KP Research Series
KP Research Series
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- Define and discuss why reliability and validity are important in research.
In research studies, reliability refers to the consistence across items to ensure internal consistency, across test-retest reliability and across the researchers. Validity on the other hand refers to the extent which the study results score will represent the variables in the study. Validity thus represents the judgement of various types of evidence. According to Kaiser Permanente research, an instrument that is not reliable, cannot definitely be valid (Kiaser Permente, 2020). This means that in nursing research study, reliability is very important as it provides direction on how the study has been able to meet the hypothesis which will also be able to ensure that the study results are often due to the study in regard to any possible extraneous variables. In the event that the study is reliable, it is going to ensure a possible implication in regard to other areas related to the study subject which are very important in improving the study areas. Reliability in research is also very important as it will be used in coming up with further research in the identified field.
According to Kaiser Permente, reliability has three categories, which is Equivalence, stability and internal consistency; all these categories makes up the credibility in the data collection of the study(Kiaser Permente, 2020). It is important since it is able to show the level to which a study measure is to what it is required to measure to validate (Kiaser Permente, 2020). There is internal and external validity which are able to summarise the study findings. Both types of validity are important in research as it analyses the meaningfulness, appropriateness and usefulness of the research study.
- Discuss how a particular data collection the technique is chosen, and share which one you will use and why.
Data collection techniques include structured and non-structure. Structured look at quantitative data and the one collected from participants, the collection techniques can be observations, interviews and self administered questionnaires. Unstructured data collection usually makes use of qualitative research studies and the data collected from research participants (Kaiser Permente, 2020). To choose a particular data collection technique one needs to first choose what the details of what one is seeking to collect. It will also be important to make a decision on the type of information that one is going to cover and who you would want to collect it from and the amount of data that one is going to required. After this is done, one can begin to formulate plans on ways of collecting the data. During the early stages of data collection and planning, it will also be important to know the time frame, this is when one is going to choose the data collection methods as this will also provide an idea of the data collection strategy (Kaiser Permente, 2020). To ensure that the right data collection method has been selected, it is important to consider the type of information that one is going to collect and time required to obtain in among other factors to be determined.
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- Define data analysis, and discuss the difference in the two categories of data analysis
Data analysis is the process of systematically applying logical and statistical techniques to illustrate, evaluate and recap or condense data. The data analysis procedure is used in providing a way of coming up with inductive from the collected data and single out the areas of interest from the fluctuations of statistics. There several categories of data analysis which includes the statistical analysis which makes use of past data in a way of dashboards. Statistical analysis usually includes analysis of data, interpretation, presentation and discussion of the findings (Kaiser Permente, 2020). Also there is the descriptive data analysis which indicates the deviation and mean for data, including frequency or percentage of the collected data.
References
Kaiser Permente. (2020). Part 13_Data Collection Methods HTML5. Retrieved from https://kpnursing.org/_SCAL/research/selfstudyseries/Part%2013_Data%20Collection%20Methods%20HTML5/presentation_html5.html
Kiaser Permente. (2020). part 12_Data Collection. Validity and Reliability HTML5. Retrieved from https://kpnursing.org/_SCAL/research/selfstudyseries/Part%2012_Data%20Collection%20HTML/presentation_html5.html
References
Edison, J. (2011). Research Methodology in Nursing. doi:10.5005/jp/books/11361
Hansell, P. (2017). Advances in Nursing Research Methodology: Big Data Analytics the Future. International Journal of Nursing & Clinical Practices, 4(1). doi:10.15344/2394-4978/2017/220
