Ch 3: Differences, Consistency, Test Scores Flashcards
Variance - Definition
- Statistical way of quantifying variability/individual differences in a distribution
- Tells you how far each data point is from the mean & every other data point
Interindividual Variability - Definition
Differences that exist between people
Intraindividual Variability - Definition
Differences that emerge in one person over time or under different circumstances
What factors determine the size of the variance?
1) How much the scores in a distribution differ from each other (duh)
2) Metric of the scores in the distribution
Variance - Formula
N - sum of squares / nr of scores
Variance (Binary) - Formula
p(1-p)
- p = proportion of Yes answers
Can the variance/SD be 0?
No, because this would mean that there are no differences in the data points at all, meaning that everyone would essentially have the same score
Covariance - Definition
Degree of association between the variability in the two distributions of scores
Covariance - Formula
N - sum of the cross product of deviation scores X & Y divided by the total number of observations
What information can be discerned from the covariance?
The direction of the association (not the magnitude though)
Correlation - Definition
Index of linear association between two variable, expressed as a value between -1 and +1
Correlation - Formula
(SDx)(SDy)
What information can be discerned from the correlation?
- direction of association
- magnitude of association
Central Tendency - Definition
The score that is the most representative of the entire distribution
What is the most commonly used reflection of central tendency?
The mean