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Business Analytics/Statistics

There are two questions to answer and each answer should be a minimum of 250 words, which is why I put 2 pages on the order. Responses should be detailed with examples, if applicable.

1) Managers in more advanced analytics companies give more weight to analytics when they make key business decisions. Employees frequently look for signals about what is important to management, and whether what is important today will be important tomorrow.
How can management help employees understand what analytics are important to monitor on a regular basis and what analytics could fluctuate as the business cycle runs its course?

2) The manager of a large manufacturing firm is considering switching to new and expensive software that promises to reduce its assembly costs. Before purchasing the software, the manager wants to conduct a hypothesis test to determine if the new software does reduce its assembly costs.
Would the manager of the manufacturing firm be more concerned about a Type I error or a Type II error? Explain.
Would the software company be more concerned about a Type I error or a Type II error? Explain.

 

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