What is the functions of parametric statistical procedures

Assignment Help Basic Statistics

Reference no: EM13893684

1. What would be the appropriate statistical procedure to test the following hypothesis: "Determine the relationship between the year in school (freshman, sophomore, junior and senior) and having a car on campus."

2. What is (are) the function(s) of parametric statistical procedures?

3. What is Type 1 error?

4. What are the assumptions underlying the use of parametric statistical procedures?

5. If a critical value is greater than the test statistic, would you accept or reject the null hypothesis?

6. Under what circumstance(s) is it appropriate to use a 2-tailed test of significance?

7. What is the appropriate statistical procedure to use when you interest is in detecting a bivariate, curvilinear association?

8. For a study comparing outcomes under alternative treatment conditions, when the null hypothesis is rejected, the researcher concludes that a difference among groups exists.

True

False

9. A researcher, for reasons passing understanding, wishes to assess the association between gender and total cholesterol values. What would be the appropriate statistical procedure?

10. An HIV educator wishes to determine whether the method of delivering teaching influences adherence to antiretroviral therapy. She decided to measure adherence as viral load (a ration measure). She teaches on group using lecture-discussion techniques. She adapts the information for access on the internet and give another group this information using this medium. For yet another group, she decided to give a CD Rom for home study and then meets with individuals to answer any questions. She obtains viral loads for all clients for comparison. What procedure will determine the significance of any differences?

Items 11-15 related to the following study results:

Study A Study B Study C

X²F=7.357 r=.83

df=4 df=4/203 df=98

p> .05 p < .05 p < .01

11. What statistical procedure was used to analyze data in Study C?

12. How many groups were compared in study B?

13. How many subjects were enrolled in Study C?

14. Which demonstrated the greatest level of statistical significance?

15. In which study is the likelihood of Type I error greatest?

Items 16, 17, and 18 relate to the following:

In a regression analysis, a nurse researcher found a correlation of ,80 between pain relief scores and satisfaction with nursing care. She also calculated the following for her regression analysis:

Pain relief (x): Mean = 58 sd = 3.9

Satisfaction (y): Mean =42 sd = 5.4

Slope = 1.56

Y intercept = -3.53

16. What will be the predicted satisfaction scores (expressed as a point estimate) for a patient with pain relief score of 60?

17. What is the standard error of estimate when predicting satisfaction from knowledge of pain relief score

18. What would be the interval estimate for satisfaction for the patient in problem 16?

Items 19-21: A nurse researcher is investigating the effect of timing of standard pain control interventions on severity of pain in adolescents with sickle-cell disease. She establishes three treatment protocols: 1) initiation of pain control immediately upon the presence of prodromal sign (an "aura" signaling the imminent onset of pain); 2) initiation of pain control one hour after the onset of pain; and 3) initiation of pain control only at the points where non-steroidal anti-inflammatories and guided imagery are no longer effective in keeping pain bearable. She conducted a one-way ANOVA to analyze her data and the following table summarizes her findings:

Source df SS MSS F p___

Among 2 75536.2 37768.1 5.159 < .05

Within 27 197660.3 7320.8______________________

Total 29 273196.5

On the basis of these data alone, she drew the following conclusions. For each conclusion, indicate whether you feel the conclusion is justified or unjustified.

19. Severity of pain is influenced by the timing of pain interventions in sickle cell crises.

20. Immediate intervention is better than either slightly delayed intervention or initiation at crisis stage.

21. She has more than 90% confidence in her conclusion that severity of pain is influenced by timing.

Items 22-23 relate to the following study results:

Study A Study B

r = .64 r=.77

df = 18 df = 21

p< .05 p< .01

22. In using the data from Study A to make predictions, what percent of time would you expect predictions to be exactly correct?

23. Which study would have the smallest margin of error in predicting one variable from knowledge of the other?

Items 24 and 25 relate to the following SPSS output. A researcher, interested in characteristics of HIV+ and HIV- adolescents, interviewed 166 young adults about their experiences during adolescence. He wished to know, among other things, if there were significant difference in the ages at which HIV+ and HIV- young adults became sexually active. The following is the printout of this analysis:

HIV Status N Mean sd Stnd. Error

Age at Positive 57 13.2 2.96576 .39282

first sexual

experience Negative 109 15.1 2.57286 .24644

______________________________________________________________________________

Independent Samples Test

______________________________________________________________________________

Levene's Test for

Equality of Variances

__________________________________________F Sig

Age at Equal variance assumed 1.313 .254

first sexual

experience Equal variance not assumed

t test for Equality of Means

t df sig. mean difference

______________________________________________________________________________

Age at Equal variance assumed -2.870 164 .005 -1.9

first sexual Equal variance not assumed -2.745 99.66 .007 -1.9

experience ____________________________________________________________

24. Were there significant differences between the groups? Give the relevant statistical data to support your answer.

25. What is the confidence interval associated with your answer to Questions #24?

Each of the questions on the following pages is a calculation problem worth 10points. Partial credit will be awarded if I can follow your procedures and determine that errors are arithmetic rather than conceptual. If would be wise, therefore, to clearly indicate your worksteps on each problem.

26. For the following data set, calculate the one-way ANOVA and test for significance at the .05 level.

Group 1		Group 2		Group 3		Group 4
x	x²	x	x²	x	x²	x	x²
6	36	10	100	12	144	16	256
8	64	12	144	14	196	15	225
7	49	13	169	13	169	18	324
9	81	13	169	11	121	17	289
8	64	14	196	13	169	20	400
11	121	15	225	15	225	21	441
9	81	14	196	13	169	22	484
58	496	91	1,199	91	1,193	129	2,419

27. Calculate the x2for the following 3 x 2 table and test for significance at the .01 level.

Group 1 Group 2 Group 3

Positive outcome

Negative outcome

14 28 1456

28. For the following group data, calculate a t-test and test for significance at the .05 level, 2-tailed level of significance.

Treatment Group Control Group

Mean = 70.4 Mean = 51.2

sd = 5.6 sd = 6.6

n=42 n=48

29. For the following paired observations, calculate the Pearson product-moment correlation coefficient and test for significance at the .01 level.

X	x²	y	y²	xy
16	256	20	400	320
17	289	19	361	323
18	324	20	400	360
19	361	17	289	323
21	441	15	225	315
22	484	19	361	418
21	441	20	400	420
23	529	19	361	437
22	484	20	400	440
19	361	17	289	323
198	3,970	186	3,486	3,679

30. For the following data regarding paired rank orders for a sample, calculate the correlation coefficient and test for significance at the .05 level.

Subject # Rank 1 Rank 2

1 1.5 1

2 1.5 2.5

3 3 2.5

4 5 4

5 6 5

6 4 8

7 7 6

8 9.5 7

9 8 10

10 9.5 9

Reference no: EM13893684

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