MATH 225N Week 3 Discussion: Central Tendency and Variation
Understanding descriptive statistics, their measures of center and their variability, helps form the
foundation of statistical analysis. Descriptive statistics tell us how frequently an observation
occurs, what is considered average, and how far data in our sample deviate from being average.
With these statistics, we are able to provide a summary of characteristics from both large and
small datasets. Measures of central tendency and variability provide valuable information on
their own, and form the cornerstone of the quantitative structures that we build in our research
studies.
Required Resources
Read/review the following resources for this activity: OpenStax Textbook: Chapter 2
Lesson
Minimum of 1 scholarly source
In your reference for this assignment, be sure to include both your text/class materials AND your
outside reading(s).
Initial Post Instructions
For this Discussion, you will examine central tendency and variability in terms of pulse rate.
Find and record the pulse rate of 10 different people where you work. Tell us a little about the
population from which you drew your data. Describe your findings in terms of central tendency
and variability. Consider using some of the following to help you form your initial discussion
post:
What are your measures of central tendency (i.e., mean, median, and
mode)? Which might be the better measure for central tendency and why?
What is the standard deviation of your data? How variable are the data
(range)?
Are there any outliers? Investigate possible reasons for these outliers, and
things that might limit them if further study were to be carried out. What are some
variables that should be … in discussing your measures of central tendency and
variation? Is there any skewness in your … data?
How would you describe this data (i.e. what insights did you gain from
this data)?
, Answer 1
According to Holmes, A., Illowsky, B. and Dean, S. (2019), central tendency is an average. It is
the mean, mode, and median that represent the center of our data sets. Variation is just the
opposite of central tendency. It measures how the data is spread out. It consists of range,
variance and quartiles. For this discussion I have chosen 10 registered female nurses that are
nurse case manager senior analysts. They make home visits 1-2 times a week and see between 5-
7 patients a week. Their job is not physically taxing but extremely mentally taxing. Ages ranged
from 35-59. The pulse rates were as follows: 68 98 66 82 94 70 78 82 86 92. To obtain the
mean, I added the 10 pulse rates together and divided by 10. The mean was 81.6. To obtain the
median, I arranged the numbers from smallest to largest and chose the middle number. 66 68 70
78 82 82 86 92 94 98. The median was 82. The mode is the number which appears most often
and that would be 82. This was a sample variance since I chose a random sampling from 50+
nurses that work at my company. The sample standard deviation was 11.187 and the sample
variance was 125.155. I was able to utilize the week 3 worksheet to check my answers. There
were no outliers that I could identify as the numbers were consistent between 66-98. Some
measures that might skew the data would be activity levels, resting, involved in stressful
situations, had caffeinated drinks, males vs female, mode of measurement, etc. According to
Wong, J., Lu, W., Wu, K., Liu, M., Chen, G., & Kuo, C. (2012), they excluded people who had
major cardiopulmonary disease or was on regular medicine for diabetes mellitus, hypertension,
renal or liver disease in effort to avoid skewed results. They verified that quality of pulse rates
varied by location of pulse so it would be important to determine that all pulses were obtained in
the same location on each individual. It is possible that my data could be slightly skewed as I did
not consider overall health, location of pulse, or any of the skewness data aforementioned. I
should have developed criteria prior to the screening process to ensure the accuracy of the data.
As one would say, ‘compare apples to apples’.
Holmes, A., Illowsky, B. & Dean, S. (2019). Openstax. Introductory Business
Statistics. Retrieved from: https://cnx.org/contents/tWu56V64@33.86:39NcLz3J@18/Measures-
of-the-Center-of-the-Data
Understanding descriptive statistics, their measures of center and their variability, helps form the
foundation of statistical analysis. Descriptive statistics tell us how frequently an observation
occurs, what is considered average, and how far data in our sample deviate from being average.
With these statistics, we are able to provide a summary of characteristics from both large and
small datasets. Measures of central tendency and variability provide valuable information on
their own, and form the cornerstone of the quantitative structures that we build in our research
studies.
Required Resources
Read/review the following resources for this activity: OpenStax Textbook: Chapter 2
Lesson
Minimum of 1 scholarly source
In your reference for this assignment, be sure to include both your text/class materials AND your
outside reading(s).
Initial Post Instructions
For this Discussion, you will examine central tendency and variability in terms of pulse rate.
Find and record the pulse rate of 10 different people where you work. Tell us a little about the
population from which you drew your data. Describe your findings in terms of central tendency
and variability. Consider using some of the following to help you form your initial discussion
post:
What are your measures of central tendency (i.e., mean, median, and
mode)? Which might be the better measure for central tendency and why?
What is the standard deviation of your data? How variable are the data
(range)?
Are there any outliers? Investigate possible reasons for these outliers, and
things that might limit them if further study were to be carried out. What are some
variables that should be … in discussing your measures of central tendency and
variation? Is there any skewness in your … data?
How would you describe this data (i.e. what insights did you gain from
this data)?
, Answer 1
According to Holmes, A., Illowsky, B. and Dean, S. (2019), central tendency is an average. It is
the mean, mode, and median that represent the center of our data sets. Variation is just the
opposite of central tendency. It measures how the data is spread out. It consists of range,
variance and quartiles. For this discussion I have chosen 10 registered female nurses that are
nurse case manager senior analysts. They make home visits 1-2 times a week and see between 5-
7 patients a week. Their job is not physically taxing but extremely mentally taxing. Ages ranged
from 35-59. The pulse rates were as follows: 68 98 66 82 94 70 78 82 86 92. To obtain the
mean, I added the 10 pulse rates together and divided by 10. The mean was 81.6. To obtain the
median, I arranged the numbers from smallest to largest and chose the middle number. 66 68 70
78 82 82 86 92 94 98. The median was 82. The mode is the number which appears most often
and that would be 82. This was a sample variance since I chose a random sampling from 50+
nurses that work at my company. The sample standard deviation was 11.187 and the sample
variance was 125.155. I was able to utilize the week 3 worksheet to check my answers. There
were no outliers that I could identify as the numbers were consistent between 66-98. Some
measures that might skew the data would be activity levels, resting, involved in stressful
situations, had caffeinated drinks, males vs female, mode of measurement, etc. According to
Wong, J., Lu, W., Wu, K., Liu, M., Chen, G., & Kuo, C. (2012), they excluded people who had
major cardiopulmonary disease or was on regular medicine for diabetes mellitus, hypertension,
renal or liver disease in effort to avoid skewed results. They verified that quality of pulse rates
varied by location of pulse so it would be important to determine that all pulses were obtained in
the same location on each individual. It is possible that my data could be slightly skewed as I did
not consider overall health, location of pulse, or any of the skewness data aforementioned. I
should have developed criteria prior to the screening process to ensure the accuracy of the data.
As one would say, ‘compare apples to apples’.
Holmes, A., Illowsky, B. & Dean, S. (2019). Openstax. Introductory Business
Statistics. Retrieved from: https://cnx.org/contents/tWu56V64@33.86:39NcLz3J@18/Measures-
of-the-Center-of-the-Data
