Provide two different examples of how research uses hypothesis testing, and describe the criteria for rejecting the null hypothesis. Discuss why this is important in your practice and with patient interactions.
A hypothesis test is a statistical procedure that’s designed to use data to validate or invalidate a claim or test a claim or a question. The claim is usually being made about a population or a parameter (one number that characterizes the whole population).
Hypothesis testing:
Making an assumption, called hypothesis about a population parameter
Collecting sample data
Calculating a sample statistic
Using the sample statistic to evaluate the hypothesis
In statistics terminology, the people in the study are the sample and the larger group they represent is called the population. Every hypothesis test contains a set of two opposing statements or hypotheses, about a population. The first is the null hypothesis, which states that the population parameter is equal to the claimed value. If the null hypothesis is rejected, we must have an alternative hypothesis which is one you would believe if the null hypothesis is concluded untrue. More simply stated, the null hypothesis is the position you take before you examine the evidence, what you believe to be true. The alternative hypothesis is the position you are willing to move to if the evidence is strong enough. An example would be, I think this therapy will work better than the placebo. You then use data to support this. You test whether this is true by collecting a random sample of the effectiveness of the therapy and the placebo. If I do not find enough evidence to support that this therapy An example would be, I think this therapy will work better than the placebo. You then use data to support this. You test whether this is true by collecting a random sample of the effectiveness of the therapy and the placebo. If I do not find enough evidence to support that this therapy is better than the placebo then I fail to reject the null hypothesis and the conclusion would be that the therapy does work better than the placebo. If the evidence was strong enough to reject the null hypothesis, the alternative hypothesis would be that the placebo worked better.
Another example would be the null hypothesis is X medication ad Y medication have the same benefits. If we fail to reject the null hypothesis the alternative hypothesis would be that X medication is better or worse than Y medication.
Quantitative research is important if we strive to practice by evidence-based practice the statistical process mentioned above must take place to realize when something needs to be change or adjusted and have the evidence to back it up.
References:
Popper, K. (2015, November). Discuss why this is important in your practice and with patient interactions. Retrieved from Quora: https://www.quora.com/In-hypothesis-testing-why-do-we-try-to-falsify-the-null-hypothesis-instead-of-research-hypothesis-alternate-hypothesis.
Rumsey, D. J. (2011). Statistics for Dummies . Indianapolis: Wiley Publishing.
Provide two different examples of how research uses hypothesis testing, and describe the criteria for rejecting...
Provide two different examples of how research uses hypothesis testing, and describe the criteria for rejecting the null hypothesis. Discuss why this is important in your practice and with patient interactions.
Provide two different examples of how research uses hypothesis testing, and describe the criteria for rejecting the null hypothesis. Discuss why this is important in your practice and with patient interactions.
Provide two different examples of how research uses hypothesis testing, and describe the criteria for rejecting the null hypothesis. Discuss why this is important in your practice and with patient interactions. give 2 references.
How researches use hypothesis testing and give two different examples? Describe the criteria for rejecting the null hypothesis. Discuss why this is important in your practice and with patient interactions?
Discuss the five steps in hypothesis testing, citing examples where necessary. Define null and research hypotheses. Explain how to prepare data for hypothesis testing. Describe exploratory data analysis as a prelude to hypothesis testing. Distinguish between Type I and II errors. What are the implications of each?
Evaluate and provide examples of how hypothesis testing and confidence intervals are used together in health care research. Provide a workplace example that illustrates your ideas.
Evaluate and provide examples of how hypothesis testing and confidence intervals are used together in health care research. Provide a workplace example that illustrates your ideas.
Evaluate and provide examples of how hypothesis testing and confidence intervals are used together in health care research. Provide a workplace example that illustrates your ideas.
Evaluate and provide examples of how hypothesis testing and confidence intervals are used together in health care research. Provide a workplace example that illustrates your ideas. give 2 references.
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