MATH 225N Week 3 Discussion: Measures of Central Tendency and Variation 

MATH 225N Week 3 Discussion: Measures of Central Tendency and Variation

MATH 225N Week 3 Discussion: Measures of Central Tendency and Variation 

For grading purposes, this particular discussion posting area runs from Sunday Jan 17 through Sunday Jan 24, inclusively.

We explore the so-called Normal Distributions this Week. This includes normal probability distributions, the standard normal distribution, the standard normal distribution Table, the concept of continuous distributions, sampling distributions, and the Central Limit Theorem.

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 ) . 🙂

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Check out the link below for some information about the so-called Standard Normal Distribution.  After that page comes up also click on the normal distribution link from that page to see some more useful and relevant information for our Week 3 concerns and COs.

Click here to ORDER an A++ paper from our Verified MASTERS and DOCTORATE WRITERS MATH 225N Week 3 Discussion: Measures of Central Tendency and Variation :

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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

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

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

And here is just an example Post showing you the potential to get Excel output into a graded Post and what it might look like and how it might work.

I will be making a lot of Posts throughout Week 3 showing and demonstrating for you how to do this. But you don’t have to wait for those Posts though if you don’t want to. There is already an 11 minute Video in Media Gallery along the left of the screen which shows you how to do this.

Thanks Friends and Best Wishes and Good Luck too !!


PS    Even though it is a little fuzzy and blurry in the graphic / image here, that z-score is negative.

It is  – 0.8  since 72 – 80 is of course negative.  And then – 8 / 10 of course is  – 0.8

And so I would think that these things in this list here would be graphical displays that you would consider here and pick two of them to propose as alternative methods to display the data.

IMPORTANT:  PLEASE remember that there are probably several “red herrings” here in this list –

Several of these graphical displays are not appropriate for the injuries data set or wait times data set in Week 2 and some of these graphical displays in this list here are not appropriate for the articles and their respective frequency tables that you are considering for this Week 3 lab turn in assignment !!!      😉

So within the context of all of these cautions and warnings please try hard to do well with the Week 3 lab turn in assignment.

Thanks Friends and Best Wishes and Good Luck too !!

OK so what I did now was to use the same 30 pieces of resting heart rate data and added two “made up” pieces of resting heart rate data ( 53 per minute and 126 per minute I think they were ) and when the program created the box and whiskers plot ( I also told the program to run diagnostics to look for potential outliers ) the program flagged both the 53 per minute and 126 per minute rates as being potential outliers ( indicated by the little blue dots ) .

You all actually had a few homework exercises along these lines where you found cutoffs for potential outliers using    1.5 times IQR    and then seeing if any really low or really high pieces of data ( observations ) fell below the bottom cut off or above the top cut off.  Remember that ??  It was probably a “select all that apply” type “multiple choice” exercise.

Dear Professor and classmates:

I selected the first ten patients from this week’s cath lab cases: six male, four female, aging in range from 46 to 79 years old. I took the heart rate from the first set of vitals done as the patient was on the table. I plugged the values into the excel workbook given this week, sorted them from low to high and then created a frequency table. I wanted to make a bar chart and a Pareto chart so the bars for the categories would also be sorted in order by size (Holmes et al., 2018). I also wanted to separate bradycardic values and give them their own category.

The normal range for adult heart rates is 60–100 beats per minute. Bradycardia less than 60 beats per minute and tachycardia is greater than 100 beats per minute (DeVesty & Schub, 2017).

week 3 first chart.jpg
week 3 second chart.jpg
week 3 freq chart.jpg

As fate would have it, the mean and median are both 76, there is no mode in this set. The standard deviation is 14.3 and the range is 48. According to the formula in Holmes (2018), there are no outliers in this sample set:

Interquartile range is Q3-Q1  or 86.75-65.75=21;  21*1.5=31.5

Outlier boundaries:  Q1 65.75-31.5=34.25; Q3 86.75+31.5=118.25

week 3 pareto.jpg
week 3 bar chart.jpg

N=10 is a small sample size, so I wouldn’t jump to any conclusions. But it was interesting to see a unimodal distribution skewed to the right. Two patients were bradycardic, only one was tachycardic. The remaining seven fell within the normal range; six of the seven fell in the IQR.

I don’t think the Pareto chart necessarily adds any value here. I like the standard bar chart.  I tried to make a box and whisker plot but Excel wasn’t playing nicely with others tonight and the graph looked terrible.


DeVesty, G., Schub, T. (2017). Physical assessment: performing a cardiovascular assessment in adults.

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

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