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Saint Leo University American Drug Store and Health Insurance Discussion Paper

Saint Leo University American Drug Store and Health Insurance Discussion Paper


Part 1(a)

Problem 2.) Gobblecakes is a bakery that specializes in cupcakes. The annual fixed cost to make cupcakes is $18,000. The variable cost including ingredients and labor to make a cupcake is $0.90. The bakery sells cupcakes for $3.20 apiece.

  1. If the bakery sells 12,000 cupcakes annually, determine the total cost, total revenue, and profit.
  2. How many cupcakes will the bakery need to sell to break even?

Problem 4.) Evergreen Fertilizer Company produces fertilizer. The company’s fixed monthly cost is $25,000, and its variable cost per pound of fertilizer is $0.15. Evergreen sells the fertilizer for $0.40 per pound. Determine the monthly break-even volume for the company.

Part 1(b)

Problem 10.) A large research hospital has accumulated statistical data on its patients for an extended period. Researchers have determined that patients who are smokers have an 18% change of contracting a serious illness such as heart disease, cancer, or emphysema, whereas there is only a .06 probability that a nonsmoker will contract a serious illness. From hospital records, the researchers know that 23% of all hospital patients are smokes, whereas 77% are nonsmokers. For planning purposes, the hospital physician staff would like to know the probability that a given patient is a smoker if the patient has a serious illness.

Problem 12.) The Senate consists of 100 senators, of whom 34 are Republicans and 66 are Democrats. A bill to increase defense appropriations is before the Senate. Thirty- five percent of the Democrats and 70% of the Republicans favor the bill. The bill needs a simple majority to pass. Using a probability tree, determine the probability that the bill will pass.

Problem 14.) A metropolitan school system consists of three—north, south, and central. The north district contains 25% of all students, the south district contains 40%, and the central district contains 35%. A minimum-competency test was given to all students; 10% of the north district students failed, 15% of the south district students failed, and 5% of the central district students failed.

  1. Develop a probability tree showing all marginal, conditional, and joint probabilities.
  2. Develop a joint probability table.
  3. What is the probability that a student selected at random failed the test?

Part 2(a) Should be between 250-500 words. Use 2 in text citations that are based in the United States and are websites. This is a discussion response.

Management science is a discipline that represents a scientific, logical, and systematic way of approaching and solving business problems. Management science uses mathematically developed techniques to resolve business issues. Those mathematical techniques can either be developed by management science discipline or can be taken from a variety of other scientific disciplines such as mathematics, statistics, physics or engineering (Taylor, 2019). Management science follows a five-step process of solving business issues: observation of the problem, detailed definition, construction of the model (often in the form of mathematical relationships) to solve the problem, solution of the model, and, finally, implementation. For example, a company that manufactures deck chairs and that has been experiencing profit losses over the last few months can use management science to get rid of inefficiencies prohibiting value growth. Following a five-step approach in tackling issues in management science, the problem needs to be first observed, and specifics of the problem and possible reasons described. If potential reasons for a loss are related to high costs, then one should look at a break-even analysis to see what the minimum price and volume should be to avoid future losses (Taylor, 2019; Williams et al., 2021).

Although business analytics can sometimes be referred to as management science (Taylor, 2019), its definition is broader. Business analytics tends to represent large amounts of data (so-called “big data”) and spans different disciplines such as information technology, computer science, statistics, mathematical modeling, operations, engineering, data science, etc. in addition to management science. Some examples of using business analytics include FMCG brands. Brands can use analytics to better understand their potential customers, convert existing customers into a loyal base and measure their brand share. For instance, those brands can use shoppers’ purchase data such as Nielsen IQ shopper scan, together with demographic and psychographic data to better understand their consumer base and create shopper segmentation (Nielsen IQ, 2022).

Data science is an interdisciplinary field that involves statistics, data analysis, data visualization, science, artificial intelligence, machine learning, and deep learning among other scientific methods. Data science collects data from different sources such as web data, as well as images and videos, cellular data, and shopper habits, and cleans this data to understand it and make it usable (Saha, 2022). Unlike business analytics data science uses coding to explore, clean, and analyze data (IMB Cloud Education, 2022) and can be used to solve a wide array of problems such as medical and scientific, whereas business analytics is used primarily for business solutions. Whereas data science calls for proficiency in linear algebra, algorithms, statistics, and programming, business analytics involve business planning, business operations optimization, predictive modeling, and storytelling (Saha, 2022). Some examples of using data science are in healthcare. For instance, Google developed a tool called LYNA (Lymph Node Assistant) to identify breast cancer tumors that metastasize to nearby lymph nodes. Noticing those tumors can be difficult for the human eye to see, especially when the new cancer growth is small. Google’s tool LYNA can identify metastatic cancer 99 percent of the time using its machine-learning algorithm (Rice, 2022). Another example can be in the service industry. For example, UBER Eats uses machine learning, and statistical modeling to optimize the full delivery process and understand how weather conditions (e.g. storms), and holiday rush traffic impacts to traffic and cooking time (Rice, 2022). Finally, UPS uses data science to optimize its package transport from drop-off to delivery: it uses the navigation system called ORION which helps drivers choose over 66,000 fuel-efficient routes. ORION has saved UPS approximately 100 million miles and 10 million gallons of fuel per year with the use of advanced algorithms, AI, and machine learning (Rice, 2022).


IBM Cloud Education. (2022). Data Science.…

Nielsen IQ. (2022). Consumer Analytics.…

Rice, Mae. (2022). 22 Data Science Applications and Examples. Builtin.…

Taylor, Bernard. (2019). Introduction to Management Science. (13th ed.). Pearson.

Suraj, Saha. (2022). Data Science vs Business Analytics – Top 5 Differences. Knowledge Hut.…

Williams, J., Bettner, M., Carcello, J. (2021). Financial & Managerial Accounting. (19th ed.).

McGraw Hill Education.

Part 2(b) Should be between 250-500 words. Use 2 in text citations that are based in the United States and are websites. This is a discussion response.

Management science is a comprehensive, multidisciplinary study of organizational decision-making and problem-solving. The applications of management science techniques are widespread, and they get frequently credited with increasing the efficiency and productivity of business firms (Taylor III, 2019). The management science method improves an organization’s capacity to make reasonable and meaningful management choices.

Analytics and management science have very similar problem-solving approaches. Indeed, many businesspeople believe that business analytics is simply a repackaged form of management science (Taylor III, 2019). The primary distinction between the two is that Business Analytics focuses on firm-related issues such as cost and profit. In contrast, Data Science addresses concerns such as the impact of location, seasonal influences, and consumer preferences on the business. In summary, Data Science is the greater of the two.


Data science Data science is the process of preparing data for analysis, which includes cleaning, aggregating, and modifying data to undertake sophisticated data analysis. Analytic apps and data scientists may then evaluate the results to discover trends and provide educated insights to

corporate executives. Such data includes illness detection and prediction, real-time shipping and logistics route optimization, fraud detection, healthcare advice, digital ad automation, etc. Data Science benefits these industries in a variety of ways.

Management Science An example is innovative web-based capabilities that reimagined clients’ ways of listening to music and viewing movies (e.g., Apple Music or Hulu). Another option is collaborative efforts, which grant access to products and administrations without requiring legal ownership (e.g., Lyft or Airbnb). Significant issues are also evident within organizations, as digital improvements alter how things get manufactured and representatives perform and collaborate. Finally, firms must evolve and react to these actual developing variables to remain aware of the turn of events and fruitful.

Business analytics Online meal ordering firms desire fresh insights that might help them increase efficiency and improve their business processes. For example, these businesses use a dashboard to provide real-time access to their customers’ life cycles. The data collected pertains to typical wait time, delivery experience, meal flavor, menu availability, loyalty card points, and product inventory levels (ProjectPro, 2022). This generated data that aided in simplifying sales operations and marketing efforts, accomplishing the objective of increasing productivity.

Mejia, P. (2019, July 22). The Success Of Streaming Has Been Great For Some, But Is There A Better Way? NPR.…

ProjectPro. (2022, July 20). How Food Delivery Apps are leveraging Big Data Analytics?…

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