Have you ever seen statistics used to prove a point or make a headline stand out and thought that something was not right? Perhaps a recent study had been conducted on the long-term effects of drinking coffee and you read two different articles about it. One article claimed that drinking coffee provides physical and mental health benefits, but the other was titled, “Top 5 Reasons to Stop Drinking Coffee.” How could two opposing interpretations come from the same study? In order to have a more accurate understanding, you might read the study for yourself. In doing so, you might find that while some negative health effects were reported, such as sleep loss or anxiety, these findings only applied to a small portion of people. Additionally, perhaps the study also mentions that some of the beneficial aspects of coffee drinking were found, but that further studies would need to be conducted in order for the results to be conclusive. Returning to the two articles, did they mention these disclaimers? Whether they did or not, by having a better understanding of how statistics are used to support a hypothesis, you can better prepare yourself to filter the relevancy and accuracy of information that is presented to you.In this Discussion, you will locate an article or news story where the author presents statistics as evidence and will consider the impact of understanding the null hypotheses, type I errors, and type II errors.To prepare for this Discussion: Review this week’s Learning Resources.Find a news story in which the author(s) presents statistics as evidence. Consider the following questions:What is the author(s) trying to prove? In other words, what question is the author(s) trying to answer?What would the null hypothesis be?What would happen if the author(s) rejected the null?What action would the author(s) take?If there were a type I error, what would be the effect of the action taken?What would happen if the author(s) could not reject the null?What action would the author(s) take?If there were a type II error, what would be the effect of the action?Review the Academic Writing Expectations for 2000/3000-Level Courses, provided in this week’s Learning Resources.By Day 3Post a 150- to 225-word (2- to 3-paragraph) explanation of the role of null and alternative hypotheses as well as type I and II errors in situations where people use statistics as evidence. In your explanation, address the following:Identify, briefly, the null and alternative hypotheses involved in the news story you located, as well as explain what the author(s) is trying to prove.Describe what the implications might be if the author(s) rejected the null and if the author(s) could not reject the null.Explain the impact of potential type I and/or type II errors.To support your response, be sure to reference at least one properly cited scholarly source.

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Use MS Word to complete "Questions to be Graded: Exercise 26" in Statistics for Nursing Research: A Workbook for Evidence-Based Practice. Submit your work in SPSS by copying the output and pasting into the Word document. In addition to the SPSS output, please include explanations of the results where appropriate.