Statistical Analysis in Nursing Essay Example | Topics and Well Written Essays - 1250 words

Statistical Analysis in Nursing - Essay Example2.Non parametric tests ilk Chi squ ar tests and Fischers test (as used in this study) are used when the sample surface is small and does not represent the population in totality and similarly when the variables are ordinal, nominal and decided variables( variables which cannot be measured and even if measured cannot be extrapolated to decimal places). Chi square value evaluates the connective or independence between the two variables. If the probability value (p value) for null hypothesis for a feature value of chi square exceeds the critical chi square value then it is inferred that the two variables are not independent and the two variables are significantly associated with each other. ... ean importance values for each chemical element for the group of 21 nurses studied which were likely to influence decision making patterns were- future health status, 39% family input, 19% persons age, 13% extra cost to agency, 12% functional status, 10% and mental competence, 6%. in that respect were three other decision-making patterns, each exhibited by one nurse One nurse relied heavily on mental competence (43%) and persons age (52%), another emphasized mental competence (43%) and functional status (29%), and the ternary used extra cost to agency (66%) supplemented by persons age (18%) for treatment of ID. Nurses work site, age, education, and years of meet did not discriminate among these decision making patterns in this small pilot study sample.(These factors were not associated or correlated with decision making ) 3. Parametric tests like Students t test and analysis of variance wee not suitable for this study as because the variables in question were not quantitative variables(measurement variables) and also because the sample size was too small. 4. The strengths of the study was rather than a prescriptive or normative status on decision making the method revealed how actually a decision making happens in a real life simulated situation. The measurements were appropriate in relation to chi square, Pearsons r and Fischers test considering small and non-representative sample of the total population. The study design included all the appropriate variables that could ease up affected decision making process. The limitations were the sample size which needed to be more to have a correct extrapolation to the ID population treated at the ED on totality. Real-world decision making may lift off from what was found in this study because simulation provides only an approximation of