# Introduction to Probability Theory and Heath Statistics (Statistics Project Sample)

Module 3 - SLP DESCRIPTIVE STATISTICS PART II: CENTRAL TENDENCY AND VARIABILITY For the third component of the Session Long Project, write a 2- to 3-page essay in which you begin to discuss the spread of the data that you‘ve been collecting by computing the variance of distribution of the measurements that you’ve taken so far. Show your work. Be sure to discuss variance of distribution in your response. SLP Assignment Expectations Use the information in the modular background readings as well as resources you find through ProQuest or other online sources. Please be sure to cite all sources and provide a reference list at the end of the paper. Submit the paper as a Word document through the link provided for the assignment. Length: 2–3 pages typed and double-spaced. Module 3 - Background DESCRIPTIVE STATISTICS PART II: CENTRAL TENDENCY AND VARIABILITY Required Reading 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. Additional Reading (Optional) McGraw Hill.com (yr. unknown). Chapter 2: Describing Data: Frequency Distributions and Graphic Presentation. Retrieved from http://highered.mcgraw-hill.com/sites/dl/free/0070880441/40846/Chapter2.pdf Additional Resources (Optional) The Johns Hopkins University and John McGready (2009).Continuous Data: Numerical Summary Measures; Sample Estimates versus Population Measures. Retrieved from http://ocw.jhsph.edu/courses/IntroBiostats/PDFs/IntroBiostats-sec1c_McGready.pdf The Johns Hopkins University and John McGready (2009). The Theoretical Sampling Distribution of the Sample Mean and Its Estimate Based on a Single Sample. Retrieved from http://ocw.jhsph.edu/courses/IntroBiostats/PDFs/IntroBiostats-sec3b_McGready.pdf The Johns Hopkins University and John McGready (2009). Estimating Confidence Intervals for the Mean of a Population Based on a Single Sample of Size n: Some examples. Retrieved from http://ocw.jhsph.edu/courses/IntroBiostats/PDFs/IntroBiostats-sec3c_McGready.pdf

source..Michaela E. Tyndell

BHS 220 Introduction to Probability Theory and Heath Statistics

SLP Descriptive Statistics Part II: Central Tendency and Variability

Introduction to Probability Theory and Heath Statistics

Professor: Sharlene Gozalians

September 08, 2014

Variability is an important measure representing the spread of data, and two sets of data may have the same mean, but it is rare to have the same spread. The spread of data shows where the data is sparse, dense or spread out (Norman, G & Streiner, 2008). Dispersion, spread and variability all have the same meaning representing the spreading out of observation distribution. There are various measures of variability, with the range the most common. Another common measure is variance which represents how the values are distributed when compared to the middle of the distribution. The mean is a measure of central tendency, and it is also represents the middle of a distribution.

DayExercise timedeviation squared deviation 112-416213-39315-114171151824620416715-118171191600101711Mean16050Median16.5Mode17Range8

The range represents the difference between the maximum and the minimum value (20-12) = 8 minutes. Even though, there are limited uses to using the range, it still helps to identify the threshold and critical low for a frequency distribution. At times, one can identify where there has been errors when recording data, as the spread should not be more than the value of eight minutes. The major drawback of the range is that it is affected by extreme values. Hence, the value should be used in conjunction with the standard deviation and the variance. The measure complements variance, which is the main measure of the spared of data.

The variance is a good measure of variability, and depends on the deviation from the mean and the frequency. It is the average squared deviation divided by the...

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