Perform necessary data cleansing and conversion tasks. You can report the data quality status, such as missing values, coding conditions, format problems, etc., and the tasks you have done in data preprocessing, such as data format conversion, value recoding, etc. You can contact the instructor for help in data processing. If the data is already clean enough, you can provide the information about the outcomes of data exploration. The reported information can include but not restricted to size of data, distributions of key variables, any interesting primitive findings, how top managements can use the data to make better decisions/competitive advantages etc.
Note: Feel free to use all these software (i.e. MS Excel, MS Access, SAS, and IBM SPSS Modeler etc.) in the data analysis.
Furnish a final project report based on the data analysis or regression analysis outcomes, with necessary modification and refinements.
A. The final project report is the final deliverable for the exam. It includes the following parts:
Table of contents
The data analysis motivation and objectives. This section presents the background of the data analysis, the importance of the data analysis, and data analysis objectives.
Dataset description. It includes: where it comes from, the description of major attributes (variables), the quality of the dataset, and data preprocessing
The techniques you use in the data analysis
References, if any
B. In general, the report must demonstrate your knowledge in both data analysis and the addressed business issue. It must look professional. The size of the report body/tables/figures/diagrams should not exceed 4 pages (point-12 font).
C. Issues you are to tackle during project accomplishment:
Deadline is on Thursday, April 9, 2019 at 11:59PM
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