Analysing Descriptive Statistics

A research begins with formulation of research questions, this are what helps to guide the data that will be collected for the study. Data in a research can either be qualitative which consists of verbal and narrative pieces of information or quantitative where data is transformed into numerical statistics (White et al., 2016).

Variables in a research are the concepts that the researcher is interested in for instance height weight, gender among others. Variables can be categorized into two, independent which are the variables that can be changed and controlled and dependent which are the variables that can be tested and measured in a scientific experiment (Polit et al., 2017). They can also be categorized as discrete and continuous variables. A discrete variable is that one that has a fixed amount of values amid any dual points for example, asking one how many times they have been hospitalized.  A continuous variable is that one that can take up an inestimable numeral value amid any dual points for example, ‘weight’ (White et al., 2016).

There are many techniques that are used to evaluate data, some of them include probability theory and decision theory. There are two forms of errors that can arise in the course of research; there is Type 1 error that comes about when the null hypothesis is overruled when it is indeed true (Polit et al., 2017). There is also Type II error that comes about when the null hypothesis is considered as true but is in reality incorrect (Polit et al., 2017).

There is what is known as descriptive statistics in a research, this is normally referenced in a study where data are numerical. The common descriptive statistics employed by most researchers include; Frequency Distribution, Ungrouped Frequency Distribution, Grouped Frequency Distribution, Measures of Central Tendency, Measures of Dispersion, Chi-Square Test of Independence, Practice Problem Exemplar Using Descriptive Statistics (White et al., 2016).

References

Polit, D. F., & Beck, C. T. (Eds.). (2017). Nursing research: Generating and assessing

            evidence for nursing practice (10th ed.). Philadelphia, PA: Wolters Kluwer. 

White, K. M., Dudley-Brown, S., & Terhaar, M. F. (2016). Translation of evidence into

            nursing and health care (2nd ed.). New York, NY: Springer Publishing Company.