AWS Certified Machine Learning – SpecialtyExploratory Data AnalysisEasy
A data scientist is analyzing a dataset of customer demographics. They want to check if there is a statistically significant association between 'PreferredCommunicationChannel' (categorical: Email, SMS, Phone) and 'PurchaseFrequencyGroup' (categorical: Low, Medium, High). Which statistical test is most appropriate for this analysis?
- AANOVA
- BIndependent samples t-test
- CPearson correlation coefficient
- DChi-squared test of independence
Show answer & explanationAnswer & explanation
Correct answer: D. Chi-squared test of independence
The Chi-squared test of independence is used to determine if there is a statistically significant association between two categorical variables. In this scenario, both 'PreferredCommunicationChannel' and 'PurchaseFrequencyGroup' are categorical.
Why the other options are wrong
- A. ANOVA compares means of a continuous variable across three or more groups.
- B. An independent samples t-test compares means of a continuous variable between two groups.
- C. Pearson correlation is for linear relationships between two continuous variables.
Chi-squared Test of Independence
A statistical test used to determine if there is a significant association between two categorical variables.
- Compares observed frequencies to expected frequencies.
- Null hypothesis: no association between variables.
- Alternative hypothesis: there is an association.
- Requires categorical data.
Memory trick: Categorical connections call for Chi-squared.