In 2-3 paragraph: Discuss the importance of statistics and level of measurement as it relates to the research process -What does inferential statistics tell you as a reader/consumer of research? -What

In 2-3 paragraph: Discuss the importance of statistics and level of measurement as it relates to the research process

-What does inferential statistics tell you as a reader/consumer of research?

-What does descriptive statistics tell you as a reader/consumer of research?

-Identify the varied numerical values you use in your clinical practice (at least two numerical values).

-Describe which level of measurements each of those type of values represent (for example, what is the level of measurement when taking a patient’s temperature?-You may not use temperature as your numerical value response). Identify two different level of measurements you use in your nursing practice on a consistent basis.

-What is your understanding about the importance of the level of measurement as it relates to data analysis?

-Identify your primary research question from the previous week. What descriptive and inferential statistics might you use to respond to your proposed questions? (You may need to slightly alter your question to respond appropriately to this question).

NOTE:  Your response should consist of complete sentences and should be at least one complete paragraph, but it should be no more than three paragraphs in length

In 2-3 paragraph: Discuss the importance of statistics and level of measurement as it relates to the research process -What does inferential statistics tell you as a reader/consumer of research? -What
Required Video LINK 1 https://www.youtube.com/watch?v=dX6m1aImJV0 Required Video LINK 2 https://www.youtube.com/watch?v=7aHI_DCOgmM Quiz question) Discussion Question: In the first video E. O. Wilson talks about an artificially constructed and genetically-synthesized “bacteria” that has been created in a laboratory as a utterly new species and that is consequently “alive.” Do you really think that it is actually alive? Before you answer this question, consider the following two points. 1. Point One: As any biologist knows, if you are viewing two one-celled protozoa under a microscope and one suddenly dies, even though materially and chemically and genetically, at that instant, they are identical, nevertheless one is infinitely different from the other since it is dead and the other is alive, and no amount of ingenuity, even piled up for century after century, on the part of experimental biologists, can ever resurrect that dead protozoan back to life. Most biologists agree, it simply wont happen. 2. Point Two: As any biologist knows, after millions of years of amino acids evolving into bigger and bigger clumps, apparently one such random clump was suddenly galvanized (by a comet or by a massive lightning stroke, or by God knows what) into an alive being. Isn’t it rather  presumptuous of us to think that we can artificially reproduce such an ageless, endless, wholly unrepeatable miracle of self-organization, self-balancing of metabolism, and especially self-motion, that is Life Itself, simply by the tiny computerized twist of a nano-knife? CASE STUDY
In 2-3 paragraph: Discuss the importance of statistics and level of measurement as it relates to the research process -What does inferential statistics tell you as a reader/consumer of research? -What
Assignment Details Assignment Details One of the items that businesses would like to be able to test is whether or not a change they make to their procedures is effective. Remember that when you create a hypothesis and then test it, you have to take into consideration that some variance between what you expect and what you collect as actual data is because of random chance. However, if the difference between what you expect and what you collect is large enough, you can more readily say that the variance is at least in part because of some other thing that you have done, such as a change in procedure. For this submission, you will watch a video about the Chi-square test. This test looks for variations between expected and actual data and applies a relatively simple mathematical calculation to determine whether you are looking at random chance or if the variance can be attributed to a variable that you are testing for. Imagine that a company wants to test whether it is a better idea to assign each sales representative to a defined territory or allow him or her to work without a defined territory. The company expects their sales reps to sell the same number of widgets each month, no matter where they work. The company creates a null and alternate hypothesis to test sales from defined territory sales versus open sales. One of the best ways to test a hypothesis is through a Chi-square test of a null hypothesis. A null hypothesis looks for there to be no relationship between two items. Therefore, the company creates the following null hypothesis to test: There is no relationship between the amount of sales that a representative makes and the type of territory (defined or open) that a representative works in. The alternate hypothesis would be the following: There is a relationship between the kind of sales territory a sale representative has (defined or open) and the amount of sales he or she makes during a month. Step 1: Watch this youtube video: Bozeman Science. (2011, November 13). Chi-squared test [Video file]. Retrieved from https://www.youtube.com/watch?v=WXPBoFDqNVk Step 2: Use the following data to conduct a Chi-square test for each region of the company in the same manner you viewed in the video: Region Expected Actual Southeast Defined 100 98 Open 100 104 Northeast Defined 150 188 Open 150 214 Midwest Defined 125 120 Open 125 108 Pacific Defined 200 205 Open 200 278 Step 3: Write an 800–1,000-word essay, utilizing APA formatting, to discuss the following: Describe why hypothesis testing is important to businesses. Report your findings from each Chi-square test that you conducted. Based solely on the Chi-square test, discuss whether the company should accept the null hypothesis in each region or reject it in favor of the alternate hypothesis. Discuss any other statistical analyses you would want the company to contemplate before deciding if it will go with a defined or open sales strategy. Describe and discuss at least 1 other business scenario in which you believe Chi-square testing would be helpful to a company. Reference Bozeman Science. (2011, November 13). Chi-squared test [Video file]. Retrieved from https://www.youtube.com/watch?v=WXPBoFDqNVk

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