Final answer:
While actual customer names cannot be provided due to privacy concerns, in an academic context, dividing the total expenditure by the number of people on a trip can determine if more than $50 was spent per person.
Step-by-step explanation:
To address the question of identifying customers who spent more than $50 per person on a trip, we would need exhaustive data on customer expenditures, which typically isn't directly disclosed due to privacy concerns. However, in a hypothetical scenario or for an academic exercise, when given transaction data with the total amount spent and the number of customers involved in a trip, one could calculate the spending per person. If the total spending divided by the number of individuals exceeds $50, you could then extract the pertinent customer names. Unfortunately, without specific transaction data or access to a business's financial records, it's not possible to provide actual names.
Independent events in probability are outcomes where the occurrence of one does not affect the occurrence of another. For example, charging more than $2,000 per month on a credit card and using a credit card that provides air travel miles for each dollar spent are two separate actions that must be analyzed to determine their relationship. The data provided in the recent poll suggests a strong correlation since 80 percent of those who charge more than $2,000 use a credit card that offers air travel miles, signifying it is not an independent event due to a significant overlap between the groups.
In the context of the onboard bills for cruise ships, this aggregated information doesn't allow for individual identification but offers insight into spending habits of groups, such as single travelers versus couples, which can be useful for budgeting and planning for businesses in the travel industry. Moreover, the summary of the bills from single travelers and couples on a cruise could provide a baseline for calculating average expenditures and determining what constitutes excessive spending.
When looking at the variation in prices of hotels across different cities, statistical tests like the ANOVA (Analysis of Variance) at a 1 percent level of significance could determine if there are statistically significant differences in hotel prices between cities. If so, this data could inform a traveler who wishes to maintain an average spending threshold, such as $50 per night.