Post by Day 4 an explanation of the importance of data cleaning, including assessment of missing data. Provide one example of data cleaning and the potential impact it might have on data analyses. Then explain the importance of descriptive statistics in data analyses. Finally, explain the relationship between hypothesis(es) and data analyses using at least one of your hypotheses and data analytic strategies from your Final Project as an example.
Performing Data Analysis
Data analyses cannot be performed until data has been cleaned. In fact, many of the errors found in standard data analyses can be traced directly back to \”dirty\” data. In a perfect world, collected data would be flawless, but as when working with humans in any capacity, errors occur.
To begin the cleaning process, you first need to check collected data for errors, problems, dubious responses, and other issues. Many such checks may be done electronically using statistical software. Once the proper adjustments are made, you can run the analyses. Which analyses techniques you use should align with your hypothesis. In other words, a survey researcher uses his or her hypotheses to drive the data analyses. The hypotheses dictate the \”family\” of analyses used for the data. The more parsimonious and testable the theory driving the hypotheses, the more straightforward the data analyses will be.
To prepare for this Discussion, consider why data cleaning, including the assessment of missing data, is important. Then think about the role that descriptive statistics plays in data analyses. Finally, consider the relationship between hypothesis(es) and data analyses and how you would illustrate this relationship using at least one of your hypotheses and data analytic strategies from your Final Project as an example.
With these thoughts in mind:
Post by Day 4 an explanation of the importance of data cleaning, including assessment of missing data. Provide one example of data cleaning and the potential impact it might have on data analyses. Then explain the importance of descriptive statistics in data analyses. Finally, explain the relationship between hypothesis(es) and data analyses using at least one of your hypotheses and data analytic strategies from your Final Project as an example.
My final project: . This study aims to determine the psychosocial role of social workers in improving the quality of life of chronic kidney disease patients. The research location will be dialysis facilities which has high numbers of kidney patients. The population comprised of inpatient, outpatient and transplanted patients diagnosed with chronic kidney infection. Survey research design will be applied in which stratified sampling will be used for identification of sample (Cozby et al, 1989). All the required ethical procedures for seeking permission to conduct research and for ensuring patients protection will be observed. The measurements for this research include; socio-demographic and psychosocial factors, KDQOL-SF, biomedical factors and the patient health questionnaire. All the data collected will be analyzed statistically and then the findings will be disseminated to all relevant people and bodies.
