write a 150-word answer/response on the below comment

(Part A) AND the question (Part B) on the specific topic.

Part A.

A measure of variability is a summary of statistics that represents the amount of distribution in a dataset. In other words, how spread or scattered are the variables in a given dataset.

What we learned in last week’s readings is that the measure of central tendency describes a standard value, measure of variability define how far away from form the center the data points fall from the center. The context about variability relate to the distribution of a given value. Further, a lower distribution indicates that that the data points tend to more closely cluster around the center. If it is a higher distribution, the spread tends to fall farther away from the center,

The example that best resonated with me was in regard to weather, which is germane to all of us on a daily basis. Extreme weather can cause problems in seasonal weather patterns. For example, you may see a weather report where the weather person shows extreme cold in one area and heavy snow in another. The question is how you correlate the two and have a standard deviation. Oftentimes, we are frustrated and confused by the extremes more than the standard. Attempting to understand the variability from the standard or mean is a vital learning point and key data point.

Variability exits in all data. Nothing is exactly the same every time. Simply, even if you cook an over easy egg each day, you never cook it the exact same way every day. There is a difference or a variability, it is just inherent in all data.

In summary, one key outcome from the learnings or main point this week from Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018) is a single number that describes how much variation and diversity there is in the distribution. Numbers that describe diversity or variation are called measures of variability. Researchers often use measures of central tendency along with measures of variability to describe their data. In this week’s readings, we discuss five measures of variability: (1) the index of qualitative variation, (2) the range, (3) the interquartile range, (4) the standard deviation, and (5) the variance. Before we discuss these measures.

Finally, it is important to discover why the measure of variability is important in research.


Frankfort-Nachmias, C., & Leon-Guerrero, A. (2018). Social statistics for a diverse society (8th ed.). Thousand Oaks, CA: SAGE Publications, Inc.

Part B.

In light of the Covid-19 update pandemic that confronts us today are we able to measure variability to assist in the containment of the viral spread?

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