When selecting customers from different age groups, what type of random sampling method should StitchFix use?

StitchFix should utilize stratified random sampling when selecting customers from different age groups. This method involves dividing the population into distinct subgroups or strata based on specified characteristics—in this case, age groups. By ensuring that each age group is represented in the sample, stratified random sampling enhances the accuracy and relevance of the results for each specific demographic segment.

This approach is particularly beneficial in situations where age may influence customer preferences, behaviors, or shopping patterns. By sampling proportionally from each age group, StitchFix can draw more reliable conclusions about the entire customer base while also gaining insights that pertain to specific age demographics.

Furthermore, this method allows for comparisons between the different age groups, making it easier to identify trends and preferences that might not be apparent if customers were selected randomly without considering their age. In contrast to other sampling methods, such as cluster sampling—which might group customers together based on proximity or another singular criterion—stratified sampling ensures a more nuanced representation across the relevant categories.