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Respond to the following discussion prompt in a minimum of 175 words:

 

Many business activities generate data that can be thought of as random. An example described in the textbook is the servicing of cars at an oil change shop. Each car entering the shop can be considered an experiment with random outcomes. A variable of interest in this experiment could be the amount of time necessary to service the car. Service time will vary randomly with each car.

We can often capture the most relevant characteristics of a stochastic process with a simple probability distribution model. We can then analyze the model to make predictions and drive decisions. For instance, we could estimate the number of technicians the oil change shop needs to service demand on a Saturday afternoon. Discuss the following:

What is a random variable?
How would you differentiate a discrete from a continuous random variable?

A laptop manufacturing company has implemented a 2-step process to test the quality of each production batch. In the first step, a technician randomly selects 15 laptops from the batch and determines whether they meet specifications. The batch is considered acceptable provided no more than 1 laptop fails to meet specifications. Otherwise, the entire batch must be tested in the second step. Historical data shows that 95% of the laptops produced adhere to specifications. Discuss the following:

What are the 4 characteristics of a binomial experiment?
Can we use a binomial distribution to model this process?
What is the probability that the entire batch unnecessarily has to be tested if in fact 95% of its laptops conform to specifications? (Hint: Use Excel’s =BINOMDIST() function to find the probability.)
What is the probability that the batch is incorrectly accepted if only 75% of its laptops conform to specifications?

(1) What questions do you have about using software to compute these outcomes?

(2) What is the difference between a Market Research Product that is statistically based, and a Market research product that is not statistically based? What pieces need to be present in the statistical market value research.

(3) Explain the difference between “confidence level” and “confidence interval”.

(4) Explain the difference between descriptive statistics and inferential statistics.]

Sample Solution

Naïvety is best defined by a person with an extreme lack of judgment or experience in everyday situations. Throughout this journal, authors Amrish Patel and Edward Cartwright discuss how the beliefs of naïve and rational people affect not only their decisions and actions they chose but how they evolve as a person. Patel and Cartwright analyze how naïve viewers chose to believe in anything they are told without inquiring whether or not the statement was credible, and decide to view things only at their superficial appearance. Rational viewers, on the other hand, choose to view situations with a more realistic approach and make decisions based on reason rather than letting their emotions overcome them. Amrish Patel works in the Department of Economics at the University of Gothenburg working in both the behavioral economics and game theory fields, while Edward Cartwright works as Professor of Economics at De Montfort University. As a result of these various achievements and qualifications, these authors are very credible for this topic. The protagonist, Candide, is an extremely naïve character who is exceedingly vulnerable to the domination of the other strong-minded characters. Similar to Patel and Cartwright’s statements, naïve people allow others to influence their decisions due to their disregard for reliable sources.

Van Leeuwen, Marco H.D., and Ineke Maas. “Historical Studies of Social Mobility and
Stratification.” Annual Review of Sociology, vol. 36, 2010, pp. 429–451. JSTOR,
www.jstor.org/stable/25735086

Throughout the many eras such as the Byzantine, the Elizabethan, the Romantic, and many more, the ideas of a social hierarchy system have remained the same. However, the mobility between classes has dramatically changed through various time periods. Throughout this journal, authors Marco H.D. van Leeuwen and Ineke Maas discuss their historical research on social mobility and structure, as well as the shifts in the social imbalance in earlier years and what factors caused these outcomes. Marco H.D. van Leeuwen is an honorary research associate at the International Institute of Social History as well as a Professor of Historical Sociology in Utrecht. Ineke Maas is a Professor at the Department of Sociology at the Universiteit Amsterdam and studies trends in mobility throughout generations, in careers, as well as in marital situations. Due to their many qualifications, Leeuwen and Maas act as an exceptionally reliable source for my topic. This article connects to the Status Mobility and Reactions to Deviance and Subsequent Conformity journal by Elihu Katz, William L. Libby Jr., and Fred L. Strodtbeck because they both discuss the differences of social mobility throughout various eras.

Zollman, Kevin James Spears. “Social Structure and the Effects of Conformity.” Synthese, vol

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