This preview shows page 1. Sign up to view the full content.
Unformatted text preview: ulate the cross
product of Z scores Cross
product = mul7plying scores on one variable by scores on another What happens in the case of a nega1ve correla1on? ▪ If you mul7ply a high Z score (+) by a low Z score (
), you get a nega7ve cross
product (
) ▪ If you mul7ple a low Z score (
) by a high Z score (+), you get a nega7ve cross
product (
) ▪ If you add up these cross
products, you get a large nega7ve number (
) In compu7ng a correla7on, we calculate the cross
product of Z scores Cross
product = mul7plying scores on one variable by scores on another What happens in the case of no correla1on? ▪ Varied associa7ons: high with high, low with low; high with low, low with high ▪ Adding up all of these cross products would result in posi7ve cross
products and nega7ve cross
products canceling each other out, given a result of 0, or close to 0. 9 11/13/13 These cross
products tell you about the direc1on of the rela7onship Posi7ve vs. Nega7ve In order to ﬁgure out the strength of the rela7onship in a standard way, need to divide the sum of the cross
products by the number of people in the study This represents the average of the cross
products of Z scores Correla7on can range from
1 to +1 (with 0 represen7ng no correla7on) Correla1on coeﬃcient: the resul7ng number when you divide the sum of the cross products of Z score by the number of people in the study Also called Pearson correla7on coeﬃcient (or the Pearson product
moment cor...
View
Full
Document
This note was uploaded on 03/24/2014 for the course PSY 21201 taught by Professor Bernard during the Winter '13 term at SUNY Stony Brook.
 Winter '13
 bernard
 Psychology

Click to edit the document details