Course Project - Phase 2
Phase 1 Scenario 2 – NCLEX Memorial Hospital
PHASE 1 SCENARIO 2- NCLEX MEMORIAL HOSPITAL
Lucia Ruiz
Rasmussen College
Author Notes
This paper is being submitted on February 17, 2017 JuTon Hemphill’s Inferential Statistics and Analytics course.
Introduction
The scenario I shall be working with is whereby I am working at NCLEX Memorial Hospital in the infectious disease unit. As a healthcare professional, I need to work to improve the health of individuals, families and communities in various settings. The current situation that has posed as a problem at the hospital and raised eyebrows is that in the past few days, there has been an increase in patients admitted with an infectious disease. The basic statistical analysis shows that the disease does not affect minors hence the ages of the infected patients does play a critical role in the method that shall be required to treat the patients to impact positively on the health and wellbeing of the clients being served whether infected with the disease or associated with those infected. After speaking to the manager, we decided that we shall work together in utilising the available statistical analysis to look closer into the ages of the infected patients. To do that, I had to put together a spreadsheet with the data containing the information we shall need to carry out the analysis.
Data Analysis
From the data collected and input on an Excel sheet, there are sixty patients with the infectious disease. Of the patient’s whose data has already been collected an input on the excel sheet, the ages range from thirty-five years of age to seventy-six. There is only one patient in their thirties with the age of thirty-five. There are five patients in their forties, One forty-five, one forty-six, two at forty-eight and two at forty-nine. There are fifteen patients in their fifties, two at fifty, one fifty-two, one fifty-three, one fifty-four, four at fifty-five, one fifty-six, one at fifty-eight and four at fifty-nine. There are twenty-three patients in their sixties, five at sixty, one at sixty-two, one at sixty-three, two at sixty-four, one at sixty-five, three at sixty-eight and seven at sixty-nine. Finally, we have fifteen infected patients in their seventies, six at seventy, three at seventy-one, three at seventy-two, one at seventy-three, one at seventy-four and one at seventy-six. From the graph in Figure 1 below, the horizontal axis depicts the age group of patients infected with the disease and the vertical axis depicts the number of patients in the age group infected with the disease.
Figure 1
Data Classification
The qualitative variables in our data analysis would be the names of the patients infected with the disease while the quantitative data would be their ages, number of patients in each age category or age bracket that are infected with the disease and the number of patients in each specific age that are affected. The graph in Figure 1 above shows a quantitative analysis of the data. The discrete variables in this analysis are the number of patients infected with the disease because they could continue to increase to a finite number and we could still count them and add them to the analysis. Our continuous variable in this analysis is the age. For our analysis, we shall use the age in years. In our data set, the qualitative data has been omitted. The quantitative data is being measured based on the number of patients counted to have the disease and their ages. We have classified them in clusters of five in the graph to visualise the analysis. The discrete variable is being measured by the number of patients already diagnosed with the diseases and the continuous variable which is the age is currently being measured annually.
The Measures of Centre and Variation
The measures of centre are the values in the middle of the data set which is the focal point. It can be determined using the mean medium and the mode. The mean defines the very centre and could also be defined as the average point. In our data analysis, it is important to figure out the centre of variation because it shall assist us to determine the most common age bracket that has been infected with the disease and shall therefore help us narrow down to the cause and effect faster by concentrating on the mean median and the mode of the data analysis.
The measures of variation are those that are utilised to describe data distribution and the variation between random variable. They show the range between the greatest and the least data values which are commonly known as the difference. Quartiles can be used to measure variation as they divide the data set into four equal parts. They are important as they assist in measuring probability of occurrence. In our case, they could be used with the most common age group to have the infectious disease and random variables such as their residents, their places of work and their activities or eating habits could be used to further analyse the data to figure out the source, the cure and the best way to prevent the spread. Arithmetically, it is derived by the variance and standard deviations of a data set.
Calculation of the Measures of Center and Measures of Variation
The Mean
The mean is the average of the data set and normally the centre of the data.
The Mean = Total of Ages / Sample Size
The Mean = 3705 / 60 = 61.81667
The Mean = 61.82
The Median
The Median = The Value in the Centre of the data which in our case is the value in the centre of the ages. There are 60 patients hence our median shall be the age of the 30th patient.
The Median = 61
The Midrange
The Midrange = The Midpoint between the lowest and the highest values. In our data set, the lowest age value is 35 and the highest is 76
The Midrange = (35+76) /2
The Midrange = 111/2 =55.5
Midrange = 55.5
The Mode
The mode is the most frequent value in the data set. Our data set is composed of the ages of the infected patients with the disease. The most frequent age is 69 which has 7 patients
Mode= 69
The Range
The range of a data set is the difference between the highest and the lowest values in the set. Our data set is composed of the infected patient’s ages. The highest value is 76 and the lowest is 35.
The Range = 76 -35
The Range = 41
The Variance
Measures how far the data are from the mean. In this case the variance is
4698.9833/60 = 78.3164
The Standard deviation is calculated from the SQRT of the variance. In this case = 8.85
Conclusion
The conclusion from our study of the patients infected with the infectious disease in NCLEX Memorial Hospital is that they are currently sixty. The most infected patients range between the age of sixty and seventy-five but the highest number of infected patients are the age of sixty-nine as they are seven. The disease seems to be attained by the elderly from the age of thirty-five and seventy-six with the average age being sixty-one. Children, teenagers, the youth and the extremely elderly are not prone to the infectious disease.