Key Terms

Question 1

What is sums of squares?

Answer 1

the sum of the squared deviations of a set of values from the mean

Question 2

What do we use sums of squares for?

Answer 2

to determine how spread apart the scores are in a data set

Question 3

What is sums of squares total?

Answer 3

how spread out scores are from the mean of all the scores

Question 4

What is sums of squares between?

Answer 4

how spread out condition means are
from the mean of all the scores (and therefore from each other)

Question 5

What is sums of squares within?

Answer 5

how spread out scores are from the
condition means

Question 7

What is sums of squares?

Answer 7

the sum of the squared deviations of some set of values from some mean

Question 8

Why do we use sums of squares?

Answer 8

Used to quantify how spread out two or more values are in a dataset

Question 9

What is sums of squares total?

Answer 9

how spread out scores are from the mean of all the scores

Question 10

What is sums of squares between?

Answer 10

y how spread out condition means are from the mean of all the scores

Question 11

What is sums of squares within?

Answer 11

how spread out scores are from the
condition means

Question 12

What does SSb tell us?

Answer 12

1. how much the groups systematically vary from
   each other and shows the EXPLAINED variability of the conditions

Question 13

What does SSw tell us?

Answer 13

1. how much each person varies after accounting for
   the condition they’re in - shows the variability NOT EXPLAINED by the
   conditions

Question 14

What is the F-test measuring?

Answer 14

1. the ratio of explained to unexplained variability
2. whether systematic variance is greater than unsystematic variance

Question 15

What is correlation?

Answer 15

the degree to which deviations on one variable go in the same direction or the opposite direction of deviations on a second variable

Question 16

How are standardised z-scores found?

Answer 16

how much the score deviates from the mean (in units of standard deviation)

Question 17

how do we measure how much those deviations go together?

Answer 17

you multiply standardized deviations (Z scores) from one variable by
standardized deviations (Z scores) from a second variable,

Question 18

How to find Pearson’s r value?

Answer 18

the average of those multiplied deviations and divide by N – 1

Question 19

Why do we use vectors?

Answer 19

Vectors turn a nominal (categorical) variable into an interval variable, and
thereby allow us to calculate a correlation

Question 20

What is a vector?

Answer 20

a numerical variable coded in such a way as to capture the difference
between the conditions of a categorical variable

Question 21

How is correlation in a Vector the same as SSb?

Answer 21

tells us how
much scores on the DV go along with the conditions thus

How much of the
variability is EXPLAINED by the conditions

Question 22

What does R^2 reg/Pearson’s r represent?

Answer 22

Pearson’s r-squared then represents the proportion of variance in the DV explained by the IV

Question 23

How is the F-test similar to ANOVA in Regression?

Answer 23

we are trying to find out is whether the EXPLAINED variability (derived from R2 Reg) is greater than the UNEXPLAINED variability (derived from R2 Res)

= (the ratio of explained to unexplained variability)