BUS-ES 102 Intro to Business Modeling Assignment #1 Due: Sunday, October 27th, 2024, by 11:59 PM EST Instructions:  This assignment aims to deepen your understanding of the concepts covered in

BUS-ES 102 Intro to Business Modeling

Assignment #1

Due: Sunday, October 27th, 2024, by 11:59 PM EST

Instructions:  This assignment aims to deepen your understanding of the concepts covered in Chapters 2-8 of the textbook. You must answer all 15 questions completely. Each answer should demonstrate your comprehension of the material and include relevant examples or applications where applicable

1.     The number of children living in each of a large number of randomly selected households is an example of which data type? Be specific.

2.     Explain why the standard deviation would likely not be a reliable measure of variability for a distribution of data that includes at least one extreme outlier.

3.     When you are trying to discover if there is a relationship between two categorical variables, why is it useful to transform the counts in a crosstabs to percentages of row or column totals? Once you do this, how can you tell if the variables are related?

4.     In checking whether several times series, such as monthly exchange rates of various currencies, move together, why do most analysts look at correlations between their differences rather than correlations between the original series?

5.     Can you see data in a Data Model if Power Pivot is not loaded? Can you use data in an Excel Data Model in a pivot table if Power Pivot is not loaded?

6.     List the advantages of a Dates table in a Data Model, assuming that there is already a Date column in the facts table.

7.     In terms of the material in this chapter and the previous chapter, what is common between Excel and Power BI Desktop? What is different?

8.     What is the role of row context when defining a DAX calculated column?

9.     Suppose officials in the federal government are trying to determine the likelihood of a major smallpox epidemic in the United States within the next 12 months. Is this an example of an objective probability or a subjective probability? How might the officials assess this probability?

10.  For each of the following uncertain quantities, discuss whether it is reasonable to assume that the probability distribution of the quantity is normal. If the answer isn’t obvious, discuss how you could discover whether a normal distribution is reasonable.

a.      The change in the Dow Jones Industrial Average between now and a year from now

b.     The length of time (in hours) a battery that is in continuous use lasts

c.      The time between two successive arrivals to a bank

d.     The time it takes a bank teller to service a random customer

e.      The length (in yards) of a typical drive on a par 5 by Phil Michelson

f.      The amount of snowfall (in inches) in a typical winter in Minneapolis

g.     The average height (in inches) of all boys in a randomly selected seventh-grade middle school class

h.     Your bonus from finishing a project, where your bonus is $1000 per day under the deadline if the project is completed before the deadline, your bonus is $500 if the project is completed right on the deadline, and your bonus is $0 if the project is completed after the deadline

i.       Your gain on a call option on a stock, where you gain nothing if the price of the stock a month from now is less than or equal to $50 and you gain (P – 50) dollars if the price P a month from now is greater than $50

11.  In a classic oil-drilling example, you are trying to decide whether to drill for oil on a field that might or might not contain any oil. Before making this decision, you have the option of hiring a geologist to perform some seismic tests and then predict whether there is any oil or not. You assess that if there is actually oil, the geologist will predict there is oil with probability 0.85. You also assess that if there is no oil, the geologist will predict there is no oil with probability 0.90. Why will these two probabilities not appear on the decision tree? Which probabilities will be on the decision tree?

12.  Insurance companies wouldn’t exist unless customers were willing to pay the price of the insurance and the insurance companies were making a profit. So explain how insurance is a win-win proposition for customers and the company.

13.  When pollsters take a random sample of about 1000 people to estimate the mean of some quantity over a population of millions of people, how is it possible for them to estimate the accuracy of the sample mean?

14.  Explain as precisely as possible what the central limit theorem says about averages.

15.  Suppose you wish to test a manager’s claim that the proportion of defective items generated by a particular production process has decreased from its long run historical value of 0.30. To carry out this test, you obtain a random sample of 300 items produced through this process. The test indicates a p-value of 0.01. What exactly is this p-value telling you? At what levels of significance can you reject the null hypothesis?