What type of sampling method should StitchFix use to ensure representation from different age groups?

StitchFix should use a stratified sampling method to ensure representation from different age groups because this method is specifically designed to ensure that sub-groups within a population are adequately represented in the sample. In the case of age groups, stratified sampling involves dividing the overall population into distinct age categories (strata) and then randomly selecting samples from each of these categories. This approach ensures that all age groups are included in the survey or analysis, which provides a more comprehensive and accurate understanding of the preferences or needs across the different age demographics.

By using stratified sampling, StitchFix can avoid the potential biases that might occur if certain age groups are underrepresented, thereby capturing a more diverse perspective on customer preferences and improving the overall effectiveness of their analysis and marketing strategy.

The other sampling methods mentioned may not produce the same level of representation across age groups. Simple random sampling does not take into account specific characteristics of the population, such as age, which could lead to some groups being overlooked. Cluster sampling involves dividing the population into clusters and then sampling whole clusters, which may not provide the representation needed for different age segments. Systematic sampling, while easier to implement, may also inadvertently favor certain groups over others, depending on the order of the population list.