Read the post below and help answer the bolded part. Please help!

I would use a relative frequency table for all the month's injuries in the clinic to display in the form of a pie chart. The relative frequency is the ratio of the number of times a data value occurs in the set of all outcomes to the total number of outcomes(Holmes, 2017). There will be the type of injury in the first column, and the number of injuries in the second column. Since I am using a pie chart to calculate the percentage, I will divide the number of injuries by the total number of injuries and multiply by 100. Then, I will display data value in a pie chart based on the percentage of type of injuries that happened that month. This type of chart is divided into a series of segments. Each segment represents the percentage of injuries that occurred that month.

For the second scenario, I would use a cumulative frequency table. Cumulative frequency is an accumulation of frequencies. I will make a continuous frequency distribution table on the first column based on time, for example, 0-10 minutes, 11-20 minutes, and so on. And the number of patients will be in the second column. Then, add the number of patients from the first category to that of the second category, add that total patient to the third category, and so on. The last value will be equal to the total number of patients that spent time in the waiting room. I will use the frequency polygon to represent the data. The x-axis would display the time spent in minutes, and the y-axis would show the number of patients.

Consider how different distributions might affect the different graphs. How might other variables affect the graphs? How could graphs be made to be biased? If a graph were biased, how might you change it to guard against that bias?