Week 6 revision Flashcards
What is the key distinction between experimental designs (3) and correlational designs (2)?
Experimental determines causation between manipulated IV’s and conditions that are randomly assigned, correlation is correlation between measured IV’s with the DV being an outcome.
What is the distinction between design issues and statistical issues, and why the two
should not be confused?
Design issues include randomised/experimental vs unrandomised/correlational designs while statistical is how continuous or grouped data is analysed
What is random assignment the only way of inferring
Causation
Define covariance
The average cross-product (multiplication) of the deviation scores (subtracted mean)
What is covariance main limitations?
It doesn’t give us any scale information to intercept strength of association/relationship, so we can’t compare covariances based on different scales because they aren’t standardized.
Define correlation in relation to covariance.
Correlation is the measurement of variables relative covariance to a common standard deviation OVER the average cross-product (multiplication) of their standard scores
How does correlation address the limitations of covariance?
It is standardized so you can compare data from different scales.
What are the terms used to indicate a bivariate correlation? (3)
Pearsons correlation
bivariate correlation
zero-order correlation
Define the coefficient of determination in the context of bivariate correlation, what letter indicates it?
The coefficient of determination is the proportion of variance in one variable that is explained by variance in another. Indicated by r(squared)
What is the relationship between the coefficient of determination and error/residual variance?
The error/residual variance is the variance left over from the coefficient of determination. (1-r(squared))
What question is being addressed when we test r for significance, and which statistical test is used for this purpose?
is there a significant correlation between the way two factors vary, is used for a statistical test of correlation.
What is the difference between r and r(adjusted)?
r is the correlation between two variables in terms of standard deviation in a sample, while r(adjusted) is the same thing for the population. r/r(adjusted) becomes more conservative as the group gets bigger.
What is the relationship between bivariate correlation and bivariate regression?
Bivariate correlation assesses the association between two variables in terms of strength and direction, while bivariate regression goes a step further by modeling the relationship between the variables and allowing for prediction of one variable based on the other.
What are the various components of the bivariate regression equation representing? (4)
Yhat = predicted value of Y (DV)
b = slop of regression line ( changes in DV/Y with a 1 unit change in IV/X)
X = Value of predictor (IV/X)
a = intercept (Value of Y when X=0)
What is the relationship between b and β (beta)?
b (standardized regression coefficient) and β (Beta coefficient) both represents the change in the outcome variable (dependent variable) per one-unit change according to the SD in the predictor variable (independent variable), while holding all other predictors constant.
What is the least squares criterion (in bivariate regression)?
The least squares criterion seeks to find the line that minimizes the distance between the observed data points and the corresponding points on the regression line according to the predicted Y.
What is the standard error of the estimate is (in words) and what it tells us (in
bivariate regression)?
Reflects the amount of variability around the regression line, and tells us how much data should deviate from the regression line.
What question is being addressed when we test the regression slope (i.e., b or β) for significance, and which test is used for this purpose?
Whether the slope of the regression line is significantly different from zero, indicating whether the predictor variable(s) have a non-zero effect on the outcome variable, we use a t-test to do this.
What do SSY, SSregression, and SSresidual represent?
SSY = Total variability
SSregression = prediction average / treatment variability
SSresidual = observation prediction / error variability
How is the F ratio calculated in regression and what question is it used to test?
MSregression/Msresidual
Does the model account for significant variance in the DV? H0 rsquare=0
What does “ANCOVA” stand for?
Analysis of Covariance
What is covariance?
The tendency for two scores to vary together/ in a similar way.
What are the key similarities between ANCOVA and blocking?
Both reduce the size of the error term by including a factor that explains a proportion of variance in the DV.
What are the key differences between ANCOVA and blocking?
ANCOVA statistically adjusts the error term, and can use control variables that are continuous.
