hypotesis testing

Scenario of NCLEX Memorial Hospital where records of the patients with infectious disease are studied in this paper, client number, infection disease status and age of the patient are recorded. Patients are faced with the same infectious disease. The age of the patients is the vital issue which is considered in statistical calculation. The data shows that there are 60 patients who are faced with the same infectious disease according to NCLEX Memorial Hospital, the age of the patients range from 35 years of age to 76 years of age.

All variables can be classified as quantitative variables. The quantitative variable in the data set is the age patients. Quantitative variable represent a measurable quantity because they are numerical. For example, the age of the patients are attained because it can be numbered. Therefore, age would be a quantitative variable. The continuous variable is the number of patients that range from 1 to 60; the number of the patient would be an example of a continuous variable, since the patient age could take on any value between 1 and 60. Infectious disease variable represent a discrete variable, when a patient is admitted he/she can be either infected or not infected.

The levels of measurements are the interval, nominal and the ordinal level of measurement. In the interval level first quantitative application of numbers happens. Observations are classified into mutually exclusive and comprehensive categories that have some clear relationship among them, and the relationship between the categories is known and exact. Ordinal level of measurement uses symbols to classify observations into categories that are not only mutually exclusive and comprehensive, (Christmann,2009). In addition, the categories have some clear relationship among them. Nominal level measurement also uses symbols to classify observations into mutually exclusive so that observations does not fall into more than one category and comprehensive categories so that observations falls into some category.

Mean, median and mode are the measurement of center. The importance is to find the average of everything: that is finding the average age by giving the idea of what is most common in the data. The most vital thing is calculating the middle of the group observed. Examples of measures of variation are range, variance, and standard deviation and the major uses are to estimate the corresponding parameter.

Mean = 3709/60

=61.82 this means that when the sum of age is calculated, is same as 60 lots of 61.82

Median

= (61+62)/ 2 =61.5

This shows the middle age of the patients infected with the disease.

Mode

=69, this is the most appearing number which means the infectious disease affect so many people at this age.

Midrange

= (76 + 35)/ 2

=55 this is the mean of the minimum and maximum of the values.

The Range is the difference between the lowest and highest values.

(76-35)=

Range= 55.5

Variance

=79.64

Standard deviation is the square root of standard deviation

=square root of variance 78.32

=8.924

Scheming data in a frequency distribution shows the general shape of the distribution and gives a general sense of how the numbers are clustered. Several statistics can be used to represent the "center" of the distribution. These statistics are commonly referred to as measures of central tendency, (Helsel, 1993). The range and standard deviation are all measures that show the amount of variability within a dataset. The range is the easiest measure of variability to calculate but can be confusing if the dataset contains extreme values.