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

 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?

Due Day 7

Reply and or respond to at least 2 of your classmates or your faculty member, and/or address the following subjects:

  1. Explain what we mean when we identify “cause and effect”.
  2. How are percentages an important part of determining probability?
  3. Why do we use “degrees of freedom?”
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The Excel function =RANDBETWEEN(a,b) generates a random integer value between a and b

The Excel function =RANDBETWEEN(a,b) generates a random integer value between a and b. Open Excel. Copy and paste the Excel function into 30 cells (rows) starting at Column A at A1. Create 30 random values between 0 and 7 to simulate the response to the question, “How many times have you dined out in the past week?”  Note: Once you have your 30 random values in Column A, select all values, copy the values, and use “Paste Special – Values” to Column B starting at B1. This will keep the spreadsheet from recalculating and changing your results.

Use Excel’s Data Analysis Tool Add-in to generate the Descriptive Statistics Summary Table for the values in Column B (as demonstrated in Section 3.2 of the text). Also use Excel’s Chart tools (as discussed in Section 3.4 of the text) to generate a box plot on the 30 responses. Comment on the measures and shape of the distribution. Do the measures and shape represent what you would expect based on randomly determined values? Why or why not?  Include the data set of the 30 random values and your output in your response. Provide references (Refer to Chapter 3 Review: Supplementary Exercises 62 in the Chapter 3 topic Resources in Essentials of Modern Business Statistics With Microsoft Office Excel in MindTap).

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