PSY 411 Chapter 5 Notes

Causality

Causality

The assumption that a correlation indicates a causal relationship between the two variable

correlation coefficient

A measure of the degree of relationship between two sets of scores. It can vary between -1.00 and + 1.00

Directionality

The inference made with respect to the direction of a relationship between two variables

Magnitude

An indication of the strength of the relationship between two variables

negative correlation

An inverse relationship between two variables in which an increase in one variable is related to a decrease in the other, and vice versa

partial correlation

A technique used to determine the effects of a third variable by removing the effect of the third variable from the correlation of the remaining two variables

person-who argument

Arguing that a well established statistical trend is invalid because we know a “person who” went against the trend

positive correlation

A relationship between two variables in which the variables move together—an increase in one is related to an increase in the other, and a decrease in one is related to a decrease in the other

restrictive range

A variable that is short and does not vary enough

Scatterplot

A figure that graphically represents the relationship between two variables

third-variable problem

The problem of a correlation between two variables being dependent on another (third) variable

coefficient of determination (r2)

A measure of how much one variable is accounted for in another variable; calculated by squaring the correlation coefficient.

Pearson product-moment correlation coefficient (Pearson’s r)

The most commonly used correlation coefficient when both variables are measured on an interval or ratio scale

phi coefficient

The correlation coefficient used when both measured variables are constant and nominal.

point-biserial correlation coefficient

The correlation coefficient used when one of the variables is measured on a constant nominal scale and the other is measured on an interval or ratio scale

Spearman’s rank-order correlation coefficient

The correlation coefficient used when both of the variables are measured on an ordinal (ranking) scale

Degrees of freedom

The number of scores in a sample that are free to vary; need the df in order to calculate the statisical significance df = n- 2

Alpha

probability level: alpha (α)  set at .05 rcrit for a two-tailed test from r table

Temporal ordering

what comes first

Assumptions of correlational analysis

1. Correlation focuses on linear relationships only

2. Correlation do not work well if the data range is "restricted"

3. Variability should be consistent at all values of x

4. Data are continuous

Homoscedasticity

when the standard deviations of a predicted variable, monitored over different values of an independent variable are constant

Heteroscedasticity

when the standard deviations of a predicted variable, monitored over different values of an independent variable are non-constant

Statistical significance

An observed difference between two descriptive statistics (such as means) that is unlikely to have occurred by chance.

Describe the difference between strong, moderate, and weak correlation coefficients.

• Strong: + .70 - 1.00

• Moderate: + .30 - .69

• Weak: + 00 - .29