McGraw-Hill OnlineMcGraw-Hill Higher EducationLearning Center
Student Center | Instructor Center | Information Center | Home
Full Study Guide
Guide to Electronic Research
Internet Guide
Study Skills Primer
Statistics primer
Appendices
Learning Objectives
Chapter Overview
Fill in the Blanks
Definitions
Flashcards
Symbols and Formulas
Problems
SPSS Exercises
Self-Test
Feedback
Help Center


Thorne and Giesen Book Cover
Statistics for the Behavioral Sciences, 4/e
Michael Thorne, Mississippi State University -- Mississippi State
Martin Giesen, Mississippi State University -- Mississippi State

Correlation and Regression

Symbols and Formulas

SYMBOLS

SymbolStands For

rPearson r, Pearson product-moment correlation coefficient
zx, zyz scores for the X and Y variables, respectively
covXYcovariance of X and Y
ρpopulation correlation coefficient, read “rho”
rcomp, rcritcomputed value of r and the critical value of r from Table E, respectively
<a onClick="window.open('/olcweb/cgi/pluginpop.cgi?it=gif:: ::/sites/dl/free/0072832517/55322/chap13_ycaret.gif','popWin', 'width=NaN,height=NaN,resizable,scrollbars');" href="#"><img valign="absmiddle" height="16" width="16" border="0" src="/olcweb/styles/shared/linkicons/image.gif"> (0.0K)</a> Y-caret, predicted values for Y based on the regression equation
bregression coefficient, slope of the regression line
aY intercept, value of Y where the regression line crosses the Y axis
sY, sXstandard deviation of the Y variable and the X variable, respectively
r2coefficient of determination
rsSpearman rank order correlation coefficient
ddifference between the ranks

FORMULAS

Formula 13-2. Computational formula for the Pearson r

<a onClick="window.open('/olcweb/cgi/pluginpop.cgi?it=gif:: ::/sites/dl/free/0072832517/55322/chap13_formula2.gif','popWin', 'width=NaN,height=NaN,resizable,scrollbars');" href="#"><img valign="absmiddle" height="16" width="16" border="0" src="/olcweb/styles/shared/linkicons/image.gif"> (2.0K)</a>

The values needed to compute the equation are: ∑X, ∑Y, ∑X2, ∑Y2, ∑XY, and N. ∑XY is found by multiplying each X by each Y and summing the result.

Formula 13-3.Regression equation for predicting Y from X

<a onClick="window.open('/olcweb/cgi/pluginpop.cgi?it=gif:: ::/sites/dl/free/0072832517/55322/chap13_formula3.gif','popWin', 'width=NaN,height=NaN,resizable,scrollbars');" href="#"><img valign="absmiddle" height="16" width="16" border="0" src="/olcweb/styles/shared/linkicons/image.gif"> (2.0K)</a>

Formula 13-4. Equation for determining the proportion of variability in data explained by correlation

<a onClick="window.open('/olcweb/cgi/pluginpop.cgi?it=gif:: ::/sites/dl/free/0072832517/55322/chap13_formula4.gif','popWin', 'width=NaN,height=NaN,resizable,scrollbars');" href="#"><img valign="absmiddle" height="16" width="16" border="0" src="/olcweb/styles/shared/linkicons/image.gif"> (3.0K)</a>

Formula 13-5. Equation for the Spearman rank order correlation coefficient

<a onClick="window.open('/olcweb/cgi/pluginpop.cgi?it=gif:: ::/sites/dl/free/0072832517/55322/chap13_formula5.gif','popWin', 'width=NaN,height=NaN,resizable,scrollbars');" href="#"><img valign="absmiddle" height="16" width="16" border="0" src="/olcweb/styles/shared/linkicons/image.gif"> (1.0K)</a>

d is the difference between the ranks of individuals on the two variables, and N is the number of pairs of observations.