Final Exam Vocabulary Flashcards
Correlation
A number that describes the extent to which two variables are related to each other
Spurious Correlation
Correlation that is brought about due to the influence of a third variable
ex: shark attacks and ice cream sales
Pearson’s r
Measures the strength and direction of the linear relationship between variables
aka: correlation coefficient
Covariance
measures the variability of two variables about their means
indicates correlation direction but not strength
“unstandardized value”
X-Variable (4)
- independent
- predictor
- regressor
- explanatory
Y-Variable
- dependent
- predicted
- regressed
- response
- criterion
Residuals
aka: error
difference between the observed and expected value
Sum of Squares
Variability
Mean Squared
Variance
(variability divided by df)
Coefficient of Determination
the proportion of variability in Y that can be explained by the variability in x
Residual Variation
VARIATION in Y that can not be predicted by X
(1 - coefficient of determination)
Residual Variability
Error variability (SSE)
Test the Significance of the Overall Model
Rho Squared (p^2)
F-Statistic
df total
n-1
df regression
1
df error
n-2
df t-test
n-2
conditional distribution
the distribution of Y scores associated with the same
value of X
Homoscedasticity
the observed values of Y vary to the same degree at each level of X
aka conditional distributions are normal and have roughly the same variance
Standard Error of the Estimate
standard deviation of the residuals about a mean of zero
Standard Error of the Regression Coefficient
Standard deviation of the sampling distribution of all the possible b1 values
OLS Simple Regression Assumptions
L - Linear Relationship
I - Independence of Errors: one error does not inform another
N - Normality of Error: the conditional distribution is normally distributed
E - Equal Variance: Hom
