Week 2 Discussion: Graphing and Describing Data in Everyday Life

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For grading purposes, this particular discussion posting area runs from Sunday Jan 10 through Sunday Jan 17, inclusively.

We continue to explore Descriptive Statistics and the fundamentals of sampling techniques and quantitative research and research design this Week. This includes data, experimental design, so-called descriptive statistics, distributions, graphs and graphical displays, and measures of central tendency, variation, and position. At a somewhat basic and introductory level, we sometimes try to describe distributions using concepts of “shape, center, and spread.” Central tendency refers to “center” and variation refers to “spread.”

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Please don’t forget to use an “outside” resource as part of the content and documentation for your first Post – the Post which is due on or before Wednesday of the Week – the Post where you make the most major contribution to the Weekly discussion posting area and attempt to address the discussion prompts / cues for the Week.  It could possibly include a web site that you discovered on the internet at large, so long as the web site is relevant and substantial and does not violate the Chamberlain University policy for prohibited web sites, and so forth.  It could possibly include references / resources that you discover through making use of the online Chamberlain University Library ( please click Resources along the left and then click Library to discover the link to the Chamberlain University online Library ) .   

Please check out the link below to see some of the key similarities and key differences between Bar Plots / Graphs / Charts and Histograms.

Link (Links to an external site.)Links to an external site.

This is one kind of an example of using an “outside” source / resource to add to what is revealed in our Weekly Lesson in Modules and in our Weekly text book reading.

Please don’t forget to look over the Graded Discussion Posting Rubric each Week to be certain that you are meeting all of the Frequency requirements as well as all of the Quality requirements for graded discussion posting each Week.

If you have any questions about anything, please do not hesitate to post in the Q & A Forum discussion posting area or to send me a direct e-mail message to  CSmith10@chamberlain.edu

Thanks Friends and Good Luck !  Work hard and learn a lot !!

Sincerely,  Mr. Smith     Chamberlain University     Math, Statistics, and Quantitative Research

Hello everyone:

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).

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:

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

Elaine

https://stattrek.com/statistics/charts/histogram.aspx?Tutorial=APLinks 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.

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.

References:

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.

Professor and Class,

For the first set of data, evaluating the number of all Injuries seen in a clinic in one month, I would use a frequency table. A frequency table is an easy to read graph, that quickly tells you how often or how many times something is happening (Glen, 2020.) To organize this data, I would take a list of chief complaints/injuries, and assemble them in the left column, alphabetically. In the right side column, I would list the number of times that injury was treated in the clinic over the last month. A histogram could be used for this data set and would be easy to assemble. The vertical axis would contain the frequency of injuries, in intervals of 5. The horizontal axis would be filled with the class of injuries. 

For the second set of data, the number of minutes that each patient spent in the waiting room, I would use a relative frequency table. Getting the percentages of wait times will better help construct a graph, and will also help the person reading the data to better understand the actual data. I’d use a pie chart, because it is easy to assemble give the relative frequencies. For example, one could quickly look at a pie chart of this data and see that 20% of wait times are between 30 and 45 minutes. To me, having this readily available for nurse managers might help to expedite the patient’s wait time and improve clinic’s waiting room policies. 

Reference

Glen, S. (n.d.). Frequency Distribution Table: Examples, How to Make One. Retrieved January 12, 2021, from https://www.statisticshowto.com/probability-and-statistics/descriptive-statistics/frequency-distribution-table/Links to an external site.

Holmes, A., & Illowsky, B. (2017). Chapter 2.1. In 1146019274 862197969 S. Dean (Author), Introductory Business Statistics. Houston, TX: OpenStax College, Rice University. Retrieved January 12, 2021, from https://openstax.org/books/introductory-business-statistics/pages/2-1-display-data

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