"Two independent raters blind to the hypotheses and experimental conditions coded participants' neck-rubbing and knee-rubbing frequencies during their separate interaction with Rland R2 (Chartrand & Bargh, 1999). Interjudge reliabilities ranged from r( 2 }0.02 to . 0.29 p5 .001." Also, the mean of rater1's neck-rubbing codes equals (round to two decimals): 3.89 The standard deviation (as an estimate of the population) of rater2's knee-rubbing codes equals (round to two decimals): 1.88 The z-score associated with rater2's neck coding second entry (2.00) is (round to two decimals): -0.99 Use the data provided below and SPSS to re-run the analysis presented from the article above. Rineck R2neck R1knee R2knee This one is a little trickier. It looks like one analysis, but you actually need to run two correlations. Two raters coded neck-rubbing, and they also coded knee-rubbing. We want the inter-rater reliability, the correlation, for these ratings. So, we need one correlation to tell us how related the two coders' neck-rubbing codes were and then another correlation to tell us how related their knee-rubbing codes were. So, you should have one correlation between Rineck and R2neck. Then you should have separate correlation between R1knee and R2knee. Now, looking at the text from the article, they reported both correlations in the one sentence. So, you need to report both correlations after the the r( ), and then summarize the p-values after that by inserting either a . What goes inside the r( )? This is the degrees of freedom. It should be the number of pairs of scores minus 2. (Hint: this will be a number under 20)