Concepts and Terminology of Statistics Applied to Business Decision Making (5-6 PP slides,75 word min.per slide)title page w/references

Big data is everywhere, and various businesses around the world are driven by big data. While some businesses rely on big data for organizational decision making, this does not mean that the implications and applications of big data are properly used to ensure optimal effectiveness for the organization

For this scenario, you have been appointed as a business analyst for Big D Incorporated, charged with providing authoritative recommendations to the Board of Directors. As the business analyst, the recommendations that you provide will be based upon data calculated from statistically appropriate formulas. Be reminded that you are not the company’s statistician yet. However, as the business analyst, you are therefore responsible for interpreting statistical data and making the appropriate recommendations.

Big D Incorporated was offered a series of business opportunities, and it is your job as the business analyst to provide expert insight and justification for recommendations regarding these potential prospects.

Assignment Details

Big D Incorporated has a business opportunity to provide two different types of information to a new client. As the business analyst, you are tasked to assess the financial feasibility of this opportunity. The new client is a retailer and looking to expand its product offerings. However, the client is requesting Big D Incorporated to assist in the decision-making process.

Prepare a presentation that addresses the following:

• Explain the difference between nominal and ordinal data.
• List 3 qualitative attributes of outdoor sporting goods that the client may want to ask consumers. Make sure 1 of the qualitative attributes is nominal.
• For each ordinal attribute, assign names for the endpoints of a 5-point rating scale.
• Explain the difference between interval and ratio data.
• List 2 quantitative attributes of outdoor sporting goods that market researchers might want to measure.
• Explain the difference between a population and a sample.

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