# Stats I Final Pitt 3

 What is correlation? correlation measures the relationship between two variables there are more than one type of correlation (depending on level of measurement) Pearson product moment correlation correlation between interval/ratio variables most widely used measure of correlation has the most assumptions Speraman rank correlation correlation between ordinal variables Phi coefficient correlation between dichotomous variables point-biserial correlation correlation between a dichotomous & interval/ration variables ex: right or wrong of an exam item and total score biserial correlation correlation between a dichotomous (w/ underlying continuum) & interval/ratio variables ex:anxiety (low, high) & depression polyserial correlation correlation between a polytomous (3 or more levels) (w/ underlying continuum) & interval/ratio variables ex: anxiety (low, medium, high) & depression tetrachoric correlation correlation betwee dichotomous variables (w/ underlying continuum) and depression ex: anxiety (low, high) & depression (low, high) polychoric correlation correlation between polytomous variable (w/ underlying continuum) Pearson Product Moment Correlation Assumptions correlation No Outliers Linearity Normal Distribution Pearson Assumptions: No Outliers correlation no extreme scores two types:-univariate -multivariate Pearson Assumption: No Outliers - Univariate correlation an extreme score that is far away from the distribution of a variable -only one variable Pearson Assumption: No Outliers - Multivariate correlation an extreme score that is far away from the joint distribution of variables it is possible for a case to be a multivariate outlier without bieng a univaritate outlier Pearson Assumption: Linearity correlation variables should NOT show any non-linear pattern Pearson Assumption: Normal Distribution correlation distribution of a variable should be univariate normal distribution of variables should be multivariate normal Range of Correlation correlation all correlation range from -1 to +1a measure of correlation is unitless (or standardized). r = -1 perfect negative relationshipr = +1 perfect positive relationshipr = 0 no relationship Scatterplot correlation when the correlation is r= +1, the scatterplot appears in a straight line as the correlation approaches 0, the variability of scores increases Covariance correlation measures of relationship between two variables in raw units (unstandardized correlation) possible range is -infinity to +infinity Types of Research Questions correlation 1. Is there a significant relationship between x and y? 2. Is there a significant difference in the relationship of x and y between group 1 and group 2? 3. What is the (1-alpha)%CI of the correlation? Sampling Distribution Correlation correlation in not normal except when r=0 due to restricted range of the correlation-bound between -1 & +1 One-sample t-test for correlation correlation For testing H0: p = 0, Greek letter rho - population correltaion df = N - 2 affected not only by N but also by r. Depends on the # of subjects & relationship When to us r-critical correlation when testing more than one correlation becomes tedious easier to compute r-critical value as long as there are same N Fisher's r-to-z transformation when to use correlation For testing a H0: p = p0 For difference in a correlation between groups For confidence interval of a correlation Convert r to z-score AuthorAnonymous ID187294 Card SetStats I Final Pitt 3 DescriptionStats I Finall Pitt part 3 Updated2012-12-05T15:55:31Z Show Answers