UKCustomPapers | Shortcomings Of Central Tendency

Shortcomings Of Central Tendency

The mean, median, and mode are frequently referred to as the measures of central tendency. All three of these are used commonly, especially by the media when trying to make a point or persuade an audience to some point of view. However, each of these three statistical measures has their own shortcomings.

For your own original contribution to this Discussion Board, complete the following:

Research the shortcomings of measures of central tendency. Summarize your findings and cite your sources.
Find an example where a mean, median, or mode was used by the media or a company to make a specific point. Evaluate this use and then share your evaluation with the class. Be sure to specifically discuss any caveats or risks associated with the way the organization in your example used their central tendency metric.
Discuss if you think the right measure was used. Share a recommendation for a better measure if you think there is one.

Sample Answer

Shortcomings of Measures of Central Tendency

Measures of central tendency, such as the mean, median, and mode, are frequently used to summarize a set of data by providing a single value that represents the “typical” or “middle” of the data. However, each of these measures has its own shortcomings that can affect their interpretation and use.

Mean: The mean is the most widely used measure of central tendency, but it is sensitive to outliers, which are data points that are significantly different from the rest of the data. Outliers can pull the mean away from the true center of the distribution, making it an inaccurate representation of the typical value.
Median: The median is less sensitive to outliers than the mean, but it does not use all the information in the data. The median simply identifies the middle value in the data when arranged from smallest to largest. This means that it ignores the values of all the data points that fall below or above the median.

Full Answer Section

Mode: The mode is the most frequent value in a dataset. It is a useful measure for nominal data, which is data that cannot be meaningfully ordered or ranked. However, the mode can be misleading for data with multiple modes or for skewed distributions.

Example of Misuse of Measures of Central Tendency

In a recent article, a news organization reported that the average salary for software engineers in the United States is $120,000 per year. However, this figure is based on the mean salary, which is likely inflated by a small number of high-earning software engineers. The median salary for software engineers is more likely to be closer to $80,000 per year.

This example illustrates the dangers of using the mean without considering the distribution of the data. In this case, the mean is not a representative value for the majority of software engineers, as it is skewed by a small number of outliers.

Recommendations for Choosing the Right Measure

The choice of which measure of central tendency to use depends on the nature of the data and the question being asked. If the data is normally distributed and there are no outliers, then the mean is a good choice. If the data is skewed or there are outliers, then the median is a better choice. The mode is only useful for nominal data or data with a single mode.

In general, it is important to consider the limitations of each measure of central tendency before using it to summarize data. It is also important to be aware of the potential for misuse of these measures by the media or other organizations.

This question has been answered.

Get Answer

Our Free Services

Paper Formatting

No Lateness!

Our Guarantees

Shortcomings Of Central Tendency

This question has been answered.

Our Services

Daily Statistics

Why Choose Us