Introduction to Probability Theory and Heath Statistics

Module 2 - SLP
DESCRIPTIVE STATISTICS PART I: NORMAL CURVES, VARIABILITY, AND PLOTTING
For the Second SLP, using the data that you collected for the Module 1 SLP, please do the following:
Calculate the mean, median, and mode of the measurements taken in Module 1 SLP. Be sure to express each value of central tendency in units.
Discuss whether the values are higher or lower than you would have expected
State which measure of central tendency you think most accurately describes the variable that you measured. Provide a thorough explanation.
Conduct a scholarly search on the internet to find reported health statistics on the variable that you are measuring. For example, if you are measuring your total daily caloric intake, American Dietetic Association. Identify the source.
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.
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This is SLP Module 1 assignment instructions: Your specific assignment for this week is to select one type of quantitative health datum to collect from your own life. Some examples of data to collect could be:
How many minutes do you spend exercising each day?
What is your total daily caloric intake in calories?
What is your resting heart rate in beats per minute?
How many ounces of water do you drink each day?
What is your estimated total caloric expenditure from exercise each day?
What is your estimated daily intake of saturated fat in grams?
If you have the equipment available, you could even take measurements of your blood pressure. Be sure to choose something that varies measurably from day to day.
Task: Describe the data you are going to collect. Be sure to specify the units of measurement, and state how it will be gathered. Start collecting data today so you have can have at least 10 observations, preferably more.
Note: you only have to choose one variable, and then collect at least 10 days worth of data on that one variable. For example, if your variable is how many minutes you spend exercising each day, simply record the number of minutes that you spend exercising each day during the sampling period. Be sure to save this data for use in remaining SLP assignments. The more data points that you gather during the session, the better.
Submit your paper by the end of this module.
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.
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This is also sources they gave us:
Data can be classified into various types (Norman and Streiner, 2008):
Nominal Variable: consists of named categories with no implied order among the categories
Ordinal Variable: consists of ordered categories where the differences between categories cannot be considered equal
Interval Variable: has equal distances between values, but the zero point is arbitrary
Ratio Variable: has equal intervals between values and a meaningful zero point
Measures of Health Status
People vary with respect to a host of factors, such as gender, age, height, and weight. In a health research study, a variable is any factor being observed or measured.
For example, various measures may be used to compare the Health Status two or more populations during the same period of time (Horton, 2004)
Life-Expectancy
Under-5 Mortality
Health Adjusted Life Expectancy
Disability Adjusted Life Years
Other than the factors described above, can you think of variables that are relevant to the Health Sciences?
The quantitative vs. qualitative distinction: If we want to ask a question about the health of a population we might ask a question that is answered by giving a number; the corresponding variable would be quantitative (Freedman et al. 1978). Those questions that cannot be answered with numbers, for example, “do you have a personal history of stroke?” are qualitative.
One of the techniques that you will learn in this course is how to display data visually.
Please proceed to the background materials for this Module.
Sources:
Freedman, D., Pisani, R. and Purves R. (1978). Statistics. W.W. Norton & Company, Inc. New York, New York. ISBN 0-393-09076-0.
Horton, L. (2004). Chapter 1: Introduction to Health Statistics. In: Calculating and Reporting Healthcare Statistics. American Health Information Management Association
Norman, G., and Streiner, D. (2008). Chapter The First: The Basics. (pages 2-6). Biostatistics The Bare Essentials.
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Reading material: Cook, A., Netuveli, G., & Sheikh, A. (2004). Basic Skills in Statistics: A Guide for Healthcare Professionals. London, GBR: Class Publishing. eISBN: 9781859591291. Available in Ebrary, accessed via Trident’s online library.
Norman, G., and Streiner, D. (2008). Chapter The First: The Basics. (pages 2-6). 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.
Module 2 Overview:
Module Overview
As we learned in Module 1, data can be classified into various types. We now turn our attention to statistical techniques that Health Scientists use to analyze data. At this point we concern ourselves with descriptive statistics to examine a sample. Later in the course we will turn our attention to inferential statistics - those techniques used to make generalizations to a wider population (Dancey et al., 2012).
Suppose we want to find out whether stroke patients differ from heart attack patients in their ability to come to terms with their illness. We could design a questionnaire that measures the ability of patients to cope after they have left the hospital (Dancey et al., 2012). In the example below, suppose that a higher score means that a patient has a higher coping ability.
Examining these scores, think about how you would describe them to a friend who couldn’t see them. What would be a typical score for stroke? As Norman & Streiner (2008) explain, a measure of central tendency is the typical value for a data set. It is important to study the concepts of Range.
When we perform many statistical tests, we are assuming that the data come from a normal distribution.
When describing how data are distributed, we concern ourselves with Shape (e.g. symmetry, skew, modality), Center (e.g. mean, median, mode), Spread (e.g. Range, Interquartile Range), and Outliers.
The Central Limit Theorem posits that regardless of how data are distributed, if we were draw a reasonably sized sample, then the distribution of the means of those samples would always be normally distributed (Norman & Streiner, 2008).
There are many ways to plot data. A histogram is one useful way that we can visually display a large amount of data. In a histogram, the relative frequency of observations is displayed as a bar graph. Notice in the example below that the histogram illustrates the underlying distribution of data (i.e. Body Mass Index for Patients), revealing the “shape” of the data and variation in the data.
A continuous variable is one that can take on any value between two specified values. Otherwise, it is called a discrete variable (i.e. one that can only take on a finite number of values).
In the next module we will examine in greater depth statistical concepts, of mean and deviations from the mean as measures of variation and dispersion in data.
Sources:
innesota Department of Health. Histogram. Retrieved July 1, 2013 from http://www(dot)health(dot)state(dot)mn(dot)us/divs/cfh/ophp/consultation/qi/resources/toolbox/histogram.html
Norman, G., and Streiner, D. (2008). Biostatistics The Bare Essentials. 3rd Edition. BC Decker Inc. PMPH USA, Ltd. Shelton, CT. eISBN: 9781607950585 pISBN: 9781550093476.
Villenueve, P. (2002). Normal Distributions: Encyclopedia of Public Health. Retrieved July 1, 2013 from http://www(dot)enotes(dot)com/normal-distributions-reference/normal-distributions.
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Module 2 required reading: I hope this helps
Required Reading
Michelson, S. & Schofield, T. (2002). Chapter 1: Description. Measures of Central Tendency (pages 9-17). 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 Second: Looking at the Data: A first look at Graphing (pages 7-18). 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.
Norman, G., and Streiner, D. (2008). Chapter The Fourth: The Normal Distribution (pages 31-36). 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.