1 / 16

More about Correlations

More about Correlations. Spearman Rank order correlation. Does the same type of analysis as a Pearson r but with data that only represents order . Ordinal data represents highest to lowest but without any indication of distance between ranks. Spearman correlation cont.

cherit
Download Presentation

More about Correlations

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. More about Correlations

  2. Spearman Rank order correlation • Does the same type of analysis as a Pearson r but with data that only represents order. • Ordinal data represents highest to lowest but without any indication of distance between ranks.

  3. Spearman correlation cont. • With a Spearmen rank order correlation both variables (x and y) are ranked. • The correlation then determines the relationship between rankings • Easier calculation but less powerful as a statistical test.

  4. Multiple Regression Correlation: Relationship between two variables. Regression: What would you predict about the dependent variable, given the independent variable(s).

  5. Since you can have several variables: • One or more are designated as dependent while all others are independent. • The DV is identified based on prior knowledge or expectations. • The IV’s can be continuous measurements (different than an ANOVA) • This analysis still does not show causation.

  6. Relationship is defined by : • Where: • a is the intercept • Each x is an IV • Each B is a regression coefficient for a particular IV

  7. Looking at the output Correlation overall is evaluated with F.

  8. IV1 IV2 DV IV3

  9. R - Multiple correlation coefficient is the measure of correlation between the predicted y and the obtained y. • R2 - the portion of the variation of the DV that is predictable from the regression equation.

  10. Output cont. • Each IV can be evaluated based on a t test based on the regression coefficients.

  11. If: cancer deaths % of smokers and % of the population over 75 are used to predict median health care costs…

  12. If: # of hospitals and # of MD’s Are used to predict median health care costs…

More Related