Download presentation

Presentation is loading. Please wait.

Published byChristian Powers Modified over 2 years ago

1

2
Co-variation or co-relation between two variables These variables change together Usually scale (interval or ratio) variables

3
A statistic that quantifies a linear relation between two variables Can be either positive or negative Falls between and 1.00 The value of the number (not the sign) indicates the strength of the relation

4

5
Y X Y X Y Y X X Linear relationshipsCurvilinear relationships Slide from: Statistics for Managers Using Microsoft® Excel 4th Edition, 2004 Prentice-Hall

6
Y X Y X Y Y X X Strong relationshipsWeak relationships Slide from: Statistics for Managers Using Microsoft® Excel 4th Edition, 2004 Prentice-Hall

7
Y X Y X No relationship Slide from: Statistics for Managers Using Microsoft® Excel 4th Edition, 2004 Prentice-Hall

8
8

9
Association between variables such that if one variable increases, then the other increases. A direct relation between the variables

10
Association between variables such that if one variable increases, then the other decreases An inverse relation between the variables

11

12

13
+.70 or higher Very strong positive relationship +.40 to +.69 Strong positive relationship +.30 to +.39 Moderate positive relationship +.20 to +.29 Weak positive relationship +.01 to +.19 No or negligible relationship -.01 to -.19 No or negligible relationship -.20 to -.29 Weak negative relationship -.30 to -.39 Moderate negative relationship -.40 to -.69 Strong negative relationship -.70 or higher Very strong negative relationship

14
Something to think about There is a 0.91 correlation between ice cream consumption and drowning deaths. Does eating ice cream cause drowning? Does grief cause us to eat more ice cream?

15
15 Correlation is NOT causation -e.g., armspan and height

16

17
Correlation is not causation. Invisible third variables Three Possible Causal Explanations for a Correlation

18
Correlation coefficient quantifies the linear relationship of two variables Also called r or r factor Shows how strongly they are connected Not proof of causality (causation)

Similar presentations

© 2016 SlidePlayer.com Inc.

All rights reserved.

Ads by Google