ToyFun is one of the two most popular manufacturing companies producing and selling a wide range of fun products for kids of all ages. One of its products is Big Hunting, which is a hunting game designed for kids of 6-10 years old. Over the last ten years, it has emerged as the most frequently purchased game by parents of kids in that age group. In recent time an alternative fun game, Star Wars, produced by it is main competitor, Toys and Games, have taken away a small part of the market share for Big Hunting. However, ToyFun still makes a substantial profit from Big Hunting, as it is still the most popular game among that age group.

At this point, the executive team of ToyFun is trying to decide if raising or lowering the price of Big Hunting will be a good idea to increase its profit, or should they consider other strategic options. ToyFun has hired your consulting firm, Information and Data Analytics (IDA), to work on this project. Your group is one of a few groups at IDA, each focused on a specific area of study. Your group has been assigned the project of ToyFun.

When your group meets with Martin Smith, the CEO of ToyFun, he explains to you the status of ToyFun in the current market, and mentions that he is specifically trying to find answers to the following questions.

1.) Should the price of Big Hunting be greater or smaller than the current price, $29.19?

2.) Does the firm's advertising expenditure have a good impact on its sales volume? Will increasing it help make larger profit on Big Hunting?

3.) What other factors, such as people's income, population size, or the price of Star Wars may be significantly impacting the sale of the product?

Martin asks your group to summarize your findings in a brief report without much technical detail. That way it will be easier to communicate your findings to other executive members of ToyFun who are not necessarily trained in the areas of economics and statistics. He also recommends that your report will preferably have several sections under appropriate self-explanatory headings, each of which will address one issue at a time, although any one section may be related to the others. Martin also asks your group to put all your technical notes in a short appendix as a reference for others who may have both the interest and the ability to review your analysis. He also advises your group to clearly mention any limitation your analysis and results might have. Martin says that you have only one week to complete the analysis and write the report.

Martin also mentions that ToyFun's resident expert, Bob Harper, has done some preliminary work. He has collected data on the variables he thinks are important to find answers to the questions. He advises conducting your analysis based on Bob's spreadsheet.

Martin hands your group a copy of the spreadsheet that Bob left before going on a leave. The spreadsheet contains data on the variables that Bob thinks are important. It also contains some notes on the data.

The next day you meet with Marilyn Heath, the Director of your group at IDA, and explain the whole project in detail. You also show her Bob's spreadsheet. She advises you of the following.

i) The entire analysis has to be done based on the estimation of two types of demand functions: i) linear; and ii) log-linear.

ii) Compare the results from the two estimations and check whether or not both sets of results lead to the same conclusions.

iii) With the production process already set up, the marginal cost over a large output range is virtually zero.

iv) Need to compute the appropriate elasticities.