on calculated values Strength of Association: R2 Coefficient of Determination, R2: The measure of the strength of the linear relationship between X and Y Learning Objectives Bivariate Regression To become aware of the coefficient of determination, R2 explained variance R = total variance explained variance = total variance - unexplained variance total variance - unexplained variance R = total variance = 1- unexplained variance total variance Learning Objectives Bivariate Regression R = 1- To become aware of the coefficient of determination, R2 unexplained variance total variance n (Yi - Yi)2 = 1- I=1 n (Yi - Y)2 I=1 Learning Objectives Bivariate Regression To become aware of the coefficient of determination, R2 Statistical Significance of Regression Results Total variation = Explained variation + Unexplained variation The total variation is a measure of variation of the observed Y values around their mean It measures the variation of the Y values without any consideration of the X values Learning Objectives Bivariate Regression To become aware of the coefficient of determination, R2 Total variation: Sum of squares (SST) SST = n i=1 (Yi - Y)2 n n = Y i i=1 Y i i=1 n Learning Objectives Bivariate Regression To become aware of the coefficient of determination, R2 Sum of squares due to regression (SSR) SSR = n i=1 (Yi - Y)2 n n = a i = 1Yi + n bi = 1Xi Yi i=1 Yi n Learning Objectives Bivariate Regression To become aware of the coefficient of determination, R2 Error sums of squares (SSE) SSE = n i=1 (Yi - Y)2 n = n Y i=1 i = 1Yi n bi = 1XiYi Learning Objectives Bivariate Regression To become aware of the coefficient of determination, R2 Hypotheses Concerning the Overall Regression Null Hypothesis Ho: There is no linear relationship between X and Y Alternative Hypothesis Ha: There is a linear relationship between X and Y Learning Objectives Bivariate Regression To become aware of the coefficient of determination, R2 Hypotheses about the Regression Coefficient Null Hypothesis Ho: b=0 Alternative Hypothesis Ha: b The appropriate test is the t-test Figure 13.4 Measures of Variation in aLearning Regression Objectives Y Yi =a + bXi Unexplained variation Total Variation Explained variation Y (X, Y) a X Xi X Learning Objectives Correlation Analysis To become aware of the coefficient of determination, R2 Correlation for Metric Data - Pearson’s Product Moment Correlation Correlation analysis Analysis of the degree to which changes in one variable are associated with changes in another variable Pearson’s product moment correlation Correlation analysis technique for use with metric data Learning Objectives To become aware of the coefficient of determination, R2 Correlation Analysis R = + - √R R can be computed directly from the data: n XY - ( X) - ( Y) R= √ [n X2 - ( X) 2] [n Y2 - Y)2] Learning Objectives SUMMARY • Bivariate Analysis of Association • Bivariate Regression • Correlation Analysis Learning Objectives The End Copyright © 2004 John Wiley & Sons, Inc ... variance) for two groups • Bivariate regression • Pearson product moment correlation Learning Objectives Bivariate Regression To understand bivariate regression analysis Bivariate Regression Defined... Learning Objectives Bivariate Analysis of Association To understand bivariate regression analysis Types of Bivariate Procedures • Two group t-tests • chi-square analysis of cross-tabulation or contingency... Learning Objectives Bivariate Regression To understand bivariate regression analysis Bivariate Regression Example Figure 13.1 Types of Relationships Found in Scatter Diagrams Y X A - Strong Positive

Ngày đăng: 18/01/2020, 23:11

Mục lục

  • Slide 1

  • Slide 2

  • Slide 3

  • Slide 4

  • Slide 5

  • Slide 6

  • Slide 7

  • Slide 8

  • Slide 9

  • Slide 10

  • Slide 11

  • Slide 12

  • Slide 13

  • Slide 14

  • Slide 15

  • Slide 16

  • Slide 17

  • Slide 18

  • Slide 19

  • Slide 20

Tài liệu cùng người dùng

Tài liệu liên quan