Basic Terminology For A State Of Affairs

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Basic Terminology: Unit Three Sheila Elyse Brooks Stanbridge College April 27, 2015 Introduction As we continue our journey through the "trials and errors" of understanding basic statistical terminology. Let 's focus our attention on the following: understanding what is the difference between a hypothesis, statistical hypothesis, and an experimental hypothesis. In addition, I want to explore how researchers determine the appropriate sample size. Now, some of you might be asking the question "what do we do once we have our hypothesis and sample population?" Well, now is a wonderful time to start experimenting with statistical methods like the chi-square test. I will explain this later on. Hypothesis A…show more content…
However, most clinical research associates do not hold medical degree of any type. This makes it rather to master the skills I need when I see my patients. Often, we are not allowed to open any lab kits (because they are in sequential order) which makes nurses prone to more mistakes. When I first came to Mount Carmel, I notice we had simulators. So, I began to think how these simulators could reduce the clinical errors in research. My hypothesis (state of affairs) could be: Clinical research nurses who practice on simulators are more likely to have fewer medical errors then those who do not. My Experimental hypothesis: Clinical research nurses are 25% more likely to make mistakes when performing clinical skills (such as lab draws and administering study medication) then those nurses who practice on patient simulators. My experiment: Compare the performance of nurses who use patient simulators to practice specific study related skills versus those who do not. After you figure out your hypothesis, you must consider what makes a "good estimate". Making Good Estimates We obtain a sample in order to obtain a statistical measurement such as a mean form our observation. One can say that different sample sizes would produce different values or variations. The variation between these individual estimates is due to sampling error (Fowler et el, 2002). It is important to note that sampling
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