Q1) Draw a decision tree for this problem. Your tree should include probabilities associated with chance nodes and payoffs associated with terminal nodes. : Please refer to the following decision tree. ( “Net cash flow = income PV-launching cost- trial cost”)

[Exhibit1]

Q2) Fold back the tree. Assuming Merck is risk neutral, should it license Davanrik? : Yes, Merck should do, since Merck is expected to earn $13.98M by licensing Davanrik.

Q3) For what range of values of “probability of success of Phase 1” would your answer to Question 2 remain the same? : To keep the decision in Q2 the same, the probability of success of Phase I should be not less than 40.93%. The calculation is as below. Assuming that the probabilities of Phase II and III are the same, the expected value of licensing can be calculated as below. If x is probability of success of Phase I, Expected value = 43.3x -30(1-x) If 43.3x -30(1-x) =0, x = 0.4093. 40.93%

Q4) How would your answer to Question 2 change if the costs of launching Davanrik for weight loss were $225 million instead of $100 million as given in the case? : Merck should license Davanrik, since its expected earning is still positive. (Please refer to the following exhibit 2.)

[Exhibit 2]

Q5) How much would Merck be willing to pay to guarantee that Phase I of the FDA approval process is successful? : If Merck can guarantee that the Phase 1 of the FDA approval process is successful, the expected value of licensing increases to $43.3M, while the current expected value is $13.98M, as you can see in Exhibit 1. In this manner, Merck would like to pay up to $29.32M(43.3M-13.98M) to guarantee.

...Trajico, Maria Liticia D.
BSEd III-A2
REFLECTION
The first thing that puffs in my mind when I heard the word STATISTIC is that it was a very hard subject because it is another branch of mathematics that will make my head or brain bleed of thinking of how I will handle it. I have learned that statistic is a branch of mathematics concerned with the study of information that is expressed in numbers, for example information about the number of times something happens. As I examined on what the statement says, the phrase “number of times something happens” really caught my attention because my subconscious says “here we go again the non-stop solving, analyzing of problems” and I was right. This course of basic statistic has provided me with the analytical skills to crunch numerical data and to make inference from it. At first I thought that I will be alright all along with this subject but it seems that just some part of it maybe it is because I don’t pay much of my attention to it but I have learned many things. I have learned my lesson.
During our every session in this subject before having our midterm examination I really had hard and bad times in coping up with this subject. When we have our very first quiz I thought that I would fail it but it did not happen but after that, my next quizzes I have taken I failed. I was always feeling down when in every quiz I failed because even though I don’t like this...

...Baur Bektemirov
BUSF 36106: Assignment 5
Freemark Abbey Winery
Assume that under no unusual circumstances (no storm), Jaeger sells 1,000 cases of Riesling. Consider diﬀerent cases: 1. Jaeger harvests grapes in anticipations of storm. Then the total revenue will be equal to 12×1000×$2.85 = $34200. 2. Jaeger doesn’t harvest and there is no storm with 50% chance. 2.1. With 40% chance, sugar concentration is 25%, then the total revenue is 12 × 1000 × $3.50 = $42000 2.2. With 40% chance, sugar concentration is 20%, then the total revenue is 12 × 1000 × $3.00 = $36000 2.3. With 20% chance, sugar concentration is below 20%, then the total revenue is 12 × 1000 × $2.50 = $30000 3. There is storm with 50% chance 3.1. Storm causes botrytis mold with probability 40%, then the price will increase but the total quantity produced will decrease by 30%. The total revenue is equal to 12 × 1000 × 70% × $8.00 = $67200. 3.2. With 60% chance, storm results in swelling of the berries and the price for a bottle goes down, though the total production output increases by 7.5%. The total revenue is 12 × 1000 × 107.5% × $2.00 = $25800. We can calculate the expected outcome based on conditional probabilities of each case or we can build a decision tree with a “decision” node at the beginning and “chance” nodes on the branch corresponding to the decision of not harvesting. The optimal decision for Jaeger is not to harvest; the expected...

...The Valley Winery is one of the nations largest privately help companies, and the top domestic producer of wine selling more than 40 percent of all wine produced in the United States. Valleys success is largely due to their high quality wine sold for a lower price, and a very aggressive and innovative sales force. Sales groups are separated into three main categories:
1) Liquor stores and bars
2) Restaurants, resorts, hotels, and motels
3) Chain Division
The company has experienced many sales organization changes in their San Francisco chain division; recently focusing on the importance of key customers classified as major accounts. Pat Waller was hired as sales manager of the San Francisco region’s branch, where he manages two are managers. The two area manages are responsible for nine district mangers, who supervise five to six sales reps each. Each sales rep is responsible for a certain number of stores from all major grocery chains, caring to all their merchandising, service, and miscellaneous needs related to Valley Winery. Although the company has had favorable sales results in the San Francisco Region in recent years, Waller recognizes problems within the company and is concerned that the company will have difficulty in maintain their current status with the rapid increase of competition within the wine industry.
Key problems in the management of Valley Winery consist of but not limited to:
• No experienced sales reps...

...-------------------------------------------------
The Valley Winery
-------------------------------------------------
Case Analysis
By: Paul Welge
Dr. Bob McDonald
MKT 4359
Section 1
Valley Winery was founded in 1933 after the prohibition and has grown to be the largest domestic producer of wine in the United States. The brand has multiple product lines that include both low-price, consistent-quality wines and also low-grade wines and wine coolers. The company has had a hard time retaining its sales force and despite the short-term increase in sales, it is not a sustainable growth.
The company has struggled to retain its sales force and has a nearly 100% turnover. There are 50 sales representatives in the San Francisco but approximately 50 new sales representatives are hired each year. The average time a sales representative is with the company is seven months. Valley Winery recruits 10 to 15 new sales reps from area universities, 10 hires from local newspaper advertisements and online job postings, and 15 to 20 representatives are hired through the use of six local employment agencies. The employees hired through the employment agencies cost the Winery approximately $3,000 per individual. It is also figured that recruiting and training each representative cost the company $30,000 per year. Pat Waller, the sales manager for the San Francisco region’s chain division, figures that...

...Case One:
Valley Winery
Valley Winery, a favorable wine company, hired Pat Waller as their sales manager of the San Francisco region’s chain division. Although the company has had increasing sales for the past several years, Valley Winery has its fair share of problems that have Waller worried. He is very aware of the competitiveness within the wine industry and is concerned that Valley Winery will not be able to continue consistently increasing their sales.
Turnover rate is the number one issue at Valley Winery. Every problem the company has bleeds into the turnover rate. The company’s turnover rate is currently at almost 100 percent a year; this is a huge issue that Waller must address. The existing sales rep employment average is seven months. There are many things that could be causing this problem. Often, sales reps are leaving the company quickly because they can’t meet their quotas. Hiring issues, which will be addressed later, are another contributing cause of the high turnover rate.
Sales reps’ aggressive attitudes are another issue that Waller will have to address. The Valley Winery as a whole is receiving negative feedback. Sales reps are not “playing fair” when it comes to competition. They have been known to tamper with competitors’ merchandise, misrepresent displays, and exaggerate their quotas. The root of these aggressive behaviors lies in the...

...techniques.
Firstly we look at data analysis. This approach starts with data that are manipulated or processed
into information that is valuable to decision making. The processing and manipulation of raw
data into meaningful information are the heart of data analysis. Data analysis includes data
description, data inference, the search for relationships in data and dealing with uncertainty
which in turn includes measuring uncertainty and modelling uncertainty explicitly.
In addition to data analysis, other decision making techniques are discussed. These techniques
include decision analysis, project scheduling and network models.
Chapter 1 illustrates a number of ways to summarise the information in data sets, also known as
descriptive statistics. It includes graphical and tabular summaries, as well as summary measures
such as means, medians and standard deviations.
Uncertainty is a key aspect of most business problems. To deal with uncertainty, we need a basic
understanding of probability. Chapter 2 covers basic rules of probability and in Chapter 3 we
discuss the important concept of probability distributions in some generality.
In Chapter 4 we discuss statistical inference (estimation), where the basic problem is to estimate
one or more characteristics of a population. Since it is too expensive to obtain the population
information, we instead select a sample from the population and then use the information in the
sample to infer the...

...The Valley Winery-Case 1.1
Is the management of Valley Winery doing an acceptable job of hiring and training qualified employees?
Management is the foundation of a company. They are the ones that make decisions which could make or break a company. They personify how the company and employees should act. If one is driven towards perfection in sales, many other important areas of the business could be overlooked. For example, maintenance of long term relationships with buyers would be overlooked. If management is pushing the sales reps to just go after the sale at any cost, reps could be looked at as unethical and even too pushy. Valley Winery management encourages reps to lie about how many cases of wine are sold to buyers. This is unethical and puffery. Pushing these sales reps to call their ethics into question, what does that say about management?
Pat Waller, employee of Valley Winery, was recently promoted to sales manager of the San Francisco region's chain division. When he arrived, he was shocked to find that such a successful division had such a horrible turnover rate. How was the San Francisco division of Valley Winery obtaining their sales goals? He began to investigate and found many problems that were mainly stemming from management. The hiring process of Valley Winery needs to be revised. Mike Wehner, personnel manager for the...

...3
Question 2a 5
Question 2b 6
Question 2c 7
Question 3a 8
Question 3b 8
Question 3c 10
Question 3d 11
Question 4 12
Question 5 14
References 15
Question 1
The sampling method that Mr. Kwok is using is Stratified Random Sampling Method. In this case study, Mr Kwok collected a random sample of 1000 flights and proportions of three routes in the sample. He divides them into different sub-groups such as satisfaction, refreshments and departure time and then selects proportionally to highlight specific subgroup within the population. The reasons why Mr Kwok used this sampling method are that the cost per observation in the survey may be reduced and it also enables to increase the accuracy at a given cost.
TABLE 1: Data Summaries of Three Routes
Route 1
Route 2
Route 3
Normal(88.532,5.07943)
Normal(97.1033,5.04488)
Normal(107.15,5.15367)
Summary Statistics
Mean
88.532
Std Dev
5.0794269
Std Err Mean
0.2271589
Upper 95% Mean
88.978306
Lower 95% Mean
88.085694
N
500
Sum
44266
Summary Statistics
Mean
97.103333
Std Dev
5.0448811
Std Err Mean
0.2912663
Upper 95% Mean
97.676525
Lower 95% Mean
96.530142
N
300
Sum
29131
Summary Statistics
Mean
107.15
Std Dev
5.1536687
Std Err Mean
0.3644194
Upper 95% Mean
107.86862
Lower 95% Mean
106.43138
N
200
Sum...

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