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Pages:
1 page/β‰ˆ275 words
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Style:
APA
Subject:
Mathematics & Economics
Type:
Essay
Language:
English (U.S.)
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Date:
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Topic:

Central Tendency and Variability

Essay Instructions:

As we continue on with descriptive statistics,
1.Identify three uses for a frequency distribution. Please provide realistic health related examples.
2.Briefly identify the differences between a normal, positive and negative skew. How does this skew or distribution curve relate to standard error? What does the standard error mean for the results? Feel free to use and example to explain your answer.
Michelson, S. & Schofield, T. (2002). Chapter 1: Description. Data Dispersion, Noise and Error (pages 18-26). In: The Biostatistics Cookbook: The Most User-Friendly Guide for the Bio/Medical Scientist. Kluwer Academic Publishers. Available in Ebrary, accessed via Trident’s online library.
Norman, G., and Streiner, D. (2008). Chapter The Third: Describing the Data with Numbers: Measures of Central Dispersion. In: Biostatistics The Bare Essentials. 3rd Edition. BC Decker Inc. PMPH USA, Ltd. Shelton, CT. eISBN: 9781607950585 pISBN: 9781550093476. Available in Ebrary, accessed via Trident’s online library.

Essay Sample Content Preview:

Central Tendency and Variability
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Identify three uses for a frequency distribution
One of the uses of a frequency distribution is to show the measures of location including, the mean, median, mode as well as the standard deviation which shows dispersion. In any case, presenting frequencies graphically through histograms represents the nature of the frequency distribution (Michelson & Schofield, 2002). The descriptive statistics further highlight on the characteristics of data. Health statistics can show the frequency of observations about outcomes on infection based on exposure to risk factors to represent the descriptive characteristics.
Frequency distributions facilitate standard hypothesis testing, since descriptive statics highlight on testing the observable phenomena. Since the frequency distribution also focuses on the cumulative percentages for various frequency counts, it provides a basis to test the likelihood that certain observations would be present in a population (Norman & Streiner, 2008). For instances the case of different rates of flu following an outbreak would be tested by focusing on the extent to which one intervention has been more beneficial than others in reducing infection rates.
Since the frequency distribution describes a variable at a time, it forms the basis to measure variability of data. This is particularly with the range and variance which show dispersion. For health practitioners this is important to indicate anomalies in obse...
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