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MATH 225N WEEK 2 DISCUSSION, GRAPHING AND DESCRIBING DATA IN EVERYDAY LIFE $7.99   Add to cart
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MATH 225N WEEK 2 DISCUSSION, GRAPHING AND DESCRIBING DATA IN EVERYDAY LIFE
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MATH 225N WEEK 2 DISCUSSION, GRAPHING AND DESCRIBING DATA IN EVERYDAY LIFE/MATH 225N WEEK 2 DISCUSSION, GRAPHING AND DESCRIBING DATA IN EVERYDAY LIFE/MATH 225N WEEK 2 DISCUSSION, GRAPHING AND DESCRIBING DATA IN EVERYDAY LIFE

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  • January 16, 2023
  • 2
  • 2022/2023
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  • math 225n week 2 discussion
  • graphing and describing data in everyday life

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MATH 225N WEEK 2 DISCUSSION, GRAPHING AND DESCRIBING
DATA IN EVERYDAY LIFE


Both sets of data are quantitative and should be organized in a manner that allows for the

generation of relevant inferences. The first set of data comprises of a list of all the injuries that

were seen in a clinic in a month's time, and can be best represented using a cumulative frequency

table. Data organized using a cumulative frequency table. Assuming that the hospital has been

reporting an average number of injuries over the past year, the cumulative frequency would be

very useful in determining the number of injuries that lie above or below the mean value.

The second set contains data on the number of minutes that each patient spent in the waiting

room of a doctor's office, and frequency table would be useful in this case because most patient

wait times will be identical, and a frequency table would provide a good representation of the

data as grouped data, especially along with their corresponding frequencies. A frequency table

will provide an overview of all distinct values and the number of times they occur.

Graphs provide an excellent opportunity for researchers to establish trends in the data collected

(Nolan & Perrett, 2016). To graph the first set of data, a line graph would be very useful in

representing the set of data values in a manner that demonstrates variation in the frequency of the

injuries with time. This means that the x-axis would have the time and the y-axis would have the

number of injuries, thus, providing a general pattern in the data sets as noted by Holmes,

Illowsky, and Dean (2018).

The second set of data can be best represented using a histogram graph because is considered the

best with continuous quantitative data (Holmes et al., 2018). The data (wait times) will be put

into classes or bins with regular intervals and frequency counts. The frequency for each bin

would be graphed on the y-axis while the bins would be on the x-axis.



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