1. Chapter 5
Correlation
Correlation – a relationship between two variables.
Correlation coefficient (Pearson’s r) – Ranges from -1 to 1.
Positive and Negative Correlations (p. 76).
Negative does not mean “less significant” or “worse” than positive.
The strength of the correlation is the absolute value of the coefficient (has nothing to do with sign)
C. Formula:

2. Practice (p Table)
Graphing Correlations
A. By hand (plot each x and corresponding y on a graph that encompasses the full range of scores). Example p. 81
Visual of positive and negative correlation (82-83).
Correlations of more than two variables (matrix; p.84).
Interpreting coefficient
Correlation Coefficient: Strength rules of thumb (p. 85 Table 5.2)
Coefficient of determination – r2 (% of variance in one variable that is explained by the variance in another variable). Example: GPA and Study hours (r=.70 and r2=.49). Means that 49% of variance in Y is explained by the variance in X (51% is not).
Visual description on page 87.
Only association, not causality

3. Some strong correlations may be directionally causal, bi-directionally causal, or not causal in any sense (coincidence). Further investigation has to be done.
Examples: sleep and feeling refreshed; unemployment and mental hospital admissions; being poor and smoking
If something is correlated, but not causal, then the relationship is said to be spurious or missing an important factor. Examples: Above – could be that divorce has contributed to admissions; (not-absurd) anti-smoking program and smoking decreases; # of fire engines and amount of fire damage ($); hair length and test scores (absurd).
IV. SPSS and Correlation