NR 439 Week 6 Graded Discussion Topic; Data Analysis and Results

Week 6 Discussion: Data Analysis and Results Data are mere facts and figures. Without data analysis, no meaningful information can be obtained from research. Data analysis enables researchers to make informed decisions ...

Week 6 Discussion: Data Analysis and Results Data are mere facts and figures. Without data analysis, no meaningful information can be obtained from research. Data analysis enables researchers to make informed decisions quickly, backing them up with facts provided by the data. Also, data analysis allows the uses of a research study to deeply understand the problem and potential solutions hence building better businesses and relationships between the business and the customers. I learned a lot about descriptive statistics, inferential statistics, and qualitative analysis of data. Descriptive statistics is the description or summarizing of data in a meaningful way to establish relationships and patterns from the data (Byrne, 2007). However, a researcher cannot make conclusions from descriptive statistics beyond the data analysed. Also, a researcher cannot reach a conclusion concerning any hypothesis developed. In other words, descriptive statistics simply provide a way to describe the data collected. What I learned from descriptive statistics is that it is important in research as it helps in visualizing what the data shows. Without it, it could have been very hard to visualize and establish patterns on data collected. Also, I learnt that with descriptive statistics we can present the collected data more meaningfully hence allowing a simpler way of interpreting it. Inferential statistics allows a researcher to make inferences (predictions) from the collected data. Inferential statistics involves taking samples from a populations and making generalizations concerning the population (Byrne, 2007). There are two things that I learnt about inferential statistics – estimating the parameters and testing the hypothesis. Estimation of parameters refer to taking a statistic from the sample data and using this statistic to infer something about the entire population. An example of sample data is the sample mean and an example of a population parameter is the population mean. Testing the hypothesis involves This study source was downloaded by 100000831988016 from CourseHero.com on 01-07-2022 23:01:51 GMT -06:00 https://www.coursehero.com/file/62540008/NR-439-Week-6-Discussion-Data-Analysis-and-Resultsdocx/ the use of the sample data to answer the research questions such as determining whether a new cancer drug is effective. Qualitative analysis uses subjective judgement, which is based on non-quantifiable information such as strength of research and development, industry cycles, labour relations, and management expertise (Sutton and Austin, 2015). I learnt that qualitative analysis deals with intangible and inexact concerns in the social and experiential realm as opposed to belonging to the mathematical realms. Qualitative approach relies on the intelligence of the machines since it is impossible to capture things like customer satisfaction, brand management trustworthiness, cultural shifts, and competitive advantage. Data analysis is necessary for discovering credible findings for nursing because it enables nursing researchers to make well-informed decisions from the data collected. It makes it possible for nursing researchers to make efficient decisions on the effects of a drug, causes of a condition, etc. Statistically significant study results in clinical research are interpreted as being clinically important. Statistical significance, on the other hand, indicates the level of reliability of study results. Therefore, clinical significance describes its impacts on clinical practice. Clinical significance is about the real life importance of research findings (ArmijoOlivo, 2018). When considering application of findings to nursing practice, clinical significance is more meaningful because it facilitates the clinicians’ understanding and interpretation of research results, and hence it is important in the transfer of knowledge obtained from research into clinical practice. Clinical relevance facilitates the understanding and interpretation of results for clinicians. In physical therapy, the assessment of this approach has become a popular method to assist the transfer of knowledge into clinical practice (Armijo-Olivo, 2018)