AWS Certified Machine Learning – SpecialtyExploratory Data AnalysisMedium
A data scientist is analyzing a dataset of customer demographics. They want to understand the relationship between 'age' (numerical) and 'preferred communication channel' (categorical: Email, SMS, Phone). Which statistical test is most appropriate for determining if there is a statistically significant association between these two variables?
- AChi-squared Test of Independence
- BANOVA (Analysis of Variance)
- CPearson Correlation Coefficient
- DStudent's t-test
Show answer & explanationAnswer & explanation
Correct answer: B. ANOVA (Analysis of Variance)
ANOVA is the appropriate statistical test for comparing means across three or more independent groups. In this scenario, 'preferred communication channel' defines three or more groups, and 'age' is the numerical variable whose mean is being compared across these groups.
Why the other options are wrong
- A. Chi-squared Test of Independence is used to determine if there is a significant association between two categorical variables.
- C. Pearson Correlation Coefficient measures the linear relationship between two numerical variables.
- D. Student's t-test is used to compare the means of a numerical variable between exactly two groups of a categorical variable.
ANOVA (Analysis of Variance)
ANOVA is a statistical test used to compare the means of three or more groups to determine if there is a statistically significant difference between them.
- Compares means of a numerical variable across multiple categories.
- Requires the numerical variable to be approximately normally distributed within each group.
- Assumes homogeneity of variances (equal variances) across groups.
Memory trick: ANOVA: A Numerical variable Over Various Averages.