Final answer:
Length of stay data can be categorized as individual length of stay or average length of stay for a group. Given an average of 2.4 days with a standard deviation of 0.9 days, the sum of stays for 80 women does not exceed a year. Other elements discussed include types of data (qualitative vs. quantitative), the systematic sampling method used in a study, and interpreting wait times with reference to box plots.
Step-by-step explanation:
When describing the two kinds of length of stay data, we are referring to individual length of stay and average length of stay for a group. For the scenario given, the average length of a maternity stay in a U.S. hospital is 2.4 days with a standard deviation of 0.9 days, and 80 women who recently bore children were surveyed.
Individual Length of Stay
The individual length of stay (X) refers to the number of days an individual person stays in the hospital. For instance, an individual might have stayed more than five days, which would be longer than the reported average.
Average Length of Stay for a Group
The average length of stay for a group (\( \bar{X} \)) is the mean stay of 80 women which, if more than five days, indicates this group's stays were longer than the national average. When summing up the women's stays, to determine if they collectively spent more than a year in the hospital, we use the formula for the sum of stays: total days = average stay * number of women. Given the average stay of 2.4 days and 80 women, the sum would be 192 days, which is less than a year.
The number of times per week is a quantitative discrete type of data, as it involves a countable number of occurrences within a defined period.
The sampling method described in the exercise is systematic, since every eighth house around the park was selected after the first random house.
The colors of the houses around the park are a type of qualitative (categorical) data as they describe attributes that cannot be quantified.
If an individual had a wait time longer than 82 percent of patients, this relates to box plots which visually represent the distribution of data and could indicate that the individual had a longer than typical wait time.