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  • Data Analytics Question

    I uploaded the files which contains the Exercise and the other files to solve it.

    Please adhere to the following:

    1- Do not use artificial intelligence, as the university detects its use and has Turnitin.

    2- Do not duplicate assignments from other students.

    3- Submit within the specified timeframe,I have chosen four days.


    Assignment:

    Format: 1500-2000 words (Excluding graphs and charts) based on the guidelines below.

    I. Assignment Brief

    This assignment requires you to produce an academically grounded business analytics report.

    You are required to select one dataset from the pool of datasets provided on the assignment

    Loop submission link. All datasets have been sourced from open-access repositories and are

    approved for use for educational purposes only.

    Choose a dataset that aligns with an industry sector of interest to you (e.g. Healthcare

    Management, Human Resources, Marketing, Inventory Management, Transport, Education,

    etc.). Your role is to identify a business problem or opportunity that can be addressed

    analytically using the variables available in the selected dataset.

    Your task is to conduct the appropriate analytics processes to address the identified problem or

    opportunity and to present your findings in a business analytics report.

    In brief, a business analytics report is a structured document that presents data-driven insights to

    inform business decision-making. Using your chosen dataset, you are required to conduct descriptive,

    predictive, and prescriptive analytics.

    1. 2. II. Analytics Report Framework

    1. Organisational Context and Decision Challenge (20%)

    This section must demonstrate that the analytics work is grounded in a business need. You should

    include:

    Industry Context: Introduce the sector and explain the relevance of the dataset to a real

    industry setting.

    Decision Problem or Strategic Opportunity: Clearly define the business problem or

    opportunity. Business Value and Strategic Importance: Explain why this issue matters and what

    organisational value is sought (e.g., efficiency, growth, risk mitigation, optimisation).

    Analytics Objectives and Key Questions: Frame clear, data-answerable business questions

    aligned with the decision challenge.

    2. Working with Data and Analytical Design (20%)

    This section must demonstrate the use of the dataset to answer the business questions, not just

    technical execution. You should include:

    Dataset Overview and Variable Classification: Identify key predictors (independent variables)

    and targets (dependent variables).

    Data Exploration and Assumptions: Discuss patterns, outliers, and potential limitations.

    Data Preparation and Transformation: Explain cleaning steps and justification.

    Analytical Approach and Justification: Describe why specific descriptive, predictive, and

    prescriptive techniques were selected (you can limit the techniques to those taught in class).

    3. Analytical Execution and Evidence (30%)

    This section presents the analytic process and techniques in a structured analytical output.

    Descriptive steps and insights

    Predictive modelling results

    Prescriptive analysis and decision scenarios

    Analytics Dashboard: All key charts, tables, and visualisations must be presented together.

    Each visual must include a short managerial insight statement.

    4. Critical Evaluation and Managerial Insight (20%)

    This section discusses your evaluation of the results.

    Interpretation of results

    Discussion of reliability, assumptions, risks, and limitations.

    Managerial implications

    Demonstrate how analytical outputs are combined with your industry understanding to inform

    decisions.

    5. Recommendations and Decision Communication (5%)

    This section translates your analysis into action.

    Actionable recommendations

    Expected organisational impact

    Implementation considerations

    6. Housekeeping (5%)

    Harvard or APA referencing (include DOIs where available)

    Logical structure and coherent argumentation

    Table of contents

    Professional presentation of dashboard and appendices

    II. Minimum Requirements for Technical Analytics

    1. Descriptive Analytics

    a) Select four (4) variables from the dataset and formulate four (4) descriptive analytics

    questions that are relevant to your stated business problem.

    b) Produce data visualisations to support your descriptive analysis and summary statistics.c) Each visualisation must include a brief insight statement explaining what the visual shows

    and what decision or action it may inform.

    All descriptive analytics visualisations should be compiled and presented together in an

    analytics dashboard.

    2. Predictive Analytics

    Formulate and analyse at least one (1) predictive analytics question. Explain how the results of the

    analysis could influence or support the business decision or action.

    3. Prescriptive Analytics

    Formulate and analyse at least one (1) prescriptive analytics question. Clearly explain how the

    resulting recommendation would change or improve the business decision or action.

    Notes:

    1. 2. 3. Academic work at MSc level is expected to demonstrate independent research and critical

    judgement, supported by academic evidence and reputable third-party sources. Please use the

    Harvard or APA referencing style throughout your work.

    A wide range of relevant peer-reviewed journal articles covering all areas of analytics is

    available and should be consulted where appropriate.

    Plagiarism will not be tolerated. All sources must be properly acknowledged in accordance

    with the chosen referencing style.

    Requirements:

  • Data Analytics Question

    I uploaded the files which contains the Exercise and the other files to solve it.

    Please adhere to the following:

    1- Do not use artificial intelligence, as the university detects its use and has Turnitin.

    2- Do not duplicate assignments from other students.

    3- Submit within the specified timeframe,I have chosen four days.


    Assignment:

    Format: 1500-2000 words (Excluding graphs and charts) based on the guidelines below.

    I. Assignment Brief

    This assignment requires you to produce an academically grounded business analytics report.

    You are required to select one dataset from the pool of datasets provided on the assignment

    Loop submission link. All datasets have been sourced from open-access repositories and are

    approved for use for educational purposes only.

    Choose a dataset that aligns with an industry sector of interest to you (e.g. Healthcare

    Management, Human Resources, Marketing, Inventory Management, Transport, Education,

    etc.). Your role is to identify a business problem or opportunity that can be addressed

    analytically using the variables available in the selected dataset.

    Your task is to conduct the appropriate analytics processes to address the identified problem or

    opportunity and to present your findings in a business analytics report.

    In brief, a business analytics report is a structured document that presents data-driven insights to

    inform business decision-making. Using your chosen dataset, you are required to conduct descriptive,

    predictive, and prescriptive analytics.

    1. 2. II. Analytics Report Framework

    1. Organisational Context and Decision Challenge (20%)

    This section must demonstrate that the analytics work is grounded in a business need. You should

    include:

    Industry Context: Introduce the sector and explain the relevance of the dataset to a real

    industry setting.

    Decision Problem or Strategic Opportunity: Clearly define the business problem or

    opportunity. Business Value and Strategic Importance: Explain why this issue matters and what

    organisational value is sought (e.g., efficiency, growth, risk mitigation, optimisation).

    Analytics Objectives and Key Questions: Frame clear, data-answerable business questions

    aligned with the decision challenge.

    2. Working with Data and Analytical Design (20%)

    This section must demonstrate the use of the dataset to answer the business questions, not just

    technical execution. You should include:

    Dataset Overview and Variable Classification: Identify key predictors (independent variables)

    and targets (dependent variables).

    Data Exploration and Assumptions: Discuss patterns, outliers, and potential limitations.

    Data Preparation and Transformation: Explain cleaning steps and justification.

    Analytical Approach and Justification: Describe why specific descriptive, predictive, and

    prescriptive techniques were selected (you can limit the techniques to those taught in class).

    3. Analytical Execution and Evidence (30%)

    This section presents the analytic process and techniques in a structured analytical output.

    Descriptive steps and insights

    Predictive modelling results

    Prescriptive analysis and decision scenarios

    Analytics Dashboard: All key charts, tables, and visualisations must be presented together.

    Each visual must include a short managerial insight statement.

    4. Critical Evaluation and Managerial Insight (20%)

    This section discusses your evaluation of the results.

    Interpretation of results

    Discussion of reliability, assumptions, risks, and limitations.

    Managerial implications

    Demonstrate how analytical outputs are combined with your industry understanding to inform

    decisions.

    5. Recommendations and Decision Communication (5%)

    This section translates your analysis into action.

    Actionable recommendations

    Expected organisational impact

    Implementation considerations

    6. Housekeeping (5%)

    Harvard or APA referencing (include DOIs where available)

    Logical structure and coherent argumentation

    Table of contents

    Professional presentation of dashboard and appendices

    II. Minimum Requirements for Technical Analytics

    1. Descriptive Analytics

    a) Select four (4) variables from the dataset and formulate four (4) descriptive analytics

    questions that are relevant to your stated business problem.

    b) Produce data visualisations to support your descriptive analysis and summary statistics.c) Each visualisation must include a brief insight statement explaining what the visual shows

    and what decision or action it may inform.

    All descriptive analytics visualisations should be compiled and presented together in an

    analytics dashboard.

    2. Predictive Analytics

    Formulate and analyse at least one (1) predictive analytics question. Explain how the results of the

    analysis could influence or support the business decision or action.

    3. Prescriptive Analytics

    Formulate and analyse at least one (1) prescriptive analytics question. Clearly explain how the

    resulting recommendation would change or improve the business decision or action.

    Notes:

    1. 2. 3. Academic work at MSc level is expected to demonstrate independent research and critical

    judgement, supported by academic evidence and reputable third-party sources. Please use the

    Harvard or APA referencing style throughout your work.

    A wide range of relevant peer-reviewed journal articles covering all areas of analytics is

    available and should be consulted where appropriate.

    Plagiarism will not be tolerated. All sources must be properly acknowledged in accordance

    with the chosen referencing style.

    Requirements:

  • Nursing Question

    Weekly Objectives

    By the end of the week the students will:

    • Identify barriers to evidence-based translation within healthcare organizations.

    CLSLOs

    • Identify barriers to evidence-based translation within healthcare organizations
    • Interpret the principles of translational science and evidence-based practice.
    • Formulate the importance and impact of evidence-based practice on nursing & formulate and refine clinical research questions relevant to advanced nursing practice.
    • Analyze the role of leadership in promoting a culture of evidence-based practice within the nursing profession.
    • Identify barriers to evidence-based translation within healthcare organizations.
    • Identify barriers to evidence-based translation within healthcare organizations.
    • Evaluate translational models used to execute and sustain evidence-based practice changes.
    • Analyze the importance of implementing sustainable peered review processes in nursing practice.

    EOPSLOs

    • I-Integrate Scientific Underpinnings into Practice
    • II-Develop Organizational and Systems Leadership for Quality Improvement and Systems Thinking
    • III-Apply Clinical Scholarship and Analytical Methods for Evidence-Based Practice V-Influence Health Care Policy for Advocacy in Health Care

    PRSPC

    • Will demonstrate effective communication
    • Will demonstrate effective relationship management

    Requirements:

  • Management Question

    Instructions

    Individual Assignment Instructions:

    Research the library and Write a three to five page APA formatted essay on the pros and cons of the US retreat from the Kyoto Accords.

    Individual Assignment Resources:

    Each URL below is available from inside the APUS library page Paste the URL in the browser window, while logged into the library.

    APA GUIDELINES

    Submission Instructions:Written communication: Written communication is free of errors that detract from the overall message.
    APA formatting: Resources and citations are formatted according to APA style and formatting.
    Font and font size: Times New Roman, 12 point.

    Requirements: 3 PAGES

  • Unit 6

    Review the before completing the assignment.

    Your writing assignment should:

    • follow the conventions of Standard English (correct grammar, punctuation, etc.);
    • be well ordered, logical, and unified, as well as original and insightful;
    • be a minimum of 4 pages in length, not including cover or reference page;
    • display superior content, organization, style, and mechanics; and;
    • use APA formatting and citation style.

    Recall what you have learned in the program thus far related to stress effects on the mental and physical body as well as what resilience is. Discuss why it is important to build psychological resilience in yourself in order to best meet the needs of your patients.

    Write a 45 page paper addressing the following:

    1. What are the physical and mental effects of stress?
    2. What is psychological resilience, and why is it so important? (consider pathophysiology and coping skills)
    3. As a PMHNP, why is it important to build psychological resilience in yourself in order to best meet the needs of your patients?
    4. On a personal note, discuss a healthy coping mechanism that you have in place that will guide you to set healthy boundaries between work and home life as well as cope with stressful cases.
    5. What areas of improvement will you set as goals for yourself to work on for your own psychological resilience?

    Attached Files (PDF/DOCX): PMHNP_Writing_Assignment_Grading_Rubric.docx, HannaA_and_PidgeonA_2018 (2).pdf

    Note: Content extraction from these files is restricted, please review them manually.

  • Discussion 2

    the video is called or by sci universe unboxed it dost let share the video but is talking about positive psychology. is a guy with glasses talking in not sure if youre able to find the video . I was able to take some screenshots if you can look up for the video

  • Data Analytics Question

    I uploaded the files which contains the Exercise and the other files to solve it.

    Please adhere to the following:

    1- Do not use artificial intelligence, as the university detects its use and has Turnitin.

    2- Do not duplicate assignments from other students.

    3- Submit within the specified timeframe; I have chosen 4 days.

    Delivering Performance Excellence (DPE): Business Analytics

    Business Analytics Assessment: Individual Assignment

    Mark: 35% of DPE Module marks

    Submission date: 5th March 2026

    Required: Business Analytics Report

    Format: 1500-2000 words (Excluding graphs and charts) based on the guidelines below.

    I. Assignment Brief

    This assignment requires you to produce an academically grounded business analytics report.

    You are required to select one dataset from the pool of datasets provided on the assignment

    Loop submission link. All datasets have been sourced from open-access repositories and are

    approved for use for educational purposes only.

    Choose a dataset that aligns with an industry sector of interest to you (e.g. Healthcare

    Management, Human Resources, Marketing, Inventory Management, Transport, Education,

    etc.). Your role is to identify a business problem or opportunity that can be addressed

    analytically using the variables available in the selected dataset.

    Your task is to conduct the appropriate analytics processes to address the identified problem or

    opportunity and to present your findings in a business analytics report.

    In brief, a business analytics report is a structured document that presents data-driven insights to

    inform business decision-making. Using your chosen dataset, you are required to conduct descriptive,

    predictive, and prescriptive analytics.

    1. 2. II. Analytics Report Framework

    1. Organisational Context and Decision Challenge (20%)

    This section must demonstrate that the analytics work is grounded in a business need. You should

    include:

    Industry Context: Introduce the sector and explain the relevance of the dataset to a real

    industry setting.

    Decision Problem or Strategic Opportunity: Clearly define the business problem or

    opportunity. Business Value and Strategic Importance: Explain why this issue matters and what

    organisational value is sought (e.g., efficiency, growth, risk mitigation, optimisation).

    Analytics Objectives and Key Questions: Frame clear, data-answerable business questions

    aligned with the decision challenge.

    2. Working with Data and Analytical Design (20%)

    This section must demonstrate the use of the dataset to answer the business questions, not just

    technical execution. You should include:

    Dataset Overview and Variable Classification: Identify key predictors (independent variables)

    and targets (dependent variables).

    Data Exploration and Assumptions: Discuss patterns, outliers, and potential limitations.

    Data Preparation and Transformation: Explain cleaning steps and justification.

    Analytical Approach and Justification: Describe why specific descriptive, predictive, and

    prescriptive techniques were selected (you can limit the techniques to those taught in class).

    3. Analytical Execution and Evidence (30%)

    This section presents the analytic process and techniques in a structured analytical output.

    Descriptive steps and insights

    Predictive modelling results

    Prescriptive analysis and decision scenarios

    Analytics Dashboard: All key charts, tables, and visualisations must be presented together.

    Each visual must include a short managerial insight statement.

    4. Critical Evaluation and Managerial Insight (20%)

    This section discusses your evaluation of the results.

    Interpretation of results

    Discussion of reliability, assumptions, risks, and limitations.

    Managerial implications

    Demonstrate how analytical outputs are combined with your industry understanding to inform

    decisions.

    5. Recommendations and Decision Communication (5%)

    This section translates your analysis into action.

    Actionable recommendations

    Expected organisational impact

    Implementation considerations

    6. Housekeeping (5%)

    Harvard or APA referencing (include DOIs where available)

    Logical structure and coherent argumentation

    Table of contents

    Professional presentation of dashboard and appendices

    II. Minimum Requirements for Technical Analytics

    1. Descriptive Analytics

    a) Select four (4) variables from the dataset and formulate four (4) descriptive analytics

    questions that are relevant to your stated business problem.

    b) Produce data visualisations to support your descriptive analysis and summary statistics.c) Each visualisation must include a brief insight statement explaining what the visual shows

    and what decision or action it may inform.

    All descriptive analytics visualisations should be compiled and presented together in an

    analytics dashboard.

    2. Predictive Analytics

    Formulate and analyse at least one (1) predictive analytics question. Explain how the results of the

    analysis could influence or support the business decision or action.

    3. Prescriptive Analytics

    Formulate and analyse at least one (1) prescriptive analytics question. Clearly explain how the

    resulting recommendation would change or improve the business decision or action.

    Notes:

    1. 2. 3. Academic work at MSc level is expected to demonstrate independent research and critical

    judgement, supported by academic evidence and reputable third-party sources. Please use the

    Harvard or APA referencing style throughout your work.

    A wide range of relevant peer-reviewed journal articles covering all areas of analytics is

    available and should be consulted where appropriate.

    Plagiarism will not be tolerated. All sources must be properly acknowledged in accordance

    with the chosen referencing style

    Requirements:

  • Slo essay

    class name: Intro to Hr/peoplesoft applications Assignment Instructions: As we wrap up the course, take time to reflect on your personal journey and learning experience by completing the SLO Essay Project. This is your opportunity to express how the course has impacted you and to demonstrate thoughtful reflection about your academic and professional growth. Your essay should cover the following topics: Essay Prompts: Why did you choose to take this course? Share your personal or academic reasons. How does this course connect to your future goals? What did you find most and least valuable? Reflect honestly on what information stood out to you. What aspects helped you grow? What felt less relevant? How will this course benefit you moving forward? Can you apply any of the knowledge or skills in your career or life? Consider how these might look on a resume, in a job interview, or as part of your skill set. Final Thought: Make it YOU. This essay is all about your experiencebe creative, reflective, and have fun sharing your perspective! Formatting Guidelines: Minimum 2 full pages 12-point font, Times New Roman Double-spaced Use proper grammar and complete sentences

  • Data Analytics Question

    I uploaded the files which contains the Exercise and the other files to solve it.

    Please adhere to the following:

    1- Do not use artificial intelligence, as the university detects its use and has Turnitin.

    2- Do not duplicate assignments from other students.

    3- Submit within the specified timeframe,I have chosen four days.


    Format: 1500-2000 words (Excluding graphs and charts) based on the guidelines below.

    I. Assignment Brief

    This assignment requires you to produce an academically grounded business analytics report.

    You are required to select one dataset from the pool of datasets provided on the assignment

    Loop submission link. All datasets have been sourced from open-access repositories and are

    approved for use for educational purposes only.

    Choose a dataset that aligns with an industry sector of interest to you (e.g. Healthcare

    Management, Human Resources, Marketing, Inventory Management, Transport, Education,

    etc.). Your role is to identify a business problem or opportunity that can be addressed

    analytically using the variables available in the selected dataset.

    Your task is to conduct the appropriate analytics processes to address the identified problem or

    opportunity and to present your findings in a business analytics report.

    In brief, a business analytics report is a structured document that presents data-driven insights to

    inform business decision-making. Using your chosen dataset, you are required to conduct descriptive,

    predictive, and prescriptive analytics.

    1. 2. II. Analytics Report Framework

    1. Organisational Context and Decision Challenge (20%)

    This section must demonstrate that the analytics work is grounded in a business need. You should

    include:

    Industry Context: Introduce the sector and explain the relevance of the dataset to a real

    industry setting.

    Decision Problem or Strategic Opportunity: Clearly define the business problem or

    opportunity. Business Value and Strategic Importance: Explain why this issue matters and what

    organisational value is sought (e.g., efficiency, growth, risk mitigation, optimisation).

    Analytics Objectives and Key Questions: Frame clear, data-answerable business questions

    aligned with the decision challenge.

    2. Working with Data and Analytical Design (20%)

    This section must demonstrate the use of the dataset to answer the business questions, not just

    technical execution. You should include:

    Dataset Overview and Variable Classification: Identify key predictors (independent variables)

    and targets (dependent variables).

    Data Exploration and Assumptions: Discuss patterns, outliers, and potential limitations.

    Data Preparation and Transformation: Explain cleaning steps and justification.

    Analytical Approach and Justification: Describe why specific descriptive, predictive, and

    prescriptive techniques were selected (you can limit the techniques to those taught in class).

    3. Analytical Execution and Evidence (30%)

    This section presents the analytic process and techniques in a structured analytical output.

    Descriptive steps and insights

    Predictive modelling results

    Prescriptive analysis and decision scenarios

    Analytics Dashboard: All key charts, tables, and visualisations must be presented together.

    Each visual must include a short managerial insight statement.

    4. Critical Evaluation and Managerial Insight (20%)

    This section discusses your evaluation of the results.

    Interpretation of results

    Discussion of reliability, assumptions, risks, and limitations.

    Managerial implications

    Demonstrate how analytical outputs are combined with your industry understanding to inform

    decisions.

    5. Recommendations and Decision Communication (5%)

    This section translates your analysis into action.

    Actionable recommendations

    Expected organisational impact

    Implementation considerations

    6. Housekeeping (5%)

    Harvard or APA referencing (include DOIs where available)

    Logical structure and coherent argumentation

    Table of contents

    Professional presentation of dashboard and appendices

    II. Minimum Requirements for Technical Analytics

    1. Descriptive Analytics

    a) Select four (4) variables from the dataset and formulate four (4) descriptive analytics

    questions that are relevant to your stated business problem.

    b) Produce data visualisations to support your descriptive analysis and summary statistics.c) Each visualisation must include a brief insight statement explaining what the visual shows

    and what decision or action it may inform.

    All descriptive analytics visualisations should be compiled and presented together in an

    analytics dashboard.

    2. Predictive Analytics

    Formulate and analyse at least one (1) predictive analytics question. Explain how the results of the

    analysis could influence or support the business decision or action.

    3. Prescriptive Analytics

    Formulate and analyse at least one (1) prescriptive analytics question. Clearly explain how the

    resulting recommendation would change or improve the business decision or action.

    Notes:

    1. 2. 3. Academic work at MSc level is expected to demonstrate independent research and critical

    judgement, supported by academic evidence and reputable third-party sources. Please use the

    Harvard or APA referencing style throughout your work.

    A wide range of relevant peer-reviewed journal articles covering all areas of analytics is

    available and should be consulted where appropriate.

    Plagiarism will not be tolerated. All sources must be properly acknowledged in accordance

    with the chosen referencing style

    Requirements:

  • Long Answer Questions

    Part II. Longer Answer Questions (responses should be roughly a couple of detailed paragraphs). Be sure not only to state the main ideas and arguments but to explain them in specific detail. Examples help to illustrate your understanding. FOUR questions will be on the exam (that I select) and students will have to answer all four questions. (Students should be sure to answer all four questions so as not to lose substantial points!) 1. Define Subjective Ethical Relativism and explain how it differs from Ethical Objectivism and Conventional Relativism. Identify some strengths or appeals of the theory. Finally, explain two critiques Pojman makes against subjective relativism. Use an example to illustrate the criticisms. 2. Define Conventional Ethical Relativism and explain how it differs from Ethical Objectivism and Subjection Relativism. Next, identify some strengths or appeals of the theory. Select one of the main criticisms of Conventional Ethical Relativism and explain the argument in detail. Use an example or two that help to illustrate the criticism. 3. Define Psychological Egoism (as opposed to Ethical Egoism) and then explain the argument from Self-Satisfaction that is used to support it. What is the critique of this argument? Use an example to illustrate the critique. 4. Identify some of the main ideas of Ayn Rands virtue of selfishness. Summarize the main argument in support of her Ethical Egoism. What are two main criticisms of Rands egoism? Use an example to illustrate one of the criticisms. 5. Explain Hobbess theory of the state of nature. What are the consequences of this state? Next explain how social contract theory provides a solution to it. Be specific in showing why accepting this solution makes the most rational sense for an egoist. 6. What are Mills position regarding the morality of an action in its relation to: (a) self-sacrifice, (b) motive, and (c) that it takes too long to calculate which action will lead to greatest happiness. Again, use examples to illustrate the claims Mill makes. Finally, explain some critiques that can be made against these claims?

    Attached Files (PDF/DOCX): Link for text book.pdf, EthicalTheory2CReviewSheet2CExam2312CSpring262CWB.pdf

    Note: Content extraction from these files is restricted, please review them manually.