Mathematics
HLT362V GCU WeeK 5 Correlation Coefficient and Linear Regression Paper

HLT362V

Grand Canyon University

Question Description

1. Submit work in SPSS by copying the output and pasting into the Word document.

2. In addition to the SPSS output, please include explanations of the results where appropriate.

Exercise 14 and 19

Exercise 21 and 35

(Calculate and interpret the correlation coefficient, Calculate and interpret a linear regression line,Calculate and interpret the chi-square test of independence).

Unformatted Attachment Preview

Statistics for Nursing Research: A Workbook for Evidence-Based Practice, 2nd Edition Exercise 14: Understanding Simple Linear Regression Questions to Be Graded Name:__________________________________ Class: ______________________ 1. According to the study narrative and Figure 1 in the Flannigan et al. (2014) study, does the APLS UK formula under- or overestimate the weight of children younger than 1 year of age? Provide a rationale for your answer. A. It overestimates the weight of these children, because the formula results are above the actual children’s weights. B. The statement in A is not correct. Answer: Choose an item. 2. Using the values a = 3.161 and b = 0.502 with the novel formula in Figure 1, what is the predicted weight in kilograms (kg) for a child at 9 months of age? Show your calculations. A. 6.68 B. 7.68 C. 8.32 D. 9.32 Answer: Choose an item. Calculation: 3. Using the values a = 3.161 and b = 0.502 with the novel formula in Figure 1, what is the predicted weight in kilograms for a child at 2 months of age? Show your calculations. A. 3.658 B. 3.858 C. 4.065 D. 4.165 Answer: Choose an item. Copyright © 2017, Elsevier Inc. All rights reserved. Questions to Be Graded 4. 5. 14-2 In Figure 2, the formula for calculating y (weight in kg) is Weight in kg = (0.176 × Age in months) + 7.241. Identify the y intercept a and the slope b in this formula. A. Intercept=0.176, slope=7.241 B. Intercept=7.241, slope=0.176 Answer: Choose an item. Using the values a = 7.241 and b = 0.176 with the novel formula in Figure 2, what is the predicted weight in kilograms for a child 3 years of age? Show your calculations. A. 13.577 B. 14.577 C. 15.577 D. 16.577 Answer: Choose an item. Calculation: 6. Using the values a = 7.241 and b = 0.176 with the novel formula in Figure 2, what is the predicted weight in kilograms for a child 5 years of age? Show your calculations. A. 15.801 B. 16.801 C. 17.801 D. 18.801 Answer: Choose an item. Calculation: 7. 8. In Figure 3, some of the actual mean weights represented by blue line with squares are above the dotted straight line for the novel formula, but others are below the straight line. Is this an expected finding? Provide a rationale for your answer. A. Yes. Not all the data points should fall on a straight line or line of best fit in a regression analysis. B. No. All the data points should fall on a straight line or line of best fit in a regression analysis. Answer: Choose an item. In Figure 3, the novel formula is (weight in kilograms = (0.331 × Age in months) − 6.868. What is the predicted weight in kilograms for a child 10 years old? Show your calculations. A. 31.85 B. 32.85 C. 33.85 D.34.85 Answer: Choose an item. Copyright © 2017, Elsevier Inc. All rights reserved. Questions to Be Graded 14-3 Calculation: 9. Was the sample size of this study adequate for conducting simple linear regression? Provide a rationale for your answer. A. Yes. The sample size was large. B. No. The sample size was not large enough. Answer: Choose an item. 10. Describe one potential clinical advantage and one potential clinical problem with using the three novel formulas presented in Figures 1, 2, and 3 in a PICU setting. Clinical advantage: Potential clinical problem: All questions: Choose an item. Exercise 19: Understanding Pearson Chi Square 1. According to the relevant study results section of the Darling-Fisher et al. (2014) study, what categories are reported to be statistically significant? A. Between RAAPS users and nonusers with respect to provider types, practice setting, percent of adolescent patients, years in practice, and practice region. B. Between RAAPS users and nonusers with respect to race, age. Answer: Choose an item. 2. What level of measurement is appropriate for calculating the χ2 statistic? A. Nominal level B. Interval level C. Ratio level Answer: Choose an item. Give two examples from Table 2 of demographic variables measured at the level appropriate for χ2. Copyright © 2017, Elsevier Inc. All rights reserved. Questions to Be Graded 14-4 3. What is the χ2 for U.S. practice region? Is the χ2 value statistically significant? Provide a rationale for your answer. A. 5.68. Significant, because the p-value is <0.05 B. 5.68. Not significant, because the p-value is ≥0.05 C. 29.68. Significant, because the p-value is <0.05 D. 29.68. Not significant, because the p-value is ≥0.05 Answer: Choose an item. 4. What is the df for provider type? Provide a rationale for why the df for provider type presented in Table 2 is correct. A. 2, because it was consistent with the formula for df. B. 2, because it was larger than what the formula for df indicated. C. 4, because it was consistent with the formula for df. D. 4, because it was larger than what the formula for df indicated. Answer: Choose an item. 5. Is there a statistically significant difference for practice setting between the Rapid Assessment for Adolescent Preventive Services (RAAPS) users and nonusers? Provide a rationale for your answer. A. Yes, because the χ2 test yielded a significant p-value. B. No, because the χ2 test did not yield a significant p-value. Answer: Choose an item. 6. State the null hypothesis for provider age in years for RAAPS users and RAAPS nonusers. A. There is a difference between RAAPS users and RAAPS nonusers with regards to provider age in years. B. There is no difference between RAAPS users and RAAPS nonusers with regards to provider age in years. Answer: Choose an item. 7. Should the null hypothesis for provider age in years developed for Question 6 be accepted or rejected? Provide a rationale for your answer. A. Accepted, because p-value<0.05. B. Accepted, because p-value≥0.05. C. Rejected, because p-value<0.05. D. Rejected, because p-value≥0.05. Answer: Choose an item. 8. Describe at least one clinical advantage and one clinical challenge of using RAAPS as described by Darling-Fisher et al. (2014). Copyright © 2017, Elsevier Inc. All rights reserved. Questions to Be Graded 14-5 Clinical advantage: Clinical challenge: All questions: Choose an item. 9. How many null hypotheses are rejected in the Darling-Fisher et al. (2014) study for the results presented in Table 2? Provide a rationale for your answer. A. 2, because 2 p-values were <0.05. B. 3, because 3 p-values were <0.05. C. 4, because 4 p-values were <0.05. D. 5, because 5 p-values were <0.05. Answer: Choose an item. 10. A statistically significant difference is present between RAAPS users and RAAPS nonusers for U.S. practice region, χ2 = 29.68. Does the χ2 result provide the location of the difference? Provide a rationale for your answer. A. Yes, the χ2 test can determine the location of the different (>0 or <0). B. No, it cannot determine the location of the difference. Answer: Choose an item. Grading Please do not add or delete a row or column for the following grading table. If you have a problem with the drop-down lists, then you can enter your answers in the second column. If you use the drop-down lists, the instructor will update your answers in the table. Thanks Question 14.1 2 3 4 5 6 7 8 9 10 19.1 Your answer Correct answer Possible points 4 4 4 4 4 4 4 4 4 4 4 Copyright © 2017, Elsevier Inc. All rights reserved. Your points Questions to Be Graded 2 3 4 5 6 7 8 9 10 Total 14-6 4 4 4 4 4 4 4 4 4 80 Copyright © 2017, Elsevier Inc. All rights reserved. Statistics for Nursing Research: A Workbook for Evidence-Based Practice, 2nd Edition Exercise 29: Calculating Simple Linear Regression Questions to Be Graded The following questions refer to the section called “Data for Additional Computational Practice” in Exercise 29 of Grove & Cipher, 2017. 1. If you have access to SPSS, compute the Shapiro-Wilk test of normality for the variable age (as demonstrated in Exercise 26). If you do not have access to SPSS, plot the frequency distributions by hand. What do the results indicate? A. The distribution significantly deviated from normality. B. The distribution did not significant from normality. Answer: Choose an item. 2. State the null hypothesis where age at enrollment is used to predict the time for completion of an RN to BSN program. A. Age at enrollment predicts the number of months until completion of an RN to BSN program. B. Age at enrollment does not predict the number of months until completion of an RN to BSN program. Answer: Choose an item. 3. What is b as computed by hand (or using SPSS)? A. 0.027 B. 0.037 C. 0.047 D. 0.057 Answer: Choose an item. 4. What is a as computed by hand (or using SPSS)? A. 10.76 B. 11.76 C. 12.76 D. 13.76 Answer: Choose an item. 5. Write the new regression equation. A. B. C. D. ŷ = 0.027x + 10.76 ŷ = 0.037x + 10.76 ŷ = 0.047x + 11.76 ŷ = 0.057x + 11.76 Copyright © 2017, Elsevier Inc. All rights reserved. Questions to Be Graded 29-2 Answer: Choose an item. 6. How would you characterize the magnitude of the obtained R2 value? Provide a rationale for your answer. A. R2 value is very low. B. R2 value is very high. Answer: Choose an item. 7. How much variance in months to RN to BSN program completion is explained by knowing the student’s enrollment age? A. 1.2% B. 2.4% C. 12% D. 24% Answer: Choose an item. 8. What was the correlation between the actual y values and the predicted y values using the new regression equation in the example? A. 0.11 B. 0.155 C. 0.346 D. 0.49 Answer: Choose an item. 9. Write your interpretation of the results as you would in an APA-formatted journal. Enter your answer here and select the “Completed” choice in the dropdown menu. If more space is needed, please hit the Enter key from your computer. Answer: Choose an item. 10. Given the results of your analyses, would you use the calculated regression equation to predict future students’ program completion time by using enrollment age as x? Provide a rationale for your answer. A. Student age (x) did significantly predict months to completion (y). Therefore, the equation will accurately predict future values of y. Copyright © 2017, Elsevier Inc. All rights reserved. Questions to Be Graded 29-3 B. Student age (x) did not significantly predict months to completion (y). Therefore, the equation will not accurately predict future values of y. Answer: Choose an item. Exercise 35: Calculating Pearson Chi-Square Questions to Be Graded The following questions refer to the section called “Data for Additional Computational Practice” in Exercise 35 of Grove & Cipher, 2017. 1. Do the example data in Table 35-2 meet the assumptions for the Pearson χ2 test? Provide a rationale for your answer. A. Yes, the data meet the 2 assumptions. B. No, the data do not meet the 2 assumptions. C. Yes, the data meet the 3 assumptions. D. No, the data do not meet the 3 assumptions. Answer: Choose an item. 2. Compute the χ2 test. What is the χ2 value? A. B. C. D. 11.93 12.93 13.93 14.93 Answer: Choose an item. 3. Is the χ2 significant at α = 0.05? Specify how you arrived at your answer. A. Yes, by comparing it with the critical value. B. No, by comparing it with the critical value. Answer: Choose an item. 4. If using SPSS, what is the exact likelihood of obtaining the χ2 value at least as extreme as or as close to the one that was actually observed, assuming that the null hypothesis is true? A. 0.1% B. 0.5% C. 1% D. 5% Answer: Choose an item. 5. Using the numbers in the contingency table, calculate the percentage of antibiotic users who tested positive for candiduria. A. 15.5% B. 25.9%. C. 47.6% Copyright © 2017, Elsevier Inc. All rights reserved. Questions to Be Graded 29-4 D. 0% Answer: Choose an item. 6. Using the numbers in the contingency table, calculate the percentage of nonantibiotic users who tested positive for candiduria. A. 15.5% B. 25.9%. C. 47.6% D. 0% Answer: Choose an item. 7. Using the numbers in the contingency table, calculate the percentage of veterans with candiduria who had a history of antibiotic use. A. 0% B. 10%. C. 15% D. 100% Answer: Choose an item. 8. Using the numbers in the contingency table, calculate the percentage of veterans with candiduria who had no history of antibiotic use. A. 0% B. 10%. C. 15% D. 100% Answer: Choose an item. 9. Write your interpretation of the results as you would in an APA-formatted journal. Enter your answer here and select the “Completed” choice in the dropdown menu. If more space is needed, please hit the Enter key from your computer. Answer: Choose an item. 10. Was the sample size adequate to detect differences between the two groups in this example? Provide a rationale for your answer. Copyright © 2017, Elsevier Inc. All rights reserved. Questions to Be Graded 29-5 A. The sample size was adequate to detect differences between the two groups because a significant difference was found, p = 0.001. B. The sample size was not adequate to detect differences between the two groups because no significant difference was found, p >0.05. Answer: Choose an item. Grading Please do not add or delete a row or column for the following grading table. If you have a problem with the drop-down lists, then you can enter your answers in the second column. If you use the drop-down lists, the instructor will update your answers in the table. Thanks Question 29.1 2 3 4 5 6 7 8 9 10 35.1 2 3 4 5 6 7 8 9 10 Total Your answer Correct answer Possible points 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 4.5 80 Copyright © 2017, Elsevier Inc. All rights reserved. Your points ...
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Final Answer

Hi again dejesus,Attached please find the Word documents containing the correct answers (highlighted) with complete solutions and SPSS output where required.Thanks again!Selenica

Statistics for Nursing Research: A Workbook for Evidence-Based
Practice, 2nd Edition
Exercise 29: Calculating Simple Linear Regression
Questions to Be Graded
The following questions refer to the section called “Data for Additional
Computational Practice” in Exercise 29 of Grove & Cipher, 2017.
1. If you have access to SPSS, compute the Shapiro-Wilk test of normality for the
variable age (as demonstrated in Exercise 26). If you do not have access to SPSS,
plot the frequency distributions by hand. What do the results indicate?
A. The distribution significantly deviated from normality.
B. The distribution did not significant from normality.
Answer: Choose an item.
Tests of Normality
Kolmogorov-Smirnova
Statistic

df

Shapiro-Wilk

Sig.

Statistic

age

.140

20

.200*

monthscompletion

.159

20

.200*

df

Sig.

.949

20

.357

.931

20

.160

*. This is a lower bound of the true significance.
a. Lilliefors Significance Correction

2. State the null hypothesis where age at enrollment is used to predict the time for
completion of an RN to BSN program.
A. Age at enrollment predicts the number of months until completion of an RN to
BSN program.
B. Age at enrollment does not predict the number of months until completion of
an RN to BSN program.
Answer: Choose an item.
Coefficientsa
Standardized
Unstandardized Coefficients
Model
1

B
(Constant)
age

Std. Error

11.763

3.536

.047

.102

Coefficients
Beta

t

.108

a. Dependent Variable: monthscompletion
b = 0.047

3. What is b as computed by hand (or using SPSS)?
A. 0.027

Copyright © 2017, Elsevier Inc. All rights reserved.

Sig.

3.326

.004

.459

.651

Questions to Be Graded

29-2

B. 0.037
C. 0.047
D. 0.057
Answer: Choose an item.
4. What is a as computed by hand (or using SPSS)?
A. 10.76
B. 11.76
C. 12.76
D. 13.76
Answer: Choose an item.
5. Write the new regression equation.
A. ŷ = 0.027x + 10.76
B. ŷ = 0.037x + 10.76
C. ŷ = 0.047x + 11.76
D. ŷ = 0.057x + 11.76
Answer: Choose an item.
6. How would you characterize the magnitude of the obtained R2 value? Provide a
rationale for your answer.
A. R2 value is very low.
B. R2 value is very high.
Answer: Choose an item.
The r-squared value is 0.012, which is very low. The r-squared value is meant to
explain the amount of variance in the dependent variable explained by the
independent variable. In this case, only 1.2% of variance in the y-variable is
explained by the independent variable.
7. How much variance in months to RN to BSN pro...

Selenica (1623)
New York University

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