The paper “Some of the Routine Applications of Descriptive Statistics” discusses the importance of descriptive statistics to the nursing leader and reveals that such statistics are used in decision making process as they inform the decisions that the leader makes…
In addition, Part B of the assignment discusses some of the use of confidence intervals in determining the statistical confidence of nursing research and explains that the approach is used test the reliability or probability of getting the same values from a sample size. However, a major controversy of statistical and clinical significance is the biasness of the resulting data when used in real clinical context.
The descriptive statistics in the article stems from the emphasis on the need to identify and include or integrate the family members of the patients during the provision of the health care services to the patient (Tudor, Berger, Polivka, Chlebowy & Thomas, 2014). As such, the article recommends there is the need to embrace patient and family-centered care as this is poised to transform the healthcare sector a great deal. In particular, the article tries to gather descriptive statistics from the characteristics or elements of the patient’s family members with the underlying assumption that involving the family of the patients in routine care can improve safety and satisfaction (Tudor, Berger, Polivka, Chlebowy & Thomas, 2014). In this case, the descriptive statistics included such elements like the ethnicity, sex, age, years of experience, work unit including other important statistics on the characteristics of the patient’s family like specialty certification, the number of times they have been involved in resuscitation (Tudor, Berger, Polivka, Chlebowy, Thomas, 2014). Other variable statistics included or involved identifying the risk and benefits of the presence of the family. ...
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(Some of the Routine Applications of Descriptive Statistics Coursework - 12)
“Some of the Routine Applications of Descriptive Statistics Coursework - 12”, n.d. https://studentshare.net/nursing/842954-any-topic-writers-choice.
This risk assumes greater importance in research where the sample sizes are large such as in the current research problem. In order to ensure that the data being presented for analysis is competent enough, the researcher employs a number of techniques. One of these techniques is better known as internal consistency / reliability or internal validity of the statistical data.
Table 1. Number of weeks the patient lived after taking the drug Patient Number No. of Weeks 1 3 2 5 3 6 4 6 5 8 6 8 7 9 8 9 9 9 10 10 11 11 12 45 Figures in Table 1 represent a data set with a mean of 10.75 and a standard deviation of 11.02. This indicates that with the new drug, the patients lived longer on the average, reaching up to 10.75 weeks of living (Creswell, 2003).
The computation of mean values was performed on the four subscales of nurses’ confidence in understanding and evaluating research. These values indicated the degree of confidence of nurses on each of the four subscales on a scale of 1 to 5, with 1 indicating a low confidence level and 5 indicating a high confidence level.
These descriptive statistics help in understanding the most common and the most distinctive traits of the data collected, as well as helping in the use of other statistical techniques that can help in making estimates about the population
You can only fund one of the two. Patients and their families are anxiously waiting for the Board of Directors to make a decision on which of the two can be funded.
Part I: Your first task it to do the following
In the pilot study, the researcher created four subscales in research self-efficacy and monitored their performance under various conditions.
By using Research Publication on the nurses, the researcher resolves whether the experience of education may influence
nderstanding distribution of levels of consumption and associated factors is significant to business organizations for policymaking and for decisions on levels of production (Lee, C., Lee, J., & Lee A., 2013). Understanding distribution of levels of income across a market