Purpose

Provide a qualitative description of report contents/problems addressed in the report (covering Appendices 1-4) and what insights the analyses will provide.

Write this introduction after you have a clear understanding of the content of your report.

Ensure you have given specific details as to what the report will contain. Follow the length guideline (given on the previous page).

Describe in 2-3 sentences, the aim of the analysis in this section including the variable of interest to the CLO.

Interpret the chosen measures of central tendency and dispersion in non-technical terms for each of the listing types. (Appendix 1 (b))

Discuss any unusual prices per stay in each listing type. If Q!-Casa sets up a minimum and maximum price per stay for each listing type, then what would be a pricing bracket guideline? (Appendix 1 (c))

Using the analysis from Appendix 1(d), discuss whether there are any obvious similarities or differences in the typical price per stay across the three types of listings. Is there a particular listing type that they should focus on? Hint: compare the boxplots to obtain your answer.

Describe in 2-3 sentences, the aim of the analysis in this section.

Describe your linear programming solution in terms of maximum revenue for the total listings put on the website, and the optimum number of stays for each listings type, Classic, Designer and Luxury. (Appendix 2(b))

If the revenue made from Luxury listings is increased by $20 for per stay then is the solution still optimal and what is the new revenue? (Appendix 2(c))

Discuss whether all the allocated budget has been used up for cleaning costs. Based on your analysis, would it be possible to increase the budget? (Appendix 2(d))

Must the CLO's decision to sell at least twice as many Designer stays asLuxury stays be adhered to?Discuss briefly. (Appendix 2(b))

Provide a recommendation as to whether the original (Appendix 2(b)) or the amended solution (Appendix 2(e) or (f)) should be pursued.

Describe in 2-3 sentences, the aim of the analysis in this section. Include any limitations you can think of with regards to the data set (Appendix 3(a)).

Include here a scatterplot of Price per Listing ($) and Cost of Advertising ($) without the trendline, the regression equation or coefficient of determination. Ensure the axes are properly labelled and you have an appropriate title that includes your network ID (Appendix 3(b)).

Interpret the general trend of the scatterplot and explain how much on average the cost of advertising changes for each dollar increase in the price of a listing (Appendix 3(d)).

Discuss the value of the R-squared coefficient of determination in everyday language and in relation to the variables Price per Listing ($) and Cost of Advertising ($). Explain whether the model is trustworthy to provide insight into predicting the average cost of advertising required based on price per listing (Appendix 3(e)).

Discuss your analysis of the average cost of advertising required for the average price per listing (Appendix 3(f)). 3 marks

Discuss whether the model can be used reliably for a listing which is priced at $300. Include any possible issues with model. (Appendix 3(g)).

Describe in 2-3 sentences, the aim of the analysis in this section.

Summarise and discuss, using either bullet points or a table, all probabilities calculated in Appendix 4(b) with a focus on a non-technical discussion relating the results to each listing type and the location in Eastern Europe.

Create a 100% stacked column chart of the data in Table 1 (Appendix 4) to include here, with an appropriate figure number and caption. Excel instructions are provided below.

By using the 100% stacked column chart provide one insight, quoting approximate percentages.

Use the 100% stacked column chart to support a brief discussion of your calculations in Appendix 4(c). Note the insights from the 100% stacked column chart should link to your probabilities calculated in Appendix 4(c). Does the preference of Luxury stays depend on the location in Eastern Europe?