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1 Week 8 Final Exam – Ethics Professor’s Name Student’s Name Institutional Affiliation Course Submission Date

2 Week 8 Final Exam – Ethics The Importance of Evidence-Based Management: Enhancing Credibility through Statistical Analysis Introduction: Research-based management is a crucial aspect of organizational decision-making, wherein data analysis allows for a comprehensive understanding of the methods and processes that impact an organization. By relying on evidence-based management (EBMgt), decision- makers can make informed choices, based on factual information and unbiased analysis, to ensure the overall health and success of the organization (Barends & Rousseau,2018). Therefore, it is essential to explore the significance of EBMgt, indicators of credible evidence, the elements necessary to establish a cause-and-effect relationship between variables, the role of concomitant variation in determining causality, and the importance of statistics in establishing credibility. Why Evidence-Based Management (EBMgt)? Evidence-based management is essential for effective decision-making in organizations. It involves systematically analyzing and synthesizing data to comprehend the potential consequences of actions and anticipate future challenges and opportunities (Russo & Schoemaker, 1990). EBMgt enables managers to base their decisions on factual evidence rather than relying on emotions or biases. It fosters a data-driven approach that ensures better and more efficient decision-making processes, leading to improved organizational outcomes. Indicators of Credibility in Evidence: When evaluating the credibility of evidence in EBMgt, it is essential to consider the source and its intentions. Objectivity is a fundamental aspect of credible evidence. Understanding the scientific processes undertaken to obtain the evidence, along with replicability in experimental settings, reinforces the consistency and legitimacy of the findings (Susan ,2020).

3 Reputable sources with reliable methodologies and unbiased research contribute to the credibility of evidence in EBMgt. Establishing Cause-and-Effect Relationships: To conclude that one variable influences another, four elements must be present. Firstly, the variables should have a correlation or relationship with each other. This correlation provides a foundation for further research and investigation (Tesfaye,2018). Secondly, evidence should logically connect the variables, expressing a temporal relationship that establishes cause and effect. Thirdly, any confounding factors that could introduce alternative explanations should be eliminated or controlled for. Finally, a coherent relationship between all variables must be developed, excluding irrelevant factors that are not deemed relevant to the research. The Role of Concomitant Variation in Establishing Cause-and-Effect: Concomitant variation plays a vital role in establishing cause-and-effect relationships between variables (Feroze & Vinay,2019). It involves observing and studying the relationship between changes in variables. By evaluating and analyzing concomitant variations, researchers can connect potential relationships based on educated estimates of cause and effect. This serves as a starting point for establishing associations between different facts based on evidence. Successful relationships between variables provide a basis for further exploration and the application of additional research methods. The Role of Statistics in Establishing Credibility: Statistics are instrumental in determining the validity and credibility of research findings. By employing a data-driven approach, statistics enhance evidence by providing factual support. Statistical analysis helps evaluate the relationships and probabilities of evidence, enabling decision-makers to make informed choices for the organization. It reduces reliance on personal

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4 or professional biases and ensures that decisions are based on objective evaluation (Sirisilla,2022). Statistics contribute to the overall credibility of research by providing a robust and verifiable evaluation of data. Conclusion: Evidence-based management plays a crucial role in organizational decision-making, allowing managers to make informed choices based on factual evidence rather than personal biases. Indicators of credible evidence involve considering the source, its intentions, and the replicability of the research. Establishing cause-and-effect relationships requires correlational analysis, logical connections, the elimination of confounding factors, and the development of coherent relationships. Concomitant variation aids in determining causal relationships, while statistics provide a data-driven approach to enhance credibility and make informed decisions. By embracing evidence-based management and incorporating statistical analysis, organizations can improve their decision-making processes and achieve sustainable success.

5 References: Russo, J. E., & H., S. P. J. (1990). Decision traps: Ten barriers to brilliant decision-making and how to overcome them . Simon & Schuster. Barends, E., & Rousseau, D. M. (2018). Evidence-based management: How to use evidence to make better organizational decisions. Kogan Page. Susan Heathfield. (2020, March 17). Evidence-based decision making (EBDM). The Balance. https://www.thebalancemoney.com/evidence-based-decision-making-4799980 Tesfaye Boru.(2018); Research Methodology; University of South Africa, PHD Thesis. ResearchGate | Find and share research. https://www.researchgate.net/publication/329715052_CHAPTER_FIVE_RESEARCH_DE SIGN_AND_METHODOLOGY_51_Introduction_Citation_Lelissa_TB_2018_Research_ Methodology_University_of_South_Africa_PHD_Thesis Feroze Kaliyadan, & Vinay Kulkarni. (2019, January). Types of variables, descriptive statistics, and sample size. PubMed Central (PMC). https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6362742/ Sirisilla, S. (2022, October 6). Role of statistics in research – Methods & tools for data analysis. Enago Academy. https://www.enago.com/academy/statistics-in-research-data-analysis/

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