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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.

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More about Correlations

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  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…

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