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Writing The results of a data analysis is not a capability with which everyone is born. It requires the practice and at least at the beginning a bit of instructions.
When writing your report, the organization will set up you for free. A good outline is: 1) Overview of the problem, 2) Your data and modeling approach, 3) The results of your data analysis (plots, numbers, etc.) and 4) their essential conclusions.
Describe the problem. Which material question are you trying to tackle? That does not have to be long, but it should be clear.
2) Data and model
Which data did you use to tackle the question, and how did you do it? Be specifically in the description of your approach. For example:
Sometimes your data and model section contain plots or tables and sometimes it will not. If you feel that a plot helps the reader to understand the problem, define the problem or the data - unlike your results - then go further and include it. A great example here are tables 1 and 2 in the main paper on the pendicide study. These tables help the reader to understand some important properties of the data and the approach, but not the results of the study itself.
In your results area, you include all numbers and tables required to create your case. Label it (Figure 1, 2, etc.), give you informative captions and refer to your numbered labels in the text in which you discuss it. Typical things that can include here may include: images of the data; Pictures and tables showing the built-in model; Tables of model coefficients and summaries.
What did you learn from the analysis? What is the answer, if available, on the question you have set at address?
Make the sections as short or long as you need to be. For example, a conclusion section is often quite short, while a result section is usually a bit longer.
It's okay to use the first person to avoid clumsy or bizarre sentence constructions, but try to be economical.
Do not contain the computer code unless explicitly called. Note: The model outputs do not count as a computer code. The outputs should be used as evidence in their result range (ideally formatted in a beautiful way). I mean with the code the order of commands with which you have processed the data, and generate the outputs.
If in case of doubt use shorter words and sentences.
A very common way that reports go wrong is if the writer simply tells the thought process he or she followed :: First, I did that, but it did not work. Then I did something else, and I found A, B and C. I was not really sure what I should do from B, but C was interesting, so I followed with D and E. Then I did that ... "Do not do that. The desire for specificity is admirable, but the overall effect is one of the amateurism. Follow the recommended outline above.
Here is a good example of an analysis for an analysis of a few relatively simple problems. Since the problems are so straightforward, there is no great need for an outline of the type described above. Nevertheless, the spirit of these guidelines is clearly in evidence. Note the clear exhibition, the marked numbers and tables referred to in the text and the careful integration of visual and numerical evidence in the entire argument. This is a fraud worth emulating.
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