MATH 225N Discussion Graphing and Describing Data in Everyday Life

MATH 225N Discussion Graphing and Describing Data in Everyday Life

MATH 225N Discussion Graphing and Describing Data in Everyday Life

For the first question, I created a frequency table of a list of injuries one might see in a walk-in clinic over the past month:

Week 2 Injury Freq Table.jpg

Rather than sort alphabetically, I sorted from highest number of injuries to lowest and then created a horizontal bar graph with the types of injuries on the y axis simply as a matter of preference, since either is acceptable in a bar graph (Holmes, Illowsky and Dean, 2018):

Week 2 Injury Bar Graph.jpg

It might be interesting to see where the data falls over the course of many months using a cumulative review of the frequency of the various injuries. I would expect bee stings to increase during warmer weather when people spend more time outside, therefore the clinic would have data to be well prepared to treat those injuries. A histogram wouldn’t be useful here, as the labels are categorical, not quantitative (Stattrek, 2020).

MATH 225N Discussion Graphing and Describing Data in Everyday Life
MATH 225N Discussion Graphing and Describing Data in Everyday Life

For the second question, Let’s assume the following wait time in minutes for a given day: 5, 5, 5, 5, 9, 10, 10, 15, 15, 30, 30, 35, 35, 40, 45, 60, 65, 70, 70, 75. First, I created a frequency table, but using the math rules taught us this week in the Knewton Lesson on frequency tables (Chamberlain University, 2020), I really didn’t care for the groups of times created, so I created a second table using increments of 15 minutes since the frequency outcome didn’t change:

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Week 2 Wait times Freq Table.jpg

I like a pie chart best to show that while most people (45%) only had a wait of less than 15 minutes, still another 45% had waits of more than 30 minutes. This pie chart makes it easy to see where improvement needs to be made.

Week 2 Wait times Pie Chart.jpg to an external site.

Holmes, A., Illowsky, B., & Dean, S.  (2018).  Introductory business statistics.  OpenStax

Chamberlain University, (2020). MATH225. Week 2 Knewton Lesson Frequency Tables (online lesson). Downers Grove, IL. Adtalem.

First of all, wow! I am impressed with your charts. This may be a really stupid question, but how did you get them to paste into the discussion board? I had mine pasted into  my word document, but for the life of me could not get them to paste on here.  I will also admit. I have not used an Excel spread sheet in years and for work, our administrative assistants do that for us, so I am technologically an idiot.    I stayed up until 2 am this morning fighting with trying to get it pasted into my discussion post with  no luck.  I would appreciate it if you could share your secret!

For data set 1, the graph does not seem to be biased since the x-axis is equally spaced. It is also a good idea to sort the injuries from lowest to highest frequency because it made the graph easier to understand. For data set 2, I think since the data is continuous, histograms are more appropriate to use. This would make sure that the distribution of the data is taken accounted for. Different distributions have different effects on the graphs. For example, if the data is normally distributed, the histogram would look bell-shaped. On contrary, if it is normally distributed, the bars of the histogram would approximately be equal.

I have a question.  If you sorted the injuries from lowest to highest frequency to make the graph easier to understand on this data set, how would you make the next months’ graphs if the results changed?   Would the graph still be organized lowest to highest frequency of injuries or stay in the same order as the first month?  I used alphabetical order for the injuries in my frequency table and on my histogram.  I was thinking of the results in the following months if the study was going to continue.  If the amount of each injury changes and is recorded on the graph, my injuries would be in the same position and yours would potentially be in different positions. The different positions might be harder to compare when two or more graphs of the months were viewed side by side.

I agree, it definitely would be interesting to see where the data falls over the course of many months using a cumulative review of the frequency. Also, I wonder if similar to my data trends, which month of the year has more injuries over the others. In the Cardiac Cath Lab we see a definite increase in heart attack trends in what appears to be the beginning of each season. I do not know why, but your post has me thinking more about the reason for the trends. Thank you for your post.

Thank you for your post. After reading your post, I was able to visualize what I was thinking and able to put my idea into words. Statistics is not a strong subject of mine, because it is not the first thing I think of to relate a story or situation to another. Although statistics are present everywhere, and we could apply them to everyday situations, being able to tie things together through statistics, isn’t as easy as typing it. I can visualize my ideas, but putting them into words and applying them is where I struggle. By seeing your picture charts, I was able to easier understand the information we needed to get across. I too thought about the specific type of injuries versus waiting times. The more serious the injury, the less the waiting time spent in the lobby and the actual waiting time for the doctor. Of course, the more serious injuries would be seen in the emergency department where I work, some patients will be seen in the clinic, then sent directly to the ED or direct admit admission to the hospital. The picture charts help clear up any confusion and allow the reader to understand the material taught. 

Again, thank you for your insightful post. 

Number of Injuries seen in a Clinic in one month –

Collecting the data, I would use frequency because I would be counting the number of injuries that fall into this class, which is looking at the number of times something happens over a period of time.

I would consider using a pie graph because the whole pie would represent the month and the number of different injuries would be a piece of the pie. This could be color coordinated by types of injuries. When presenting a pie chart it is easier for people to understand.  Although you could use a Box Plot graph to demonstrate this as well.

Time Spent in the Waiting Room –

I would use a histogram to organize my data. On the Axis – y I would put the number of minutes waited and on the X-axis I would put the number of patients that waited that amount of time.

I would use a Stem plots graph because we are exploring data to be analyzed. (2020). This type of graph gives you a quick way to see the exact information that you are collecting data on. Although you cannot use a graphing calculator on this type of graph this type of graph is useful for finding distribution as long as the data is relatively small. (Mcafee, 2011). Below is an example of a stem plot graph. The stem of the graph would represent the time spent in the waiting room and the Leaf would be the number of patients that waited.


Chamberlain University, (2020). MATH225. Week 2 Knewton Lesson Frequency Tables (online lesson). Downers Grove, IL. Adtalem.

Mcafee, Gerry. Boston, MA : Course PTR. 2011. eBook., Database: eBook Collection (EBSCOhosLinks to an external site.

I liked reading your post. You mentioned that you would use pie graph for the number of injuries seen in clinic. Pie graph is a simple and easy-to-understand picture.Pie graph or chart shows data in slices, as it has a circular shape. As a whole pie graph represents the sum of all its data; individual slices represent a percentage of whole.  It represents data visually as a fractional part of a whole, which can be an effective communication tool. It enables the audience to make an immediate analysis or to understand the information quickly. On the other side, if we use too many pieces of data, pie graphs become less effective. They themselves may become crowded and hard to read if there are too many pieces of data. Still as of today, pie chart is one of the most popular data visualization formats.

You have a great response. I think I was over thinking the instructions and could not come up with an example like you did. But your example of the frequency table for the first set and then the stem and leaf table for the second set was very helpful in understanding it. I’m the type of person that even though I see examples from books, sometimes I need an example from the professor or a classmate in order to understand things more. I was able to picture everything and understand why you chose both tables.

What’s interesting is that, I understood the stem and leaf concept from the book. It was the easiest one for me to understand, but to use it the way you did, I wouldn’t have thought of it. Like I said, I probably over thought my answer.  

Working in a clinic, especially an urgent care clinic opens you up to patients with a variety of ailments. According to Solv Health (2020), “Some of the most common injuries seen in an urgent care clinic are: Fractures, whiplash, sprains, cuts, burns, injury from falls, and injury from car accidents. These facilities are not appropriate for life threatening illnesses or injuries. If, for example, you have a cut that is extremely deep and will not stop bleeding, an emergency room may be a better option than the urgent care” (p.1).

The best way to show the number of injuries a clinic sees over a months’ time would be to display it first in a frequency table. That way you get an accurate view of that one month and the number and types of accidents seen. According to Holmes, Illowsky, and Dean (2017), “A frequency table is the number of times a value occurs. Relative frequency is the ration (fraction or proportion) of the number of times a value of data occurs in the set of all outcomes to the total number of outcomes. Cumulative relative frequency is the accumulation of the previous relative frequencies” (OpenStax, section 1.3). If we were looking at data for several months, then using relative frequency or cumulative relative frequency would be a better alternative but using a frequency table is the best for one months’ worth of data. 

To decide which would be the best way to show my data, I choose a bar graph to display the type of injuries seen in an urgent care clinic in the last month. I feel this shows the best example of being the easiest way to read and interpret the data presented. The X axis represents the number of injuries and the Y axis represents the type of injury. According to Holmes, Illowsky, and Dean (2017), “Two graphs that are used to display qualitative(categorical) data are pie charts and bar graphs. In a bar graph, the length of the bar for each category is proportional to the number of precent of individuals in each category” (OpenStax, section 1.2).

Gathering information from my bar graph, 36 patients were seen with injuries at the urgent care client over the last month. The wait time in minutes for the patients were as follows: Eight patients stated they waited 15 minutes to be seen, five waited 20 minutes, two waited 25 minutes, four waited 35 minutes, six waited 40 minutes, five waited 30 minutes, and six waited 60 minutes. A frequency chart could be made to chart these times. 

Doing a frequency chart seems to be the best way to organize your data so it is easy to read and the data can be incorporated it into another chart. I chose a pie chart to represent the amount of time represent per percentage. The pie chart is good at showing percentages of the wait times to get a picture of the data given. I have never used Excel to make charts before, so not sure if this was done right or not, but I was proud of myself for muddling through it to even create the charts I did. You tube is a blessing.  

I was trying to figure a way to display both sets of data on one scatter chart, but it was not possible as I did not have a second set of data to do so.  You would need how many patients were seen with each ailment on a specific date to get the numbers you needed to get an X and Y axis. So, I made a scatter chart for the wait time for patients for the past month. On the X axis is the number of patients and the Y axis is the wait times. It is just another way to show the data. If you do not have enough data, your representation may be skewed and inaccurate. The more data you can draw from the more accurate your results will be. 

For some reason I am not able to display my Excel work that I did. It will paste into Word, but not here for some reason and I am not sure why, so I attached my word document to my discussion post so you can see what it looks like. 


Holmes, A., Illowsky, B., & Dean, S. (2017). Introductory business statistics. OpenStax. to an external site.

Solv Health. (2020). What are the Most Common Urgent Care Conditions?, 1-2. Retrieved from,the%20ankle%2C%20knee%2C%20or%20shoulderLinks to an external site.