Build multiple regression model sufficient sophistication

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Reference no: EM131073639

STA 108 Final Project

About the Final Project

The final project is an opportunity to put all you have learned in STAT 108 in action. Your task is to conduct a start-to-finish statistical analysis of a real data set. This includes formulating questions, building models, performing analysis and diagnostics, interpreting results and wrapping everything up in a report. Four datasets are uploaded on the SmartSite, choose one dataset to analyze for this final project.
Scope of the Project. 

In the final project, you are expected to build multiple regression models with sufficient sophistication aided by knowledge and techniques learned in this class. Examples of things you may consider include (but not limited to): whether transformations are needed, which predictors should be included, whether certain interaction terms and/or higher-order powers should be included, whether model assumptions hold, whether there are influencing outliers and/or severe multi-collinearity, how to choose among competing models, how to validate the final model, how to interpret your model and how the model helps you answer your questions, etc...

Last but not least, you are expected to write a report which gives a clear and coherent description of the data analysis and the conclusions based on the analysis results. The report should be prepared by a word processor such as word or latex rather than handwritten.

Project Report Format
The project report should include the follows:
1. Title Page: The title of the project, your name, email address, and section number.
2. Abstract : A brief summary of the project, questions of interest and findings.
3. Introduction: A description of (i) the relevant background of the topic; (ii) 5 questions of interest; and (iii) the motivation of the project i.e., why other people should be interested.

You should also briefly describe the data and the variables in the data.
*The questions of interest should be formulated in terms of the application, not the statistical methods.

4. Methods and Results: A detailed description of your analysis, supported by numerical results, figures and tables (figures, tables and R outputs should be included in appendices, but being referred to in the main text as needed). For example, you should describe in details how you reached your final model and then write down the final model and the assumptions, parameters estimates and relevant statistics, diagnostics, etc. You should include an exploratory data analysis step to explore the data before conducting more sophisticated analysis. For each step of your analysis, you should provide a motivation (Why do you do it? What goals you intend to achieve by this analysis?), a justification (Is the analysis reasonable for the data and the goals?), and a description of results (What does the analysis tell you?).

5. Conclusions and Discussion: A brief summary of main findings; and discussion of the follows: What do your results mean for the questions you were trying to answer? What is your conclusion? How general are your results, to what extent do they apply or not apply? What are the limitations of your analysis? What you might have done to address these limitations? And any other comments and discussions that you deem important.

6. Appendices: The following should be included in the appendices (do not include these in the main text):
• Appendix 1: Figures and tables (if any).
• Appendix 2: R Codes and outputs.
How to Submit the Report
If you decide to do the final project, you need to submit both a hard copy in class and an electronic copy through the dropbox on the smartsite by the report due date. For the electronic copy, use "STAT108-YourFirstName-YourLastName" as the filename. The preferred file format is either a word document or a pdf file.

Reference no: EM131073639

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