Resources Use Any Of The Following Capella Library Articles

Resourcesuse Any Of The Following Capella Library Articles For This Un

Resources use any of the following Capella library articles for this unit's assessment or find appropriate articles on your own: · Anders, G. (2017). The looming retail bailout. Forbes, 199(6), 94–99. · Badenhausen, K. (2016). The world's highest-paid athletes. Forbes, 197(9), 22. · Cam, D., & Au-Yeung, A. (2017). Doctorate, degree or dropout? Forbes, 200(5), 24. · Canal, E., Kauflin, J., & Adams, S. (2016). Shark Tank's toothless deals. Forbes, 198(7), 24–25. · Decarlo, S., Elam, D. G., Smyth, K., Agus, S., Austin, C., Hackett, R., ... Wieczner, J. (2017). 100 Fastest-Growing companies. Fortune, 176(4), 157–163. · Growing, growing... gone! (2016). Forbes, 197(5), 28. · Lim, P. J. (2018). The 50 best mutual funds and 50 best ETFs. Money, 47(1), 86–91. · Meet the world's richest. (2016). Forbes, 197(4), 26–27. · Salisbury, I. (2018). How we got here. Money, 47(1), 52–57. · Sorvino, C. (2016). Dollar days. Forbes, 197(4), 28. There are select chapters from the following text throughout this course that are useful for preparation for each assessment: · Lind, D. A., Marchal, W. G., & Wathen, S. A. (2019). Basic statistics for business and economics (9th ed.). New York, NY: McGraw-Hill. · Chapter 1, "What Is Statistics?" This chapter explains why studying analytics and statistics is essential in business today. If this is your first venture into the world of analytics, the following resources can provide a solid foundation of knowledge: · Kenny, P. (2014). Better business decisions from data: Statistical analysis for professional success. New York, NY: Apress. · Chapter 5, “Raw Data.” This resource presents an overview of how data are used to make business decisions in the professional context. · Thomas, R., & McSharry, P. (2015). Big data revolution: What farmers, doctors, and insurance agents can teach us about patterns in big data. West Sussex, England: Wiley. Chapters 1–9. These chapters give practical examples of the use of analytics. · Watson, H. J. (2018). Successful analytics leaders. Business Intelligence Journal, 23(1), 5–11. This reading covers key characteristics of how leaders use analytics in business effectively.

Paper For Above instruction

In the contemporary business landscape, analytics and statistical analysis are integral to making informed decisions and gaining competitive advantage. The resources provided from the Capella Library, as well as supplementary scholarly texts, serve as foundational tools to understand the significance and application of data-driven strategies in various industries.

Gina Anders' article, "The Looming Retail Bailout," illustrates how retailers face financial distress, emphasizing the necessity of employing advanced statistical models to predict future cash flows and identify failing stores early (Anders, 2017). Retail companies utilize data analytics to optimize inventory, improve customer experiences, and refine marketing strategies, which are crucial for survival amid economic challenges. The ability to interpret sales data, customer preferences, and macroeconomic indicators can enable retailers to strategize effectively and avoid bankruptcy.

Similarly, the article by Badenhausen (2016) on "The World's Highest-Paid Athletes" employs statistical tools to analyze earnings, endorsements, and popularity metrics, demonstrating how quantitative analysis can enhance brand valuation and athlete management. Quantitative analysis enables stakeholders to gauge performance metrics numerically, ultimately guiding contractual negotiations and marketing investments.

The Forbes article by Cam and Au-Yeung (2017) explores the dropout rates in professional and academic settings, highlighting the importance of statistical assessments in understanding dropout factors. By analyzing data from educational institutions, stakeholders can develop targeted intervention programs to reduce dropout rates, demonstrating the value of statistical insights in social policy and educational planning.

Decarlo et al.'s (2017) examination of the "100 Fastest-Growing Companies" demonstrates the application of growth metrics, revenue data, and market analysis through statistical models. Identifying patterns among these organizations provides insights into successful business practices and investment opportunities, illustrating the power of data analytics in recognizing emerging industry leaders.

In the investment sector, P. J. Lim's (2018) article on mutual funds and ETFs discusses performance metrics and risk assessments, emphasizing how statistical analysis informs investment decisions. Investors rely on quantitative data to construct diversified portfolios, assess risk, and optimize returns, demonstrating the application of statistics in financial management.

The foundational principles of statistics, as discussed in Lind, Marchal, and Wathen's (2019) "Basic Statistics for Business and Economics," highlight the importance of understanding data collection, summarization, and interpretation. These principles underpin the uses of analytics in practical scenarios, such as those illustrated by the articles mentioned above.

Moreover, Kenny (2014) emphasizes the significance of raw data analysis in making successful business decisions. The chapter elucidates methods for cleaning, organizing, and analyzing data, which are essential skills for any business professional seeking to leverage analytics for strategic benefits.

Thomas and McSharry's (2015) "Big Data Revolution" expands upon practical examples where patterns derived from extensive datasets inform decisions in agriculture, healthcare, and insurance. The chapters demonstrate how big data analytics reveal insights that would be otherwise unnoticed, leading to improved efficiency and innovation.

Finally, Watson (2018) discusses characteristics of successful analytics leaders, stressing the importance of leadership qualities such as vision, communication skills, and technical expertise. Effective analytics leaders foster organizational cultures that prioritize data-driven decision-making, facilitating successful application of statistical insights across business functions.

In conclusion, the integration of analytics and statistics into business practice enables organizations to make smarter, evidence-based decisions. From retail and finance to education and sports, quantitative analysis guides strategic initiatives, reduces risks, and uncovers growth opportunities. Equipped with a foundational understanding of statistical principles, as presented in the sources, future business professionals can harness the power of data to drive innovation and competitive advantage in their respective fields.

References

• Anders, G. (2017). The looming retail bailout. Forbes, 199(6), 94–99.
• Badenhausen, K. (2016). The world's highest-paid athletes. Forbes, 197(9), 22.
• Cam, D., & Au-Yeung, A. (2017). Doctorate, degree or dropout? Forbes, 200(5), 24.
• Canal, E., Kauflin, J., & Adams, S. (2016). Shark Tank's toothless deals. Forbes, 198(7), 24–25.
• Decarlo, S., Elam, D. G., Smyth, K., Agus, S., Austin, C., Hackett, R., ... Wieczner, J. (2017). 100 Fastest-Growing companies. Fortune, 176(4), 157–163.
• Lim, P. J. (2018). The 50 best mutual funds and 50 best ETFs. Money, 47(1), 86–91.
• Salisbury, I. (2018). How we got here. Money, 47(1), 52–57.
• Sorvino, C. (2016). Dollar days. Forbes, 197(4), 28.
• Lind, D. A., Marchal, W. G., & Wathen, S. A. (2019). Basic statistics for business and economics (9th ed.). McGraw-Hill.
• Kenny, P. (2014). Better business decisions from data: Statistical analysis for professional success. Apress.