Correlation (Fields Ch. 6)

Question 1

Bivariate correlation

Answer 1

a correlation between two variables (only)

Question 2

Coefficient of determination

Answer 2

(r-squared)
the proportion of variance in one variable explained by a second variable. It is Pearson’s correlation coefficient squared.

Question 3

Kendall’s tau

Answer 3

a non-parametric correlation coefficient (use w/ small data set with a large number of tied ranks.)

Question 4

Partial correlation

Answer 4

a measure of the relationship between two variables while ‘controlling’ the effect of one or more additional variables on both.

Question 5

Pearson’s correlation coefficient

Answer 5

Pearson’s product-moment correlation coefficient, to give it its full name, is a standardized measure of the strength of relationship between two variables. It can take any value from _1 (as one variable changes, the other changes in the opposite direction by the same amount), through 0 (as one variable changes the other doesn’t change at all), to 1 (as one variable changes, the other changes in the same direction by the same amount).

Question 6

Spearman’s correlation coefficient

Answer 6

a non-parametric correlation coefficient. It is Pearson’s correlation coefficient performed on data that have been converted into ranked scores.

Question 7

Standardization

Answer 7

the process of converting a variable into a standard unit of measurement. The unit of measurement typically used is standard deviation units (see also z-scores). Standardization allows us to compare data when different units of measurement have been used (we could compare weight measured in kilograms to height measured in inches).

Question 13

Ftest

Answer 13

The amount of systematic variance divided by the amount of unsystematic variance
The model explained the devided by the error of the model
as the value of F increases the models predictive capacity increases relative to the inaccuracy of the model

Question 14

B-value

Answer 14

The slope of the regression line. Bigger b means the predictor variable is a stronger predictor of the outcome