Download presentation

Presentation is loading. Please wait.

Published byAdrian McCarthy Modified over 3 years ago

1
Section 4.2

2
Correlation and Regression Describe only linear relationship. Strongly influenced by extremes in data. Always plot data first. Extrapolation – Use of regression line or curve outside the values of the domain of explanatory variable.

3
Averaged Data Correlations based on averages, not actual data, are usually too high. Smooths out data. Does not allow for scatter among individuals.

4
Lurking Variables Variables that influence the two studied variables but are not in the study. Can falsely suggest a strong relationship. Can hide a relationship. Ex: Herbal tea in nursing homes/Ice cream drowning.

5
Association does not imply Causation Strong associations cause/effect relation. Causation – Change in x causes change in y. Common Response – Both x and y respond to changes in some unobserved variable. Confounding – The effect on y of x is mixed up with effects on y of other variables.

6
Lurking Variables

7
Experiments Best way to get good evidence that x causes y. Only x is changed, while lurking variables are controlled.

Similar presentations

© 2017 SlidePlayer.com Inc.

All rights reserved.

Ads by Google