I have the problem below that needs to be completed. I have included Weekly GOOGLE time series data from the past few years. The analysis must be done on this data. I have also included sample code and analysis. Please do the analysis similar to this with thorough answers. It will be easier if you just copy and paste the sample code and modify it. 

The analysis should be submitted as a report consisting of two sections:

1. A non-technical summary not longer than one typewritten page, describing the conclusions of your statistical analysis to a non-technical audience. It should be intelligible to a person who does not know regression analysis. Suppose you are talking to your boss who does not know statistics or to a friend who is not familiar with statistical terminology.

2. A technical summary not exceeding 5 pages, with details of your statistical analysis. This section is intended for a statistically literate audience and must be written in a clear organized fashion. For instance, you can organize the report into subsections such as

a. Exploratory analysis of the data.

b. Model fitting.

c. Residual analysis and model diagnostics.

d. Forecast analysis

e. Analysis of the results and discussion.

You should include appropriate output and graphs from your  R programs in your document in a presentable format. Further details may be relegated to an appendix that may contain the R code, some graphs, computer output or supplementary information about the field of study.

It is possible that you may not find a satisfactory model that fits adequately your data. Sometimes a data set may admit more than one satisfactory answer; sometimes there may be none. If the statistical analysis shows that no time series models are suitable for your data set, please mention what approaches you have tried and what was unsatisfactory about them. If there is more than one suitable model, mention the pros and cons and compare their performance in forecasting future observations.