Descriptive Statistics Nursing Paper

Descriptive Statistics Nursing Paper

Descriptive Statistics Nursing Paper

This week, you explore key statistical concepts related to data and problem solving through the completion of the following exercises using SPSS and the information found in your Statistics and Data Analysis for Nursing Research textbook. The focus of this assignment is to become familiar with the SPSS data analysis software and to develop an understanding of how to calculate descriptive statistics and make conclusions based on those calculations. As you formulate your responses, keep in mind that descriptive statistics only allow you to make conclusions and recommendations for the sample at hand—not for the larger population to which that sample may belong.

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To prepare:

  • Review      the Statistics and Data Analysis for Nursing Research chapters      assigned in this week’s Learning Resources. Pay close attention to the      examples presented, as they provide information that will be useful when      you complete the software exercise this week. You may also wish to review      the Research Methods for Evidence-Based Practice video      resources to familiarize yourself with the software.
  • Refer      to the Week      4 Descriptive Statistics Assignment page and follow      the directions to calculate descriptive statistics for the data provided      using SPSS software. If you run into any difficulties or problems, post      them to the Week 4 Discussion 2 area (see attached file)
  • Download      and save the Polit2SetA.sav (see      attached file) data set. You will open the data file in SPSS.
  • Compare      your data output against the tables presented in the Week 4 Descriptive Statistics SPSS Output      document (see attached file) This will enable you to become      comfortable with defining variables, entering data, and creating tables      and graphs.
  • Formulate      an initial interpretation of the meaning or implication of your      calculations.

To complete:

 

Required Media

Laureate Education, Inc. (Executive Producer). (2011). Research methods for evidence-based practice: Quantitative research: Data analysis. Baltimore, MD: Author.

Note: The approximate length of this media piece is 10 minutes.

In this week’s video, the presenter describes challenges to collecting and utilizing quantitative data and offers suggestions for assessing and improving data quality. The strategic use of quantitative data by health care organizations is also considered. Descriptive Statistics Nursing Paper

Introduction to SPSS”

Used by permission from SPSSVideoTutor.com A division of ConsumerRaters LLC., 1121 S Military Trail, 314, Deerfield Beach, FL 33442, USA

Descriptive Statistics”

Used by permission from SPSSVideoTutor.com A division of ConsumerRaters LLC., 1121 S Military Trail, 314, Deerfield Beach, FL 33442, USA

Note: The approximate length of this media piece is 12 minutes.

Note: The approximate length of this media piece is 11 minutes.

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Required Readings

Gray, J.R., Grove, S.K., & Sutherland, S. (2017). Burns and Grove’s the practice of nursing research: Appraisal, synthesis, and generation of evidence (8th ed.). St. Louis, MO: Saunders Elsevier.

  • Chapter      21, “Introduction to Statistical Analysis”

This chapter discusses the concepts of statistical analysis with regard to hypothesis testing. The chapter also identifies and defines common statistical terminology.

Polit, D. (2010). Statistics and data analysis for nursing research (2nd ed.). Upper Saddle River, NJ: Pearson Education Inc.

  • Chapter      1, “Introduction to Data Analysis in an Evidence-Based Practice      Environment”

This chapter provides an introduction to quantitative and qualitative data in evidence-based practice. The chapter introduces levels of measurement and types of statistical analyses relevant to different types of research studies.

  • Chapter      2, “Frequency Distributions: Tabulating and Displaying Data”

Chapter 2 discusses frequency distributions as well as the different methods of presenting data, especially when data are very extensive. The chapter includes information on the use of bar charts, pie charts, histograms, and frequency polygons.

  • Chapter      3, “Central Tendency, Variability, and Relative Standing”

This chapter examines the many ways data distribution for a quantitative variable can be described through shape, central tendency, and variability.

Software

IBM SPSS Statistics Standard GradPack (current version). Available in Windows and Macintosh versions. Please refer to the IBM SPSS Software area in the Course Overview section on the left navigation bar for more information on how to install, register, and license this software.

Optional Resources

Bilheimer, L. T., & Klein, R. J. (2010). Data and measurement issues in the analysis of health disparities. Health Services Research, 45(5), 1489–1507. doi:10.1111/j.1475-6773.2010.01143.x

Granberg-Rademacker, J. S. (2010). An algorithm for converting ordinal scale measurement data to interval/ratio scale. Educational & Psychological Measurement, 70(1), 74–90.

This site provides step-by-step procedures and screenshots for working with SPSS.

Walden University. (n.d.). Descriptive statistics. Retrieved August 1, 2011, from http://streaming.waldenu.edu/hdp/researchtutorials/educ8106_player/educ8106_descriptive_stats.html

  • attachment

    Week_4_Descriptives_SPSSoutput.pdf

    Week 4 Descriptive Statistics Exercises SPSS Output

     

    Part I

    Respondent’s Age

    Descriptive Statistics

    N Minimum Maximum Mean Std. Deviation Skewness

    Statistic Statistic Statistic Statistic Statistic Statistic Std. Error

    Respondent’s age at time of

    interview

    1000 19.378 49.430 36.63733 6.198741 -.374 .077

    Valid N (listwise) 1000

    Highest School Grade Completed

    Descriptive Statistics

    N Minimum Maximum Mean Std. Deviation Skewness

    Statistic Statistic Statistic Statistic Statistic Statistic Std. Error

    Highest school grade

    completed

    989 1 16 11.28 1.561 -.727 .078

    Valid N (listwise) 989

     

    Race and Ethnicity

    Race/ethnicity

    Frequency Percent Valid Percent

    Cumulative

    Percent

    Valid Black, not Hispanic 803 80.3 80.5 80.5

    Hispanic 128 12.8 12.8 93.3

    White, not Hispanic 53 5.3 5.3 98.6

    Other 14 1.4 1.4 100.0

    Total 998 99.8 100.0

    Missing Refused 1 .1

    DK 1 .1

    Total 2 .2

    Total 1000 100.0

     

     

     

    Currently Employed

    Currently employed?

    Frequency Percent Valid Percent

    Cumulative

    Percent

    Valid No 546 54.6 54.7 54.7

    Yes 452 45.2 45.3 100.0

    Total 998 99.8 100.0

    Missing System 2 .2

    Total 1000 100.0

    Part II

     

     

     

    Part III Family Income

    Descriptive Statistics

    N Minimum Maximum Mean Std. Deviation Skewness

    Statistic Statistic Statistic Statistic Std. Error Statistic Statistic Std. Error

    Family income prior month,

    all sources

    895 $0 $6,593 $1,172.59 $26.345 $788.153 2.030 .082

    Valid N (listwise) 895

  • attachment

    Polit2SetA.sav
  • attachment

    Week_4_Descriptives_and_Frequencies_CE1.docx

    Week 4 Descriptive Statistics

    Part I

    Using the Polit2SetA data set, run descriptive statistics on the following variables: respondent’s age (age) and highest school grade completed (higrade). Create a frequency distribution for the variables: race and ethnicity (racethn) and currently employed (worknow). Create a table (in APA format) summarizing the results, using the below table shell as a model. Write a paragraph summarizing the information in the table. Descriptive Statistics Nursing Paper

    Table 1. Demographic Data (N = 30)

    n % M (SD)

    Age (in years) 30 15(2.4)

    Highest School Grade Completed 29 11(1.2)

    Race and Ethnicity

    Black, Not Hispanic 14 (46.67)

    Hispanic 8 (26.67)

    White, Not Hispanic 6 (20.0)

    Other 2 (6.66)

    Currently Employed

    Yes 27 (90)

    No 3 (10)

    Note. Differences in sample size are due to missing data.

    Follow these steps when using SPSS:

    1. Open Polit2SetA data set.

    2. Click on Analyze, then click on Descriptives Statistics, then Descriptives.

    3. Click on the first continuous variable you wish to obtain descriptives for (respondent’s age), and then click on the arrow button and move it into the Variables box. Then click on highest school grade completed and then click on the arrow button and move it into the Variables box.

    4. Click on the Options button in the upper-right corner. Click on meanstandard deviationminimummaximum, and skewness.

    5. Click on Continue and then click on OK.

    To run the frequency distribution in SPSS, do the following:

    1. Click on Analyze, then click on Descriptive Statistics, then Frequencies.

    2. Click on the first categorical variable you wish to obtain a frequency for (race and ethnicity), and then click on the arrow button and move it into the Variables box. Then click on currently employed, and then click on the arrow button and move it into the Variables box. Click on the Statistics button in the upper-right corner, then in the Dispersion box click on Minimum and Maximum.

    3. Click on Continue and then click on OK.

    Assignment: Create a table (in APA format) summarizing the results, using the below table shell as a model. Write a paragraph summarizing the information in the table.

     

    Part II

    For the variables respondent’s age (age) and highest school grade completed (higrade) create a histogram with a normal curve displayed over the histogram.

    To create a histogram for respondent’s age in SPSS, do the following:

    1. Click on Graphs, then on Legacy Dialogs, then Histogram.

    2. Click on the variable respondent’s age and then click on the arrow button and move it into the Variables box. Click on the Display Normal Curve button, which is right below the Variables box.

    3. Click on OK.

    To create a histogram for highest school grade completed in SPSS, do the following:

    1. Click on Graphs, then on Legacy Dialogs, then Histogram.

    2. Click on respondent’s age in the Variable box and click the arrow to move it back to the box on the left that contains all the variables.

    3. Click on the variable highest school grade completed and then click the arrow button and move it into the Variables box. The Display Normal Curve button should alredy be on.

    4. Click on OK.

     

    Assignment: Using the data obtained when you ran the descriptives and the histograms, determine whether the data skewed. If so, is it a positive or negative skew?

     

    Part III

    Using the Polit2SetA data set, run descriptive statistics on the variable “Family Income Prior Month, all sources” (Income). Descriptive Statistics Nursing Paper

    Follow these steps when using SPSS:

    1. Click on Analyze, then click on Descriptives Statistics, then Descriptives.

    2. Click on Family Income Prior Month, all sources, and then click on the arrow button and move it into the Variables box.

    3. Click on the Options button in the upper-right corner. Click on meanstandard deviationminimummaximumS.E. Mean (standard error of the mean), and skewness.

    4. Click on Continue and then click on OK.

    Assignment: Using the descriptive statistics for Family Income Prior Month, all sources (Income), answer the following questions:

    1. What is the mean income in this sample?

    2. What is the standard deviation?

    3. What is the standard error of the mean?

    4. Compute a 95% confidence interval around the mean. (Use 1.96 for the 95% CI and get the standard error from the descriptive statistics table). The formula is as follows:

    95% CI = [mean ± (1.96 SE)]

    5. Compute a 99% confidence interval around the mean. (Use 2.58 for the 99% CI and get the standard error from the descriptive statistics table). The formula is as follows:

    99% CI = [mean ± (2.58 SE)]

    6. Which interval is wider? Explain.

    Review the corresponding Week 4 Descriptive Statistics Exercises SPSS Output document that has the SPSS output for the above problems. Compare your output with the output in the file.