Question

question #14
which statement about the relationship between correlation and causation is true?
a causation implies correlation.
b correlation implies causation.
c positive correlation implies causation.
d negative correlation implies a lack of causation.

question #15
which correlation coefficient best represents data that has a strong negative correlation?
a -0.95
b -0.05
c 0.05
d 0.95

Explanation:

Question #14 Step1: Evaluate causation-correlation links

If one variable causes another, there must be a measurable relationship (correlation) between them. Correlation (positive/negative) never guarantees causation, and negative correlation does not rule out causation.

Question #15 Step1: Define correlation coefficient range

Correlation coefficients range from $-1$ to $1$. Values close to $-1$ mean strong negative correlation, values close to $1$ mean strong positive correlation, and values near $0$ mean weak/no correlation.

Question #15 Step2: Match to strong negative correlation

$-0.95$ is closest to $-1$, so it represents a strong negative correlation.

Answer:

Question #14: A. Causation implies correlation.
Question #15: A. -0.95