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Pages:
3 pages/≈825 words
Sources:
3 Sources
Style:
APA
Subject:
Health, Medicine, Nursing
Type:
Statistics Project
Language:
English (U.S.)
Document:
MS Word
Date:
Total cost:
$ 15.55
Topic:

Exercise 29 in Statistics for health care reseach: a practical workbook:SIMPLE LINEAR REGRETION AND POPULATION & SAMPLING DISTRIBUTION EXCEL WORKSHEET

Statistics Project Instructions:
Module 2: Assignments Exercise 29 1) Read Exercise 29 in Statistics for health care research: a practical workbook 2) Complete the study questions about the reading. 3) Check your answers to the study questions. 4) Copy and paste the Exercise 29: Questions to be Graded from page 224 into a word document. a) Complete the questions on the document and place the document in the assignment drop box. Or, as an alternative, you can b) Print the page out, and complete the questions by hand (make sure your answers are legible). Scan your completed paper and place the document in the assignment drop box. 5) In order to receive full credit on calculated answers, please show your work. (Use Word's equation editor, etc., and/or provide a short written description as to how you obtained the final result.) 6) Submit the assignment to the instructor by the end of Module 2. Population and Sampling Distribution Excel Worksheet 1) Refer to "Population and Sampling Distribution Excel Worksheet" located within the Additional Resources folder in Canyon Connect. 2) Answer the questions on the Excel document. 3) Submit the assignment to the instructor by the end of Module 2. I WILL SEND THE EXERCISE 29 QUESTIONS,THE STUDY QUESTIONS AND THE POPULATION & SAMPLING DISTRIBUTION EXCEL WORKSHEET BY ATTACHMENT TOMORROW. Please, answer all questions. Last week order you did not do the histogram. If it is possible, you can do it separately and send it to me please.
Statistics Project Sample Content Preview:
EXERCISE 29 Name: Grade Course: Tutor’s Name: (11 March, 2012) Exercise 29 1. Were the groups in this study independent or dependent? Provide a rationale for your answer. The groups were independent; this is because they did not rely on any other groups to be affected by the variable (Grove, 2007). For instance, the variables in the study each affected men and women independently. 2. t = 3.15 describes the difference between women and men for what variable in this study? Is the value significant? Provide a rationale for your answer. The variable described by t = 3.15 is mental health; its p value is 0.002 which means it is less than that of the probability (0.05) (95 percent confidence limits); hence it is significant. 3. Is t = -1.99 significant? Provide a rationale for your answer. Discuss the meaning of this result in this study. The value of t = - 1.99 is for the variable health functioning; its p value is 0.049 which means it is less than that of the probability of 0.05 (95 percent confidence limits). This means that the sample collected for that variable for the two groups i.e. men and women are significant and relevant to the study being done. 4. Examine the t rations in table VI. Which t ratio indicates the largest difference between the males and females post MI in this study? Is this t ratio significant? Provide a rationale for your answer. The values where t = - 1.98 and t = -1.99 physical functioning and health functioning respectively had the largest values of p values. Though they were high they were still less than alpha i.e. 0.05 since they were at 0.0049. This means they were statistically significant. 5. Consider t = -2.50 and t = -2.54. Which t ratio has the smaller p value? Provide a rationale for your answer. What does this result mean? The t = -2.50 for physical component score has a p value of 0.01 while t = -2.54 for role physical has a p value of 0.007. This means that t = -2.54 for role physical with a p value of 0.007 has a smaller value and hence has more significant findings in the study. 6. What is Type I error? Is there a risk of a Type I error in the study? Provide a rationale for your answer. Is also known as error of first kind; the researcher may incorrectly reject a null hypothesis which is true (Anderson, et al....
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