Final answer:
A one sample t-test is the appropriate choice for Lululemon to determine if the average in-store spending per consumer is significantly higher than $50.
Step-by-step explanation:
Lululemon's inquiry about whether the average in-store spending for each consumer is significantly higher than $50 can be addressed using a statistical hypothesis test. Specifically, the appropriate test for this scenario is a one sample t-test. This test is used to compare the sample mean to a known value (in this case, $50) to determine if there is a statistically significant difference between them. The one sample t-test is suitable when you have a single sample and want to assess whether the sample mean differs from a known or hypothesized population mean.
For example, let's consider a similar scenario where a statistical test is required: A survey of 43 stores, yielding a sample mean calculator cost of $84 and a sample standard deviation of $12, prompts a test to claim that the standard deviation is greater than $15. This would not use the one sample t-test but rather a chi-square test for variance, since the question pertains to the standard deviation rather than the mean.
Overall, the Lululemon scenario falls under the umbrella of hypothesis testing in statistics, which is an essential tool for making inferences about population parameters based on sample statistics.