Stats Chapter 10

A correlation coefficient is used to:

determine if, and how, two variables might be related to each other

A correlation can only be used if the scores on each variable:

are paired or linked to each other in some way

Positive z scores represent values that are:

above average

The absolute value of a z score indicates:

how much better or worse a given score is than the mean score

When paired z scores tend to have the same sign, the resulting r value is:

positive

When paired z scores tend to have opposite signs, the resulting r value is:

negative

Correlations reveal:

the strength and direction of the relationship between two variables

If two variables have a weak relationship, the absolute value of r will be close to:

0

Correlation coefficients range from:

-1 to +1

A negative correlation indicates that high scores on one variable are associated with:

low scores on the second variable

The strongest association is represented by:

the value furthest from zero

In a scatterplot, each dot represents:

a set of paired X and Y scores

An outlier can cause r to:

overestimate or underestimate the association depending on the location of the outlier

If a trend is monotonic but not linear, use:

Spearman's correlation

Ceiling and floor effects tend to:

underestimate the true population correlation

If both variables are interval or ratio scale, use:

Pearson's correlation

If at least one variable is ordinal, use:

Spearman's correlation

Correlation does not imply:

causation

No statistics are sufficient evidence for inferring:

causality

Inspecting a scatterplot helps determine:

whether Pearson's or Spearman's correlation is appropriate and whether the trend is linear

The null hypothesis for a Pearson correlation predicts r will be close to:

0

The coefficient of determination is:

r²

r² represents:

the percentage of variability in one variable predicted by variability in the other variable

If r² = .36, then:

36% of the variability is predicted by the other variable

For a correlation, degrees of freedom equal:

n - 2

If r(8) = .65, then the sample size is:

10

If r(8) = .65, then r² =:

.4225

The sign of r indicates:

direction

The absolute value of r indicates:

strength

A positive correlation means:

scores on both variables tend to move in the same direction

A negative correlation means:

scores on the variables tend to move in opposite directions

The strongest possible positive correlation is:

+1

The strongest possible negative correlation is:

-1

The weakest possible correlation is:

0

Pearson's correlation requires:

interval or ratio variables and a linear relationship

Spearman's correlation should be used when:

at least one variable is ordinal or the trend is monotonic rather than linear

Each participant contributes:

one pair of scores

The effect size for a correlation is:

r²

A strong correlation is represented by:

a value far from zero

A weak correlation is represented by:

a value close to zero

High scores paired with high scores and low scores paired with low scores indicate:

a positive correlation

High scores paired with low scores indicate:

a negative correlation