CompTIA Data+ (DA0-002)Data AnalysisEasy
A team of data analysts is investigating the relationship between advertising spend and sales revenue. They have collected data over several months and want to quantify the strength and direction of the linear relationship between these two continuous variables. Which statistical measure should they calculate?
- APearson correlation coefficient
- BStandard deviation
- CANOVA F-statistic
- DChi-square statistic
Show answer & explanationAnswer & explanation
Correct answer: A. Pearson correlation coefficient
The Pearson correlation coefficient (r) is used to measure the strength and direction of a linear relationship between two continuous variables. A positive value indicates a positive linear relationship, a negative value indicates a negative linear relationship, and values closer to 1 or -1 indicate a stronger relationship.
Why the other options are wrong
- B. Standard deviation measures the spread of a single variable, not the relationship between two variables.
- C. ANOVA F-statistic is used to compare means of three or more groups.
- D. Chi-square statistic is used for testing relationships between categorical variables.
Pearson Correlation Coefficient
A statistical measure that quantifies the strength and direction of a linear relationship between two continuous variables, ranging from -1 to +1.
- Values range from -1 (perfect negative linear correlation) to +1 (perfect positive linear correlation).
- A value of 0 indicates no linear correlation.
- Only measures linear relationships; non-linear relationships may exist even with r=0.
Memory trick: Pearson Correlation is like seeing if two friends always walk in the same direction and how close they stay.