See the attached file

MODULE 3 WORKSHEET

Relationships between Variables

Purpose: You will be able to demonstrate a general understanding of interpreting statistical output to examine relationships between variables.

Instructions: Answer each item on this worksheet below and then upload this worksheet under the ASSIGNMENTS section in blackboard.

For Questions 1-7: A nurse on a busy pediatric unit noticed that her patients’ heart rates seem to be lower in the past few months since her unit hired a new music therapist. The previous music therapist would bring her amp with her into patients’ rooms and play her electric guitar LOUD. The previous music therapist left after many family complaints were filed against her. The new music therapist plays her acoustic guitar quietly in patients’ rooms and the patients seem much calmer and the nurse started to notice that the patients seem to have lower heart rates. The nurse was talking with her unit manager about this anecdotal observation and her manager encouraged her to search the literature to see if there is evidence supporting her hypothesis that the volume of music played in a patient’s room correlates to the patient’s heart rate. The nurse searched the literature with the help of the hospital librarians and found no evidence about this relationship. The unit manager thought the nurse was on to something and encouraged her to pursue this question through a unit-based research study. The nurse collaborated with a music therapist and a research mentor in the hospital, wrote a protocol, received IRB approval to conduct the study, and consented and enrolled 100 patients/families on her unit. For this study, she played music in each patient’s room and measured the volume of the music. The volume measurements ranged from 60 (soft music) to 95 (loud music). She recorded the volume of the music in the room and the infant’s heart rate at the end of 20 minutes of listening to data. Here is the SPSS output from his study:

Descriptive Statistics

MeanStd. DeviationN

Music77.56009.30659100

HR115.3926.681100

Correlations

MusicHR

MusicPearson Correlation1.081

Sig. (2-tailed).424

N100100

HRPearson Correlation.0811

Sig. (2-tailed).424

N100100

1.What was the mean volume of music played in the patients’ rooms? (2 points)

2.What was the mean heart rate of the patients? (2 points)

3.What is the null hypothesis being tested? (2 points)

4.What is the correlation coefficient (r) from this analysis? (5 points)

5.What is the p value from this analysis? (5 points)

6.Would you reject or fail to reject the null hypothesis? (5 points)

7.What conclusion would you make? (5 points)

For Questions 8-12: The nurse was frustrated with her results from the previous study (and she’d caught the research bug) so she met with the study team about replicating the study but this time measuring patient/family satisfaction instead of heart rate. She thought maybe the volume of music would relate to patient/family satisfaction. She received IRB approval for this new study, consented and enrolled another 100 patients, and used the same protocol of measuring music volume and then she added a satisfaction survey that patients/families completed at the end of their admission. The satisfaction survey was scored and satisfaction scores ranged from 0-100 and included any numbers in between (including fractions and decimal points). Here is the SPSS output from his study:

Descriptive Statistics

MeanStd. DeviationN

Music77.56009.30659100

Satisfaction63.650022.51660100

Correlations

MusicSatisfaction

MusicPearson Correlation1-.661**

Sig. (2-tailed).000

N100100

SatisfactionPearson Correlation-.661**1

Sig. (2-tailed).000

N100100

**. Correlation is significant at the 0.01 level (2-tailed).

8.What was the mean satisfaction score? (2 points)

9.What is the correlation coefficient (r) from this analysis? (5 points)

10.What is the p value from this analysis? (5 points)

11.Would you reject or fail to reject the null hypothesis? (5 points)

12.What conclusion would you make? (5 points)

For Questions 13-16: The nurse was excited about these results and wanted to take her analysis a step further. She submitted an amendment to the IRB to allow for a new statistical analysis plan. Her statistician ran a linear regression. Here is the SPSS output:

Coefficientsa

ModelUnstandardized CoefficientsStandardized CoefficientstSig.

BStd. ErrorBeta

1(Constant)187.70114.32413.104.000

Music-1.599.183-.661-8.722.000

13.What is the null hypothesis being tested? (2 points)

14.What is the p value from this analysis? (5 points)

15.Would you reject or fail to reject the null hypothesis? (5 points)

16.What conclusion would you make? (5 points)

For Questions 17-18: The nurse presented her findings at a national conference and then published her results in a peer-reviewed academic nursing journal. A nurse at the adult hospital in town wondered if these findings could be translated to adult patients. Inspired by this other nurse, she decided to do a small scale study at her hospital. She partnered with others at her hospital, wrote a protocol, received IRB approval, and consented and enrolled 25 patients. She followed the same protocol and measured music volume, but she decided to create her own satisfaction survey that was less time consuming. She simply gave her patients a paper to fill out at discharge that asked one question:

How satisfied were you with your hospital stay?

Very satisfied

Somewhat satisfied

Neutral

Somewhat dissatisfied

Very dissatisfied

She sent her data off to her statistician and here is the SPSS output she got back:

Correlations

MusicSatisfaction

Spearman’s rhoMusicCorrelation Coefficient1.000-.669**

Sig. (2-tailed)..000

N2525

SatisfactionCorrelation Coefficient-.669**1.000

Sig. (2-tailed).000.

N2525

**. Correlation is significant at the 0.01 level (2-tailed).

17.She immediately sent an email back to the statistician and said there must be something wrong. She said that she replicated a published study and in that study, the results were reported as a Pearson Correlation. She asked that the statistician re-analyze the data using a Pearson correlation. Provide a response that the statistician may have provided that would explain her choice in statistical tests. (5 points)

18.The nurse understood this explanation and realized the output above was the correct test. What conclusion did she make from this output? Did her study find similar results to the study she was replicating? (5 points)

ISSUE: Should we pay dividends?

PRELUDE: Over the years, General Electric [GE]the firm has performed well and now (mid 2017) they have a new CEO. The handsome dividends paid in the past maybe cut by 50%. GE is now at the stage that it is overextended – this poses two problems:

1.   The GE portfolio could be too large,

2.   Dividend payments are not sustainable.

There has to be a new strategy.

INFORMATION.

Academic studies:

John Lintner a Professor at the Harvard Business School in the 50’s, through interviews, gathered that investors prefer dividends and that CFO’s have a target payout ratio that they wish to achieve in the long run.

Miller & Modigliani (of capital structure fame) in a seminal paper show that dividends are irrelevant. Investors who wish for a dividend can adjust their ownership in stock. They go on to say that, dividends at the least, must be a byproduct of their capital investment policy, which essentially means do not forego positive NPV projects..

           Practice:

Firms may choose to use funds and pay dividends.

Firms may wish to avoid establishing a cash paying policy thereby, not creating an expectation in the market. A share buyback will be appropriate.

Non-cash dividends can be stock splits or stock dividends.

           What we know:

•     Aggregate payouts are big and increasing.

•     A small number of large and mature firms pay dividends.

•     Managers are reluctant to cut dividends.

•     Managers smooth dividends.

•     Stock prices react to unanticipated changes in dividends.

Financial projections:

I have constructed pro forma Income and Balance Sheet statements. Using very restrictive assumptions to some optimistic ones, I can safely state that GE has to rethink its position.

•     GE has too many business interests in many segments.

•     Some lines are not as profitable as others.

•     IF some lines are sold and the GE gets a ‘new’ focus, then, it may need make sure it has an adequate cash flow to service debt.