Systems Analysis Methods :

Requirement:

Choose, or collect, some data to analyze that you think should fit a statistical distribution (normal, exponential Poisson, etc.). Your dataset should have a sufficient number of observations where you can complete a full analysis of the data (mean, median, standard deviation, etc.). Examine the data against a theoretical statistical distribution based on the statistical parameters of your data. Submit a report that describes the results and conclusions of your analysis, including graphs, tables of numbers, computations, etc. Plots and other visual representations of data are very useful in conveying your conclusions. Using Excel or other statistical analysis software is encouraged.
Submit your report in PDF. Your report will probably be about 4-6 pages long, but there are no fixed upper or lower bounds on its length. Write at an appropriate length paper: neither so brief that you omit information, nor so verbose that you overstate your analysis or bury important information under irrelevant details.
Your report might contain the following parts. You are permitted to write additional sections as well.
Title and author(s). The title should be descriptive of your research questions.
Overview of research questions and results. In 1-3 sentences, state each research question — that is, each problem you investigated. What are you trying to compute, and why? After each research question, clearly state the answer you determined. You don’t have to give details or justifications yet — just the answer.
Motivation and background. State, explain, and motivate the problem. In other words, explain the context and why the problem matters. This expands on the research questions that you already stated. Why are they worth computing? What difference would knowing the answers make?
Dataset. Describe the real, pre-existing dataset that you used, including exact URLs as necessary. You do not have to turn in the dataset itself (it may be quite large, or it might be available only via the web rather than as a single download).
Methodology (algorithm or analysis). Make a complete, clear, unambiguous English description of the analysis you performed. This should be sufficient for someone else to reproduce your results, even without access to your source code.
Results. Present and discuss your research results. Focus in particular on the parts that are most interesting, surprising, or important. Discuss the consequences or implications.
Reproducing your results. Give clear and explicit instructions for obtaining the data and for running the analysis, and for interpreting the results or finding the interesting parts in the output
Collaboration and reflection. What did you learn from this assignment? What do you wish you had known before you started? What would you do differently?

 
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