1..Explain the criteria of minimising expected cost, and apply it to this problem. Calculate the expected cost with and without the revision course.

2.Note that 'equally likely' implies a probability of 0.5 to each, so that the expected failure rate after the course is (0.05 X 0.5) + (0.10 X 0.5) = 0.075.

2.Then calculate the likelihood of two fails in a sample of 10 using the Binomial distribution and combine with the prior probabilities using Bayes Theorem to find posterior probabilities.

4.Use these posterior probabilities to determine whether the course should run, using expected cost or opportunity loss as the decision criteria.

5. List the assumptions made to answer the question, and assess their relevance in these circumstances.

6. Examine the methods available for demand estimation, comparing and contrasting the explanatory and extrapolatory approaches.

7.Discuss the decision about resources to be devoted to demand estimation, primarily determined by the use to which forecasts are to be put.

8.Explain what is meant by forecast reliability, and how this can be estimated prior to forecast use.

9.. Explain what is meant by a new product, carefully defining the concept of 'newness', and examine the cost and demand estimation problems surrounding new product pricing.

10.Analyse the importance of the competitive environment, and explain the factors determining whether a 'skimming' or 'penetration' policy should be used, using the example given in the question, and its implicit emphasis on the importance of entry conditions.

11. Examine the role and consequences of advertising, contrasting the market expansion and redistributional implications of advertising. Outline the model of advertising as information, and consider the circumstances in which advertising information reduces the cost of search to the consumer.