Answer

Data Analysis and Results

Descriptive analysis refers to the act of grouping data into a form. This particular grouping is based on known variable tendencies throughout the set, and understanding the relationship between them. It is understanding the behavior of particular elements in the data set which in turn helps in statistical analysis (Lester et al., 2020). Such variables include the mean, median and least variables in the set. Some of the measures of descriptive analysis include measures of central frequency, dispersion or variation and position.

       Inferential analysis in statistics, on the other hand, refers to the sampling of a larger data set like a population and representing it in a smaller sample size with the same characteristics. It is based on the general assumption that a large population size must incur a margin of error during research and may therefore be represented in a smaller size with less errors incurred (Lester et al., 2020).  An example is representing certain aspects of the population of a country with percentages and graphs which accounts for and draws its information from the larger population statistics.

                Qualitative analysis of data refers to the measurement of the how and what as opposed to the numerical values that it has. It is impossible to, therefore, measure qualitative data and it cannot be used on a larger population size as a result (Jackson & Bazeley, 2019). In nursing, for example, it is noting that certain patients respond with certain side effects to a certain drug, and not looking at the number of patients affected by the effect. A nurse may benefit to know that a certain drug X can induce sleep pain inpatients for example and this is more clinically significant in its use as opposed to just understanding the number of people who used it in a day. It is, therefore, important to know the clinical significance as opposed to the statistical one in nursing so as to know the how and why as well.