Statistical methods with financial applications, Advanced Statistics

Assignment Help:

The marketing manager of Handy Foods Ltd. is concerned with the sales appeal of one of the company's present label for one of its products. Market research indicates that supermarket consumers ?nd little appeal in the drab, somewhat cluttered appearance of the label. The company hired a design artist who produced some prototype labels, one of which was chosen consistently as best by the marketing executives. Nevertheless, the marketing executive is still in some doubt as to whether the new label would appreciably bene?t sales. He decides to make further enquiries about the consequences of a decision to switch to a new label. The decision to change to a new label is denoted by D1 and to keep the old by D2.

First he considers the costs associated with converting his company's machinery, inventory, point of purchase displays, etc., to the new label, and estimates that an out-of-pocket, once and for all cost of £250,000 would be involved. If the new label were really superior to the old, the marketing executive estimates that the present value of all net cash ?ows over and above this cost related to increased sales generated over the next three years by the more attractive label will be £400,000. Based on his prior experience and the discussion held with his colleagues, he is only willing to assign a 0.5 probability to the outcome 'new label superior to old', denoted B1. Let B2 denote the event that 'new label is not superior to the old'. Rather than make his decision on these data alone, however, he could delay it and obtain further market research information. The survey is such that it is 'perfect' at a cost of £150,000. The information from the market research survey is shown as either positive (R) or negative (  R) in favour of the new label. Draw a decision tree and decide whether it is worth carrying out market research.


Related Discussions:- Statistical methods with financial applications

Describe multiple imputation, Multiple imputation : The Monte Carlo techniq...

Multiple imputation : The Monte Carlo technique in which missing values in the data set are replaced by m> 1 simulated versions, where m is usually small (say 3-10). Each of simula

Design matrix, It is used generally for the matrix which specifies a statis...

It is used generally for the matrix which specifies a statistical model for a set of observations. For instance, in a one-way design with the three observations in one group, tw

Observational study, Observational study   is the study in which the object...

Observational study   is the study in which the objective is to discover cause-and-effect relationships but in which it is not feasible to use the controlled experimentation, in th

Disclosure risk, The risk of being able to recognize the respondent's confi...

The risk of being able to recognize the respondent's confidential information in the data set. Number of approaches has been proposed to measure the disclosure risk some of which c

Window estimates, Window estimates is a term which occurs in the context o...

Window estimates is a term which occurs in the context of the both frequency domain and time domain estimation for the time series. In the previous it generally applies to weights

Define model, Model is the description of the supposed structure of a set ...

Model is the description of the supposed structure of a set of observations which can range from a fairly imprecise verbal account to, more commonly, a formalized mathematical exp

Linear Programming, 1. The production manager of Koulder Refrigerators must...

1. The production manager of Koulder Refrigerators must decide how many refrigerators to produce in each of the next four months to meet demand at the lowest overall cost. There i

Regression, regression line drawn as Y=C+1075x, when x was 2, and y was 239...

regression line drawn as Y=C+1075x, when x was 2, and y was 239, given that y intercept was 11. calculate the residual

Clustering, hello I have a dataset including both categorical & numerical v...

hello I have a dataset including both categorical & numerical variable for market segmentation.how can i cluster them via k-means in matlab? thank you

Write Your Message!

Captcha
Free Assignment Quote

Assured A++ Grade

Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!

All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd