NURS 820 WU Nurse Burnout Issue in Healthcare Delivery Papers

Week six Assignment  # 1

  • Review the Week 6 Correlations Exercises SPSS Output provided in this week’s Learning Resources.
  • Review the Learning Resources on how to interpret correlation results to determine the relationship between variables.
  • Consider the results presented in the SPSS output and reflect on how you might interpret the results presented
  • Answer the following questions using the Week 6 Correlations Exercises SPSS Output provided in this week’s Learning Resources.What is the strongest correlation in the matrix? (Provide the correlation value and the names of variables)What is the weakest correlation in the matrix? (Provide the correlation value and the names of variables)How many original correlations are present on the matrix?What does the entry of 1.00 indicate on the diagonal of the matrix?Indicate the strength and direction of the relationship between body mass index (BMI) and physical health component subscale.Which variable is most strongly correlated with BMI? What is the correlational coefficient? What is the sample size for this relationship?What is the mean and standard deviation for BMI and doctor visits?What is the mean and standard deviation for weight and BMI?Describe the strength and direction of the relationship between weight and BMI.Describe the scatterplot. What information does it provide to a researcher? 

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    Discussion # 1  for Week 6

  • Review this week’s Learning Resources and focus on the types of research questions that can be answered using a correlational statistic.
  • Brainstorm a number of healthcare delivery or nursing practice problems that could be explored using correlational statistics. Then, select one problem on which to focus for this Discussion.
  • Formulate a research question to address the problem and that would lead you to employ correlational statistics.
  • Develop a null hypothesis and alternate hypotheses.
  • Ask yourself: What is the expected direction of the relationship?
  • Week 6 – Correlations SPSS Outputs
    Descriptive Statistics
    Mean
    Number of doctor visits, past
    Std. Deviation
    N
    6.80
    12.720
    997
    Body Mass Index
    29.2226
    7.37893
    970
    SF12: Physical Health
    45.11422
    10.840059
    893
    46.82843
    10.806477
    893
    12 mo
    Component Score,
    standardized
    SF12: Mental Health
    Component Score,
    standardized
    Correlations
    Number of
    Number of doctor visits, past Pearson Correlation
    12 mo
    Body Mass Index
    SF12: Mental
    Health
    Health
    Component
    Component
    doctor visits,
    Body Mass
    Score,
    Score,
    past 12 mo
    Index
    standardized
    standardized
    1
    Sig. (2-tailed)
    N
    SF12: Physical
    997
    **
    .131**
    -.316**
    -.133**
    .000
    .000
    .000
    967
    890
    890
    1
    **
    -.134
    -.078*
    .000
    .022
    Pearson Correlation
    .131
    Sig. (2-tailed)
    .000
    N
    967
    970
    866
    866
    **
    **
    1
    .168**
    SF12: Physical Health
    Pearson Correlation
    -.316
    -.134
    Component Score,
    Sig. (2-tailed)
    .000
    .000
    standardized
    N
    890
    866
    893
    893
    **
    -.133
    *
    -.078
    **
    .168
    1
    .000
    SF12: Mental Health
    Pearson Correlation
    Component Score,
    Sig. (2-tailed)
    .000
    .022
    .000
    standardized
    N
    890
    866
    893
    **. Correlation is significant at the 0.01 level (2-tailed).
    *. Correlation is significant at the 0.05 level (2-tailed).
    893
    Scatterplot
    Descriptive Statistics
    Mean
    Std. Deviation
    N
    Body Mass Index
    29.2226
    7.37893
    970
    Weight-pounds
    171.4624
    45.44083
    971
    Correlations
    Body Mass
    Index
    Body Mass Index
    Pearson Correlation
    Weight-pounds
    1
    Sig. (2-tailed)
    N
    Weight-pounds
    .000
    970
    970
    **
    1
    Pearson Correlation
    .937
    Sig. (2-tailed)
    .000
    N
    970
    **. Correlation is significant at the 0.01 level (2-tailed).
    .937**
    971

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