Capella University Descriptive Statistics and Data Visualizations Summary

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Mathematics

Capella University

Description

  • Create a descriptive statistics table and histogram for selected variables in a dataset. Write a 2-3 page narrative summary in a Word document and insert the table and histogram graphic into this document.

    Introduction

    Note: You are strongly encouraged to complete the assessments in this course in the order they are presented.Descriptive statistics play an important role in analyzing data. It numerically summarizes key characteristics of variables. Measures of central tendency (mean, median, and mode) and dispersion (variance, standard deviation, and range) characterize the probability distribution. A histogram visualizes the distribution of numerical data indicating the number of data points that lie within a range of values. For this assessment, you will perform descriptive statistics and create a histogram for selected variables in a dataset.

    Overview

    Note: Complete the assessments in this course in the order in which they are presented.

    Data Analysis Software

    To complete the assessments in this course, you will need to use data analysis software to complete statistical calculations, create graphs, and tabular summaries, and share your results in a Microsoft Word document. You will use Microsoft Excel and Microsoft Excel Analysis ToolPak add-in. Be aware that not all statistical calculations, graphs, and tabular summaries can be completed in this software, so you may need to do some work outside of the software.
    Microsoft Excel Data Analysis ToolPak Add-In for PC and Mac
    Microsoft Excel Analysis ToolPak Activation for PC Users: The Microsoft Excel Analysis ToolPak is a specialized Excel add-in included in the standard Microsoft Office suite. If your Excel software meets the standard Capella University Computer Requirements, you will not need to purchase this software. However, you may need to activate the application before you can use it. If you do not own Microsoft Excel, Capella arranges for a significant discount for Microsoft Office for Capella learners. The following provides an overview of the Analysis ToolPak, instructions for loading and activation and instructions on using the ToolPak to perform data analysis. Note that these instructions are for 2016 and older versions of Microsoft Excel for PC and for the 2016 version only for Mac. If you are using a different version, you may need to search Microsoft's website for the appropriate instructions.

    Preparation

    Download the Assessment 1 Dataset [XLSX]. The dataset contains the following variables:
    • utilization (average number of patient days per month).
    • satisfaction (patient satisfaction scores percentile rank).
    • readmissions (readmission rate per month).

    Instructions

    Nursing home administration has the objectives of higher utilization, higher patient satisfaction, and lower readmissions, and they need to make a decision on whether to retain the department manager based on average performance over the past 70 months. For this assessment, create a descriptive statistics table and histogram based on the Assessment 1 Dataset. Write a narrative summary in a Word and insert the table and histogram graphic into this document. See Copy From Excel to Another Office Program for instructions. Submit both the Word document and the Excel file that shows the descriptive statistics output.

    Grading Criteria

    The numbered assessment instructions outlined below correspond to the grading criteria in the Descriptive Statistics and Data Visualizations Scoring Guide, so be sure to address each point. You may also want to review the performance-level descriptions for each criterion to see how your work will be assessed.
    1. Perform the appropriate descriptive statistics for selected variables in a dataset.
      • Report descriptive statistics table with measures of central tendency and dispersion.
    2. Create a histogram that visually depicts the distribution of selected variables in a dataset.
    3. Interpret statistical results used in the data analysis.
    4. Write a narrative summary of the results that includes practical, administration-related implications of the descriptive statistics.
      • Write a separate summary for the histogram.
    5. Write clearly and concisely, using correct grammar, mechanics, and APA formatting.

    Additional Requirements

    Your assessment should meet the following requirements:
    • Written communication: Write clearly, accurately, and professionally, incorporating sources appropriately.
    • Length: 2–3 pages
    • Resources: Not applicable.
    • APA format: Cite your sources using current APA format.
    • Font and font size: Times Roman, 12 point.

    Competencies Measured

    By successfully completing this assessment, you will demonstrate your proficiency in the following course competencies and assessment criteria:
    • Competency 2: Analyze data using computer-based programming and software.
      • Perform the appropriate descriptive statistics for selected variables in a dataset.
    • Competency 3: Interpret results of data analysis for value-based health care decisions, policy, or practice.
      • Interpret statistical results used in the data analysis.
    • Competency 4: Present results of data analysis to support a decision or recommendation.
      • Create a histogram that visually depicts the distribution of selected variables in a dataset.
      • Write a narrative summary of the results that includes practical, administration-related implications of the descriptive statistics.
    • Competency 5: Communicate audience-appropriate health management content in a logically structured and concise manner, writing clearly with correct use of grammar, punctuation, spelling, and APA style.
      • Write clearly and concisely, using correct grammar, mechanics, and APA formatting.
      • SCORING GUIDE
  • Use the scoring guide to understand how your assessment will be evaluated.

Unformatted Attachment Preview

utilization satisfactionreadmissions 74,27057 100 0,084485 63,99188 16 0,177423 98,59192 31 0,164667 83,83318 3 0,178409 102,6872 89 0,007154 67,99378 22 0,150899 46,14154 19 0,044172 43,72361 29 0,048756 57,88714 79 0,165101 67,59221 59 0,142432 86,79082 70 0,020972 97,85154 26 0,064269 65,94915 22 0,126403 68,7699 51 0,160362 73,48808 10 0,143454 44,06588 52 0,117126 21,39799 8 0,096196 63,73128 6 0,058184 60,3591 21 0,122917 104,9315 35 0,124026 44,06642 19 0,068038 74,79688 19 0,094528 73,80654 12 0,147442 74,13603 7 0,098442 53,15719 45 0,207075 37,7386 71 0,036068 56,67985 6 0,104524 34,09113 62 0,118022 82,18294 57 0,207321 117,4468 55 0,145666 72,63796 69 0,089209 66,48575 99 0,101125 60,31853 78 0,075609 97,4345 60 0,150218 55,71568 74 0,124018 78,65189 37 0,124208 101,5713 15 0,187252 65,80222 11 0,026605 76,79661 11 0,10254 73,13039 96 0,075294 44,72086 29 0,056506 98,73114 96 0,048891 33,8434 83 0,174334 84,88798 78 0,131844 52,40842 96 0,167126 57,31398 81 0,112467 52,43385 65,57764 83,33311 43,04142 37,8057 74,8687 69,84653 65,56504 60,51123 71,25343 54,01618 51,56944 66,47474 110,626 35,71084 107,777 73,49521 96,69419 105,5554 64,83288 61,43368 69,81598 114,9896 87,70982 70 99 96 91 58 38 59 79 88 38 13 54 35 63 56 22 90 28 8 94 78 7 27 50 0,061826 0,131735 0,081496 0,099062 0,073216 0,144065 0,042271 0,030994 0,119027 0,180316 0,08865 0,106493 0,022939 0,162756 0,098004 0,078145 0,065701 0,119516 0,103598 0,015921 0,123979 0,114584 0,081302 0,10172 NOTES PROFESSOR LEFT ON LAST ATTEMPT COMPETENCY 1 Analyze data using computer-based programming and software. CRITERION Perform the appropriate descriptive statistics for selected variables in a dataset. Faculty Comments: Criteria 1 MET: Good job. You used MS Excel Data Analytics "add-in" ToolPak module functions that have the formula built into the Excel spreadsheet the statistic functionality. (MS, 2020). COMPETENCY 3 Present results of data analysis to support a decision or recommendation. CRITERION Create a histogram that visually depicts the distribution of selected variables in a dataset. Faculty Comments: Criteria 2 MET: Really good histograms and bins (intervals/ranges) in the y and xaxes. The histogram is an effective graphical technique for showing both the skewness and kurtosis of the data set. The histogram is a distribution of your dataset. The normal distribution is a symmetric distribution with well-behaved tails. The skewness for a normal distribution is zero, and any symmetric data should have a skewness near zero. Negative values for the skewness indicate data that are skewed left and positive values for the skewness indicate data that are skewed right. By skewed left, we mean that the left tail is long relative to the right tail. Similarly, skewed right means that the right tail is long relative to the left tail. If the data are multi-modal, then this may affect the sign of skewness. COMPETENCY 2 Interpret results of data analysis for value-based health care decisions, policy, or practice. CRITERION Interpret statistical results used in the data analysis. Faculty Comments: Benchmarks are helpful often helpful to analyze and judge how well the organization is doing. Is utilization good, bad, and why? Is satisfaction good, bad, and why? Is readmission good, bad, and why? Mean risk-adjusted rates of community discharge and potentially avoidable readmissions, 2011†“ 2017 (Smith, et al., 2019). Measure---------------------------------------------------2011----2013-----2015-----2016-----2017 Potentially avoidable readmissions: -During SNF Stay------------------------------------------12.4-----11.2-----10.4-----10.9-----10.9 -During 30 days after discharge from SNF-------------5.9------5.5------5.0-------5.8------6.1 Relatively Efficient SNFs (Benchmark) -Medicare average length of stay-------------30 days -Medicare Occupancy rate--------------------87% (What is the occupancy rate in this case?) Reference: Smith, L., Coots-Daras, L., Van-Skinner, C. (2019). Skilled Nursing Facility 30-Day All-Cause Readmission Measure (SNFRM). RTI International. Created for CMS Contract No. HHSM-5002013-13015I Task Order HHSM-500-T0001. April 2019. Retrieved from https://www.cms.gov/Medicare/Quality-Initiatives-Patient-Assessment-Instruments/ValueBased-Programs/SNF-VBP/Downloads/SNFRM-TechReportSupp-2019-.pdf COMPETENCY 3 Present results of data analysis to support a decision or recommendation. CRITERION Write a narrative summary of the results that includes practical, administration-related implications of the descriptive statistics. Faculty Comments: The results look mixed for this case. However, the results are really poor for all 3 measures because if the bed census is low, so you would expect the readmission rate to also be shown as low. Therefore, we do not really know what the readmission rates would be if the beds were full, and thus readmissions are skewed. Whether you retain or terminate this NH Manager, you would want to make them accountable for the organization's performance. Be very specific in your management decision or recommendations based on the statistical results. The focus of this class is using data for management decision-making. Each case requires a definitive Management decision or recommendation. What questions does this case want you to answer? What management decision will you make for this case? Narrative: Things to think about for this case is that the results for Utilization, Satisfaction and Readmissions are mixed. Are they significant enough to terminate the Manager? Does the Manager need a Performance Improvement Plan (PIP)? Or, should you retain the Manager? This is a leadership decision, therefore, your decision, however, I encourage exploring all of the pros and cons. You also want to hold the NH Manager accountable for the NH performance. You can do this by developing a strategic plan with specific goals that they are required to achieve. What are the goals you want the NH Administrator to focus on? This class is a "management decision" making class using statistics and analysis in each assignment. Explore and explain some pros and cons of your decisions, supported with evidence-based sources. Example Evidence-Based, Peer-Reviewed, and Primary Source references that support the narrative: Primary Source reference: SHRM.org Society of Human Resource Management (SHRM). (2017). Performance Management that Makes a Difference: An Evidence-Based Approach. Science-to-Practice Series. Retrieved from https://www.shrm.org/hr-today/trends-and-forecasting/special-reports-and-expertviews/documents/performance%20management.pdf Evidence-Based Research reference: Peer-Reviewed Research Song, M., Meier, K. J., & Amirkhanyan, A. (2020). Goal Ambiguity, Management, and Performance in U.S. Nursing Homes. Administration & Society, 52(8), 1170†“ 1208. https://doi.org/10.1177/0095399720901343 COMPETENCY 4 Communicate audience-appropriate health management content in a logically structured and concise manner, writing clearly with correct use of grammar, punctuation, spelling, and APA style. CRITERION Write clearly and concisely, using correct grammar, mechanics, and APA formatting. Faculty Comments: NOTES: At the Master's level, it is required that any written paper be supported with a minimum of 3 scholarly references, preferably more. Paper Headings/Subheadings: In any paper, always start with a short introduction of what it is about, then your headings/subheadings, then a brief summary to highlight the key points and a Management Decision. The focus of this class is using data for management decision-making. The papers are executive summaries of your statistical results and management decision-making. So, with that said, you want them to be a very professional, well-organized paper. My suggestion is that you use the Grading Rubrics, i.e., create an outline and use the outline as Headings and Subheadings, i.e., 1. 2. 3. 4. 5. Introduction-what the paper will be about. Statistics, which includes your results tables or graphs. Interpretation of the statistical results. Narrative summary with a supported management decision. Conclusion 10/2/21, 12:20 AM Descriptive Statistics and Data Visualizations Scoring Guide Descriptive Statistics and Data Visualizations Scoring Guide CRITERIA NONPERFORMANCE BASIC PROFICIENT DISTINGUISHED Perform the appropriate descriptive statistics for selected variables in a dataset. Does not perform the appropriate descriptive statistics for selected variables in a dataset. Incorrectly performs the appropriate descriptive statistics for selected variables in a dataset. Performs the appropriate descriptive statistics for selected variables in a dataset. Performs the appropriate descriptive statistics for selected variables in a dataset. Ensures the table is complete, follows the correct format, is well constructed, and is easy to read. Create a histogram that visually depicts the distribution of selected variables in a dataset. Does not create a histogram that visually depicts the distribution of selected variables in a dataset. Creates a histogram that visually depicts the distribution of selected variables in a dataset but it is incomplete or contains errors. Creates a histogram that visually depicts the distribution of selected variables in a dataset. Creates a histogram that visually depicts the distribution of selected variables in a dataset. Ensures the histogram is accurate, well constructed, and easy to interpret. Interpret statistical results used in the data analysis. Does not interpret statistical results used in a data analysis. Interprets statistical results of an analysis but the interpretation is incomplete, inaccurate, or logically inconsistent with the data. Interprets statistical results used in the data analysis. Interprets statistical results used in the data analysis. Ensures the interpretation is complete, provides a perceptive and clearly articulated conclusion, and includes an assessment of caveats and limitations. Write a narrative summary of the results that includes practical, administrationrelated implications of the descriptive statistics. Does not write a narrative summary of the results that includes practical, administrationrelated implications of the descriptive statistics. Writes a narrative summary of the results that contains incorrect or insufficient administration-related implications of the descriptive statistics. Writes a narrative summary of the results that includes practical, administrationrelated implications of the descriptive statistics. Writes a scholarly narrative summary of the results that includes practical, administration-related implications of the descriptive statistics. Draws valid, fully justified conclusions well supported by scholarly literature. Write clearly and concisely, using correct grammar, mechanics, and APA formatting. Does not write clearly and concisely, using correct grammar, mechanics, and APA formatting. Writes in a manner that is unclear and disorganized, includes errors in grammar and mechanics that inhibit effective communication, or contains incorrect or improperly formatted source citations and references. Writes clearly and concisely, using correct grammar, mechanics, and APA formatting. Writes clearly and concisely. Ensures grammar, mechanics, and APA formatting are error free. https://courserooma.capella.edu/bbcswebdav/institution/MHA-FPX/MHA-FPX5017/210700/Scoring_Guides/a01_scoring_guide.html 1/1 Running head: DESCRIPTIVE STATISTICS AND DATA VISUALIZATIONS Descriptive Statistics and Data Visualizations Data Analysis for Health Care Decisions Capella University August 30, 2021 Descriptive Statistics for Measures of Central Tendency and Dispersion 1 DESCRIPTIVE STATISTICS AND DATA VISUALIZATION Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum Maximum Sum Count Utilization 69.82198 2.586369 67.793 #N/A 21.63912 468.2515 -0.36956 0.239966 96.04878 21.39799 117.4468 4887.539 70 Satisfaction 49.35714 3.694719 51.5 96 30.91223 955.5663 -1.36249 0.119794 97 3 100 3455 70 Histogram Utilization Frequency Utilization Histogram 40 30 20 10 0 20 40 60 80 100 120 More Bin Satisfaction Satisfaction Histogram Frequency 20 15 10 5 0 0 20 40 60 Bin Readmissions 80 100 More 2 Readmissions 0.105987 0.005776 0.104061 #N/A 0.048329 0.002336 -0.60375 -0.0105 0.200167 0.007154 0.207321 7.419095 70 DESCRIPTIVE STATISTICS AND DATA VISUALIZATION 3 Readmissions Histogram Frequency 40 30 20 10 0 0 0.1 0.15 0.2 0.25 0.3 More Bin Interpretation and Summary of Statistical Results As established, data for Readmissions seems to be more centrally placed around the mean as compared to that of Utilization and Satisfaction. The case is given by the fact that the standard deviation for the Readmissions dataset at, 0.048329, is the lowest of the 3. Also, the range of the dataset at, 0.200167, is the lowest. Data for Satisfaction appears to be highly dispersed of the three variables, given that its variance is the highest, at 955.5663 (Black & Masten, 2020). Satisfaction is the only variable that has a mode, which is a value that appears more than once; 96. The level of skewness of the values from the mean for Readmissions is also deemed to be significantly low, at -0.0105. The skewness from the mean for Utilization at 0.239966, is deemed to be very high. Therefore, the case means that the predictability of data for Readmissions is bound to be higher than that of Utilization (Goneppanavar, Ali, Bhaskar, & Divatia, 2019). The hospital management can easily make decisions around Readmissions as compared to one that it could make as it pertains to Utilization. Summary of Histogram DESCRIPTIVE STATISTICS AND DATA VISUALIZATION 4 Based on the histogram computation, data for Utilization and Readmissions appear to rise as it moves towards the mid values before declining steadily. However, data for Satisfaction does not have a distinct shape and has fluctuations in it. References DESCRIPTIVE STATISTICS AND DATA VISUALIZATION Black, W. H., & Masten, L. B. (2020). Empirical Investigation of Alternative Measures of Central Tendency. Journal of Forensic Accounting Research, 5(1), 216-256. https://doi.org/10.2308/JFAR-19-030 Goneppanavar, U., Ali, Z., Bhaskar, S. B., & Divatia, J. V. (2019). Types of data, methods of collection, handling and distribution. Airway, 2(1), 36. https://www.arwy.org/article.asp?issn=26659425;year=2019;volume=2;issue=1;spage=36;epage=40;aulast=Goneppanavar 5 utilization Bin 74.27056954 63.99188284 98.59192257 83.83318212 102.6871802 67.99377691 46.14154034 43.72361464 57.88713726 67.59221338 86.79081725 97.85154455 65.94915051 68.76990274 73.48808447 44.06587746 21.39799373 63.73128349 60.35910446 104.9315102 44.06642223 74.7968829 73.80654405 74.13602894 53.1571873 37.73860199 56.67984641 34.09112699 82.18293693 117.4467723 72.6379605 66.48574683 60.3185256 97.43450181 55.71567771 78.65188652 101.5712693 65.80222227 76.79660638 73.13038906 44.72085933 98.7311357 33.84339854 84.88798296 52.4084181 satisfaction 20 40 60 80 100 120 Bin 100 16 31 3 89 22 19 29 79 59 70 26 22 51 10 52 8 6 21 35 19 19 12 7 45 71 6 62 57 55 69 99 78 60 74 37 15 11 11 96 29 96 83 78 96 0 20 40 60 80 100 readmissions Bin 0.084484827 0.177422977 0.164666974 0.178409165 0.007154269 0.150898989 0.044172167 0.048756409 0.165100719 0.142431915 0.020972093 0.064269433 0.126402713 0.160361531 0.143454174 0.117126077 0.096196262 0.058183692 0.122917387 0.124026435 0.068037548 0.094527829 0.147442146 0.098442344 0.207074904 0.036068172 0.104523644 0.118021847 0.207321088 0.14566582 0.089209326 0.101125202 0.075608557 0.1502176 0.124018043 0.124207699 0.187252169 0.026605422 0.102539843 0.075293593 0.0565061 0.048890597 0.17433435 0.13184357 0.167126172 0 0.1 0.15 0.2 0.25 0.3 57.313983 52.43385028 65.57764052 83.33310893 43.04142378 37.80570282 74.86869799 69.84653266 65.56504003 60.51123203 71.25342663 54.01618366 51.5694412 66.47474127 110.6260107 35.71083798 107.7769648 73.49520956 96.69419044 105.5553666 64.83288061 61.43368345 69.81597841 114.9896157 87.70981944 81 70 99 96 91 58 38 59 79 88 38 13 54 35 63 56 22 90 28 8 94 78 7 27 50 0.112466728 0.061826191 0.131734982 0.081495838 0.099062442 0.07321605 0.144065398 0.042271049 0.030993855 0.119027408 0.180316374 0.088649967 0.106493072 0.022938534 0.162755757 0.098004264 0.07814496 0.065701279 0.119515767 0.103598281 0.015920836 0.123978709 0.114583695 0.081302123 0.101719804 Utilization Satisfaction Readmissions Minimum 21.39799 Minimum 3 Minimum 0.007154 Maximum 117.4468 Maximum 100 Maximum 0.207321 20 40 60 80 100 120 More Frequency 0 6 15 30 11 8 0 Utilization Histogram Frequency Bin 40 30 20 10 0 Frequency 20 40 60 80 100 120 More Bin 0 20 40 60 80 100 More Frequency 0 17 15 12 12 14 0 Satisfaction Histogram Frequency Bin 20 15 10 5 0 Frequency 0 20 40 60 80 100 More Bin 0 0.1 0.15 0.2 0.25 0.3 More Frequency 0 31 25 12 2 0 0 Readmissions Histogram Frequency Bin 40 30 20 10 0 Frequency 0 0.1 0.15 0.2 Bin 0.25 0.3 More Frequency Frequency Frequency
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View attached explanation and answer. Let me know if you have any questions.Hey there,I have completed this assignment 100% with accuracy and perfection. The analysis has been performed in excel and a detailed report has been written for you. I have uploaded both the files as a draft for now so that you can review them. If you want me to reduce the length of the report or many any changes/additions just send me a message and I will fix that for you :)If all is perfect, then mark this question as completed with a good tip :)I am now waiting for your feedback :)

Running head: STATISTICS REPORT

1

Descriptive Statistics and Data Visualizations
Student’s Name
Institutional Affiliation

STATISTICS REPORT

2
Descriptive Statistics and Data Visualizations
Introduction

The ultimate objective of the administration in a nursing home is higher patient
satisfaction, higher utilization, and lower readmission. The purpose of this report is to analyze
the performance of the departmental manager based on these three key measures and make a
final decision regarding whether the administration should retain the department manager or not.
Descriptive statistics and histograms will be generated for each of the three variables to analyze
the performance of the nursing home. The final decision would be made by comparing the data
analysis with the set benchmarks of the industry.
Statistics and Interpretation of the Statistical Results
Descriptive Statistics
The descriptive statistics have been generated for each variable in an excel spreadsheet
using the Data Analysis ToolPak (Black & Masten, 2020). These are shown in table 1 below:
Variables
Particulars
Mean
Standard Error
Median
Mode
Standard Deviation
Sample Variance
Kurtosis
Skewness
Range
Minimum
Maximum
Sum
Count

utilization

satisfaction

69.8219826
49.35714286
2.58636947
3.694718726
67.79299514
51.5
#N/A
96
21.63911949
30.91223467
468.2514923
955.5662526
-0.369564621
-1.362485489
0.239965528
0.119793849
96.04877859
97
21.39799373
3
117.4467723
100
4887.538782
3455
70
70
Table 1: Descriptive Statistics

readmissions
0.105987074
0.005776462
0.104060962
#N/A
0.048329353
0.002335726
-0.603746401
-0.010495708
0.200166819
0.007154269
0.207321088
7.419095158
70

STATISTICS REPORT

3

Table 1 above shows the summary of the entire dataset for each of the three variables.
The average utilization rate for the past 70 months is 69.82, with a standard deviation of 21.64
and a median value of 67.79. The goal of the nursing home is to maximize the utilization rate
equal to its standard deviation of 21.64, but it is far from close to this. Therefore, the nursing
home has a lot of room for improving its utilization rate to achieve 91.46 (69.82+21.64). The
range of 96.04 is too high for the current values.
The average satisfaction score for the past 70 months is 49.836, with a standard deviation
of 30.631 and a median value of 51.5. The goal of the nursing home is to maximize the
satisfaction scores and bring them close to the mode value of 96. Therefore, the nursing home
has a lot of room for improving its satisfaction score to achieve an average score of 96. The
range value for this measure is also too high.
The average readmission rate for the past 70 months is 0.11, with a standard deviation of
0.04 and a median value of 0.10. The goal of the nursing home is to reduce the readmission rate
by at least 0.04, which can mean a significant improvement. High quality healthcare and
healthcare improvements can help to reduce the readmission rates for the nursing home.
Histograms
The histograms have been generated for each of the three variables using an excel
spreadsheet, and these are shown below:

STATISTICS REPORT

4

Utilization Histogram
30

15
11
0
20

8

6
40

0
60

80

100

120

MORE

Figure 1: Utilization Histogram
Figure 1 shows the histogram for the utilization variable, and it is a bell-shaped curve
which means that the data for this variable is normally distributed. In other words, the
fluctuations in the utilization rates might be huge, but they are consistent, and thus the above
histogram is symmetrical in shape. The skewness value is close to 0, which means the data is not
skewed. Kurtosis, on the other hand, is -0.36, which means tails are thin, and distribution is flat,
as depicted in the above figure.

Satisfaction Histogram
17
15

14
12

12

0
0

0
20

40

60

80

100

MORE

STATISTICS REPORT

5
Figure 2: Satisfaction Histogram

The histogram for satisfaction scores in figure 2 is not normally distributed, and the shape
of the distribution is not symmetric. The skewness value is close to 0 because the data is not
skewed, but it is also not normally distributed with a bell-shaped curve. The kurtosis is also
negative for this variable as tails are thin and distribution is flat.

Readmission Histogram
31
25

12

0
0

0.1

0.15

0.2

2

0

0

0.25

0.3

MORE

Figure 3: Readmission Histogram
The histogram in figure 3 for the readmission variable shows that the data is not normally
distributed, and it is rightward skewed. This means that the right tail is long as compared to the
left tail. The kurtosis for readmission rates is -0.6, indicating that tails are thin and distribution is
flat.
Narrative Summary with a Supported Management Decision
The performance of the nursing home based on all three measures is poor to average. The
utilization rate is low, and so the readmission rates are also low, and the overall results of the
statistical analysis are mixed. If the average statistics of the nursing home are compared with

STATISTICS REPORT

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industry benchmarks, then the performance of the nursing home can be accurately analyzed.
Medicare's average length of stay is 30 days, with an occupancy rate of 87% (Smith et al., 2019).
...


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