As part of her thesis for the Adult Nurse Practioner Program, a student interest
ID: 2927024 • Letter: A
Question
As part of her thesis for the Adult Nurse Practioner Program, a student interested in determining whether a difference exists between self-reported heights and measured heights for UIC students. Listed below are sample results from her study. Analyze the data using StatCrunch, and answer the following questions. Table 2: Self-reported and measured heights of UIC Students ID Reported Measured 1. 68 67.9 2. 71 69.9 3. 63 64.9 4. 70 68.3 5. 71 70.3 6. 60 60.6 7. 65 64.5 8. 64 67.0 9. 54 55.6 10. 63 74.2 11. 66 65.0 12. 72 70.8 13. 66 64.8 14. 68 67.6 15. 64 62.1 16. 56 56.8 17. 57 57.3 18. 58 59 19. 54 54 20. 53 52.2 21. 52 51 22. 61 61.4 23. 62 63 24. 62 61.2 25. 60 59.4 26. 59 57.5 27. 58 59 28. 57 57.3 29. 53 51.8 30. 57 56.5 a. What type of analysis should be used to answer this question? Why did you choose that type of analysis? Your options are: one sample t-test, one sample z-test, Two sample t-test, chi-square, ANOVA, and paired t-test. Check if the conditions for reliable use of the test are met. [2 points]
Explanation / Answer
Solution:-
Two sample t-test should be used for the analysis of the data.
Yes, all the conditions for reliable use of the test are met.
From the two set of data given, we need to find Mean and Standard deviation for each of them.
Null and alternative hypothesis are often stated in the following form.
H0: 1 = 2
Ha: 1 2
Formulate an Analysis Plan -
The analysis plan describes how to use sample data to accept or reject the null hypothesis. It should specify the following elements.
Analyze Sample Data -
Using sample data, find the standard error, degrees of freedom, test statistic, and the P-value associated with the test statistic.
SE = sqrt[ (s12/n1) + (s22/n2) ]
DF = (s12/n1 + s22/n2)2 / { [ (s12 / n1)2 / (n1 - 1) ] + [ (s22 / n2)2 / (n2 - 1) ] }
t = [ (x1 - x2) - d ] / SE
Interpret Results -
If the sample findings are unlikely, given the null hypothesis, the researcher rejects the null hypothesis. Typically, this involves comparing the P-value to the significance level, and rejecting the null hypothesis when the P-value is less than the significance level.
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