Today, with the advent of new technologies, it is found that the expectations of the patients from healthcare organizations have increased. Also, the nursing and the support staff need to get trained on the modules of leadership, management, and these new technological modules that will not only allow them to perform better but will also ensure meeting the expectations of the patients in a given healthcare environment (Johnson, 2016). The business enterprises have gone through an online approach for the purpose of easily exchanging data and thereby saving time, efforts, resources, and money. Even, the healthcare sector has implemented new Healthcare Information Technologies for the purpose of improving the overall efficiency in a given operational environment. However, there is a need to determine how data science plays a vital role in improving the lives of patients from the technology perspective. Also, there is a need to determine how data science will assist the physicians and other medical staff in tackling difficult challenges like influenza in a given community.

Quantitative Research Question and Hypotheses
Research Question of Apply Descriptive Statistics

What is the role of data science in improving the lives of patients and assisting the medical staff from a perspective of technology?

Hypothesis of Apply Descriptive Statistics

H0: Data science does not improve the lives of patients or assist the medical staff from a perspective of technology

H1: Data science improves the lives of patients and assists the medical staff from a perspective of technology

Variables to be measured of Apply Descriptive Statistics

            There are three major variables in this research study i.e. Data science, patients’ lives, and medical staff assistance. The first variable i.e. data science is dependent variable while other two variables i.e. patients’ lives and medical staff assistance are the independent variables. Data science refers to the multidisciplinary blend of technological, algorithm development, and data inference in order to solve the analytically complex problems. On the other hand, patients' lives refer to the lives of patients that is assumed to be improved with the help of data science and medical staff assistance is a help to physicians, surgeons, and other medical staff that is assumed to be assisted through data science. All of the three variables will be measured through indirect measurement method as the values will be obtained by measuring the relationships between the physical quantities (Giudici, et al., 2013).

Table 1

Data Scale and Data Type of Apply Descriptive Statistics

            The data for these variables will be collected through a survey questionnaire using a five-Likert scale where 1 referring to strongly disagree, 2 for disagree, 3 for neutral, 4 for agree, and 5 for strongly agree. The questions will be based on the research question. The data scale of the above three variables is continuous because the values of this data set belong to a set that belongs to an infinite or finite interval because it is based on five-Likert scale. The data type of all of the above three variables is ordinal because this is a categorical data where all of the three variables have ordered and natural categories and a distance are not known between the categories (OSWEGO, 2019).

Mean, Median, and Mode of Apply Descriptive Statistics

            Specific to each variable, mean, median, and mode tell the almost same thing. Mean, median, and mode tell the averages of the data; mean tells the average value of these three variables, median tells the middle value of these three variables, and mode tells the most repeated value of these three variables. For the above mentioned research question, if the value of mean, median, and mode are not same and turned out to the different values then the best representation of data will be median because the data type of these variables is ordinal and the median is the best measurement of the tendency for ordinal data because such data has a skewed distribution (OSWEGO, 2019).

Standard Deviation and Range of Apply Descriptive Statistics

                The standard deviation is a statistical test showing the description of the spread of data that how widely the data is distributed about the expected value. If the standard deviation for variable 1 i.e. data science is very small then it means that the point of the data is very close to the mean value or expected value of the data. A very small value of standard deviation indicates that more of the values in the dataset are clustered about the average or mean of the data. This comparison of the dataset to the means tells various things that depends on the nature of data. Furthermore, if the standard variable for variable 3 is very large then it means that the point of data in variable 3 is spread out over the broad values’ range. Moreover, the range of the data provides the clearer picture of the data distribution because it indicates the smallest and largest value of the data, one can easily know that the values of some specific dataset lie within these maximum and minimum value. The relative size of the standard deviation matters less as it tells about the data structure that varies nature to the nature of the data (Giudici, et al., 2013).

Histograms of Apply Descriptive Statistics

            A histogram tells the distribution of the variable and it plots quantitative data with the data range. If the histogram or bar graph for variable data science is somewhat flattened in the middle with nearly vertical tails instead of being a perfect bell curve then this visualization of the graph indicates that the distribution of dataset is kurtosis. While on the other hand if the histogram or bar graph for patients’ lives has the high point (hump) shifted to the left and the tail off to the right is elongated then the visualization of that graph suggest that distribution of the data set is skewed (Giudici, et al., 2013).