A data analytics manager has gathered usage data on four new application features that were originally predicted to have the same level of user adoption. The actual user adoption rates for each feature deviate from what was forecast. Which technique helps determine if this difference is significant?
Simple linear regression
Chi-squared test
z-test
ANOVA
The correct technique to determine if the difference in user adoption rates among multiple groups (in this case, four application features) is statistically significant is: ANOVA (Analysis of Variance).
ANOVA (Analysis of Variance) is a statistical method used to determine whether there are significant differences between the means of three or more independent groups.
z-test: Appropriate for comparing a sample mean to a population mean, or comparing two groups, not more.
Chi-squared test: Suitable for categorical data (e.g., frequencies), not for comparing means.
Simple linear regression: Used to model the relationship between a dependent and an independent variable, not for comparing multiple group means.
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