Suppose that you have two sets of data to work with. The first set is a list of all the injuries that were seen in a clinic in a month's time. The second set contains data on the number of minutes that each patient spent in the waiting room of a doctor's office. You make assumptions about other information or variables that are included in each data set.
For each data set, propose your idea of how best to represent the key information. To organize your data would you choose to u frequency table, a cumulative frequency table, or a relative frequency table? Why?
What type of graph would you use to display the organized data from each frequency distribution? What would be shown on e the axes for each graph?
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For the first data set, which is a list of all the injuries seen in a clinic in a month's time, a frequency table would be the most appropriate way to represent the key information. A frequency table would show the number of times each injury occurs in the data set, which would give a clear picture of the most common injuries.
To display the organized data from the frequency table, a bar graph or a pie chart would be suitable. The x-axis of the graph would represent the different injuries, and the y-axis would represent the frequency or count of each injury. This graph would give a visual representation of the distribution of injuries in the clinic.
For the second data set, which contains the number of minutes each patient spent in the waiting room of a doctor's office, a cumulative frequency table would be a good choice to represent the key information. This table would show the number of patients who waited for a certain range of minutes, which would give insights into the waiting time distribution.
To display the organized data from the cumulative frequency table, a histogram or a cumulative frequency graph would be appropriate. The x-axis of the histogram would represent the ranges of waiting time (e.g., 0-10 minutes, 10-20 minutes), and the y-axis would represent the cumulative frequency or the number of patients. This graph would provide a visual overview of the waiting time distribution in the doctor's office.
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