Nurse Research Decision Theory Describes the Rules Essay

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Nurse Research

Decision theory describes the rules and standards that are used to make some specific form of decision or judgment. With respect to data analysis, decision theory describes the rules and procedures that should be used to interpret the results of the findings in the data. Such rules include hypothesis testing, qualitative data interpretation, and other types of inferential procedures. Probability theory is used in quantitative data analysis and provides the basis for interpretation of data using statistical procedures. Probability theory relates to the understanding of how frequent a particular result or observation is as well as how often the result could occur by chance alone. Probability theory is very important in determining the relevance of any findings; in particular if the findings are significant (meaningful) or if the results are more likely due to chance or random effects. Inference is the process of taking the data and deducing what the relationships between the descriptive statistics (see below) actually mean in quantitative data analyses or identifying themes and processes in qualitative analysis. Generalization describes the ability to extend these inferences beyond the current sample to a broader relevant group or population. Inferences are made on the basis of how the data is analyzed or interpreted (the statistics or methods used), whereas generalizations are made with respect to how the data is collected (what type of sampling method was used).

Descriptive statistics simply provide simple numerical summarizations of the many observations in the data. The mean, median, and mode are descriptive statistics and are all measures of central tendency.

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Central tendency describes the trend for the majority scores or observations in a data set to bunch around the middle values of the distribution. The mode represents the most frequently occurring score or value in the data. A given distribution of data can have more than one mode. The median represents the one observation or score in the data that cuts the distribution in half (the 50th percentile); 50% of the scores lie above and below the median, whereas the mean is the arithmetical average of all the values in the data. In a normal distribution the values of the mean, mode, and median are the same; in non-normal distributions these values will differ. The standard deviation is a measure of dispersion of a measure of how far the scores in the distribution are spread out. The standard deviation represents the average amount of variability or spread scores are from the mean of the distribution. The larger the standard deviation the greater the scores in the distribution are spread around the mean (Nunnally & Bernstein, 1994).

Nurses often play important roles in making sure that confidentiality and other research participant rights are maintained during research protocols. The nature of medical research often deals with private and sensitive issues. Therefore nurses, who often engage in the data collection and recording….....

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