elementary biostatistics

Discussion 1:
You reviewed some elementary biostatistics this week. Based on our readings this week, describe (or define) at least 2 different types of quantitative methods.
Cite and reference your work using APA format
Use your readings on biostatistics this week to develop your discussion post
Remember to spell-check your work
Use at least one scholarly resource (note: wikipedia is not a scholarly reference)
Minimum word limit: 250 words
Summarize your work using your own words

Below is this week’s reading material.
I also attached a link and reference below to help with the writing.

In this course you will conduct your own quantitative analysis with a dataset that will be provided to you by the instructor.
This week serves as a review of some of the biostatistics concepts you explored in your prerequisite course, STAT 230. You will review these concepts and consider which operation you want to use in your quantitative analysis assignment. This week’s review will focus on how to performdescriptive statistics, which are used to describe the distribution of and relationship among variables.
Univariate Associations
You can use descriptive statistics to understand the distribution of a variable with secondhand data. Secondhand data gives you the opportunity to re-analyze variables in an existing dataset. For instance, you can select a variable you want to explore, such as the income levels or race/ethnicity of patients at a given hospital, for a specific dataset. Graphs or bar charts are common ways to show the data (see figure 3.1).
Figure 3.1
Bar Chart Example

Based on the data above, we can determine that persons with incomes between $51,000 and $100,000 are likely to visit Hospital X.
Cross-Tabulations
If we want to examine how two variables are related to each other, we can perform a cross-tabulation. A cross-tabulation is a statistical process that includes data tables. A cross-tabulation allows you to examine interrelationships between variables. The result is a contingency table. We can perform a cross-tabulation if we want to find out the ages at which men and women have the highest cardiovascular admission rates (see table 3.1).
Table 3.1
Cross-Tabulation Contingency Table Example
Age Male Females Totals
0–18 0 1 1
19–30 1 2 3
31–45 20 18 38
46–64 70 65 135
>65 62 70 132
Totals 153 156 309
Based on the cross-tabulations in table 3.1, we can conclude that cardiovascular admissions are higher among men who are between the ages of 46 and 64 and in women who are older than 65. The table also tells us that more women than men are admitted to Hospital X for cardiovascular diseases.
Frequency Distributions
You can also examine and display the distribution of one variable using a frequency distribution. Frequency distributions display the number of times (or cases) a variable appears in a dataset as a percentage. For example, if we wanted to know which age group had the highest cardiovascular admission rates in 2013 for a given hospital we would examine the frequency at which different age groups were admitted for cardiovascular episodes and display the results in a bar chart (figure 3.2).
Figure 3.2
Frequency Distribution Example

Based on the data in the above bar chart, we can conclude that persons who are 65 years old or older have the highest admittance rates for a cardiovascular episode in Hospital X: 32 percent.
Measures of Central Tendency
Data can be analyzed using measures of tendency, which include three types of statistics: mean, median, and mode (see figure 3.3). Each measure is defined by Chambliss and Schutt (2013):
Mean. The mean is the arithmetic, or weighted average computed by adding up the value of all the cases and dividing by the total number of cases. The mean tells us the average number of nurses needed to establish efficient and quality patient services on an inpatient floor.
Median. The median is the position average, or the point, that divides a distribution in half (the 50th percentile). The median age of physicians in Hospital X can be calculated.
Mode. The most frequent value in a distribution; also termed the probability average. The mode can be used to describe the type of injuries most commonly seen in a hospital emergency room.
Figure 3.3
Measures of Central Tendency

References
Chambliss, D. F., & Schutt, R. K. (2013). Making sense of the social world: Methods of investigation, fourth edition. Thousand Oaks, CA: SAGE Publications, Inc. Retrieved fromhttp://www.sagepub.com/upm-data/46056_Pages_from_Chambliss_%284e%29_Chapter_8.pdf
Discussion 2:
Learning Activity #1
Read the article on the 27 reasons people do bad things. Cite three of the reasons from your personal experience or observation which you feel are particularly troublesome for the average person.
http://www.businessinsider.com/27-psychological-reasons-why-good-people-do-bad-things-2012-8#tunnel-vision-1
*Use the left/right arrow located above the image to check all 27 reasons!

Learning Activity No. 2
What side do you take on whistleblowing- including Mr. Snowden who worked for the agency whose fort this building abuts? Is your view that whistleblowers are generally disloyal to their employer and just seeking money or publicity? Or do you view whistle blowers as heroes? Of course it may depend on the facts of a particular case, but in general how do you stand on this issue? Under what circumstances, and for how long should a whistleblower attempt to resolve matters INSIDE the company before going to the press or law enforcement authorities? Give a hypothetical or actual example.
http://www.bostonreview.net/books-ideas/scheuerman-snowden-greenwald-harding-sagar
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