STATISTICAL CONCEPTS. Health, Medicine, Nursing Essay
STATISTICAL CONCEPTS
Assignment Overview
For a healthcare professional, the review of data is unavoidable and it is imperative to not only identify types of data, but also to know how the data can be measured (through using variables parts of the data as key variables). There are four scales of measurement: nominal, ordinal, interval, and ratio.
In addition, the use of statistical analysis is vital. While statistical analysis can range from simple to complex, the most fundamental elements of statistical analysis are based upon mean, median, mode, and standard deviation.
Case Assignment
Using the link below, access and download the DRG Summary for Medicare Inpatient Prospective Payment Hospitals (data) provided by the U.S. Centers for Medicare & Medicaid Services:
https://www(dot)cms(dot)gov/Research-Statistics-Data-and-Systems/Statistics-Trends-and-Reports/Medicare-Provider-Charge-Data/Downloads/Inpatient_Data_2015_XLSX.zip
This is a two-part assignment.
Part 1:
In 1 page, complete the following:
Define and explain the 4 main types of scales variables can be measured on: (1) nominal; (2) ordinal, (3) interval, and (4) ratio scales.
Using the chart below or creating your own, identify each of the 12 columns on the spreadsheet as nominal, ordinal, or interval/ratio data.
Part 2:
In 2 pages, complete the following:
Define and explain the differences among mean, median, mode, and standard deviation.
Using the excel data, sort Column A, DRG Definition, to only show “001 - HEART TRANSPLANT OR IMPLANT OF HEART ASSIST SYSTEM W MCC” records.
For this part of the assignment, you will only use data from Column I, Total Discharges, and Column L, Average Medicare Payments.
Using excel, calculate the mean, mode, median, and standard deviation for Column I, Total Discharges.
Using excel, calculate the mean for Column L, Average Medicare Payments.
Present your findings in your paper in the chart below, or one that you have created.
Explain what each calculation means in terms of the data presented. (Note: The data is DRG Summary data for Medicare Inpatient Prospective Payment Hospitals for 2015. You will need to explicitly explain the calculation findings based on the dependent variable, heart transplants and/or implant of heart assistance system. An example of such an explanation would consist of the following, “I found a mean of 37 for DRG 007 – Lung Transplant. This data shows that on average in 2015, 22 Medicare patients were discharged for lung transplants.”
Assignment Expectations
Conduct additional research to gather sufficient information to justify/support your report.
Limit your response to a maximum of 3 pages (title and reference page is not included in page number count).
You may use the following source to assist in your formatting your assignment: https://owl(dot)english(dot)purdue(dot)edu/owl/resource/560/01/.
For additional information on reliability of sources review the following source: https://nccih(dot)nih(dot)gov/health/webresources.
This assignment will be graded based on the content in the rubric.
Statistical Concepts
Name
Course
Instructor
Institution
Date
Part 1:
Define and explain the 4 main types of scales variables can be measured on: (1) nominal; (2) ordinal, (3) interval, and (4) ratio scales.
1 nominal
The nominal (categorical variable) scale consists of two or more mutually exclusive categories. Each category is usually assigned a label (or the name of an attribute) of an element or a code number without quantitative meaning and there is no order. Examples include Sex: 1) male;2) feminine or is "male" or "female" and married or not married.
2 ordinal
When the data shows the properties of the nominal data, but the ranking order (or hierarchy) of the nominal data also makes sense, then this is an ordinal scale and like the nominal scale it is qualitative. For instance, a variable that measures the quality of a service where the variable can take integer values ββfrom 1 to 5 with value 1 as the worst and 5 the best is an ordinal scale of measurement.
3 Interval
On an interval scale, the data has the properties of ordinal data, but in turn the separation between the variables makes sense. This data type is always numeric, and the value zero does not indicate the absence of the property (McClave & Sincich 2018). For instance, the average temperature of a city in degrees Fahrenheit or centigrade is an interval scale of measurement. The higher numbers represent higher temperatures and the order matters as is the differences between the temperatures.
4 Ratio
On a ratio scale, the data has all the qualities of the interval data, and the ratio between them makes sense. This requires that there is real absolute zero value of the scale indicates the absence of the property to be measured. Examples of these types of variables are the weight of a person and a person's salary.
Using the chart below or creating your own, identify each of the 12 columns on the spreadsheet as nominal, ordinal, or interval/ratio data.
DRG Definition
Provider Id
Provider Name
Provider Street Address
Provider City
Provider State
Provider Zip Code
Hospital Referral Region (HRR) Description
Total Discharges
Average Covered Charges
Average Total Payments
Average Medicare Payments
Nominal
Nominal
Nominal
Nominal
Nominal
Nominal
Nominal
Ratio
Ratio
Ratio
Ratio
* The first eight columns are qualitative and the next four are quantities (Total Discharges, Average Covered Charges, Average Total Payments and Average Medicare Payments)
Part 2:Using excel, calculate the mean, mode, median, and standard deviation for Column I, Total Discharges
Total Discharges
Mean
36.82
Mode
11.00
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