Reading...
Play button
Play button
Use LEFT and RIGHT arrow keys to navigate between flashcards;
Use UP and DOWN arrow keys to flip the card;
H to show hint;
A reads text to speech;
24 Cards in this Set
- Front
- Back
|
The product-moment (Pearson) correlation coefficient between two variables (x and y) is a measure of
|
the linear association between those variables.
|
|
|
a measure of the linear association between those variables.
|
product-moment (Pearson) correlation coefficient
|
|
|
product-moment correlation coefficient is also called
|
(Pearson)
|
|
|
This coefficient for the product-moment (Pearson)
|
usually denoted as r and assumes values from -1 to 1.
|
|
|
n
|
= the number of observations, indexed i = 1,…
|
|
|
= the number of observations, indexed i = 1,…
|
n
|
|
|
Correlation Significance Tests
Ho and Ha |
Ho: p = 0 (the population correlation is zero)
Ha: p does not equal 0 |
|
|
Ho: p = 0 (the population correlation is zero)
Ha: p does not equal 0 |
Correlation Significance Tests
Ho and Ha |
|
|
Correlation Significance Tests- alpha
|
=.05`
|
|
|
Correlation Significance Tests
how many tails? which distribution table? degrees of fredom? |
two-tail test
t distribution n-2 |
|
|
For Correlation Significance Tests, how do you look up the number in the t table
|
.05/2 and d.f is n-2
|
|
|
if the calculated t value is smaller than the table t value
|
do not reject
|
|
|
if the calculated t value is greater than the table t value
|
reject ho
|
|
|
a measure of the linear association between those variables after controlling for (or adjusting) for the effects of other variables.
|
partial correlation
|
|
|
partial correlation
|
a measure of the linear association between those variables after controlling for (or adjusting) for the effects of other variables.
|
|
|
z
|
in partial correlation, it is the "other variable
|
|
|
What is the ____correlation between X and W after adjusting for V.
|
partial
|
|
|
yi=
|
the measure of dependent variables of observations, i (in regression)
|
|
|
p=
|
the number of independent variables, indexed j = 1,.....p
|
|
|
Xij=
|
measure of independent variable j on observation i
|
|
|
bo=
|
an intercept term
|
|
|
b1=
|
slope coefficients
|
|
|
prediction error=
|
yi - yi(hat)
|
|
|
predition line
|
yi(hat) = bo + b1Xil
|
