A scientific report is not just a summary, it’s a detailed statement that explains the methods, results and conclusions of the study.

A scientific report is not just a summary, it’s a detailed statement that explains the methods, results and conclusions of the study.
You can’t just show the “examples” by talking about what you learned while conducting the study (it’s a big step down from writing an actual report). The only information you can present is the results – as you did with your undergraduate thesis. It’s up to you to make the case for the conclusions you come up with by presenting the results.
If you want the reader to believe that you understand statistical concepts even though you didn’t understand concepts in a prior undergraduate course, then your evidence needs to include a scientific report. This has something to with research design, the interpretation of your results, and the reporting of your results.
There’s something to be said for getting your PhD in statistics. It’s a very demanding set of degree programs that are difficult, but if you’re willing to commit to one year of your time you will learn some useful things about statistics. One good thing about statistics PhD programs, however, is that they are designed for science and are generally designed to give you information about science. If you are serious about learning how to get the results you want, you’ll need to master the science.
When you come across a scientific report, try to remember three things. First, this isn’t a description of your learning – it’s a description of the results you reported and how you obtained them. Use references to the data, methods, and findings when summarizing results from this study. Second, you will find that statistics, and the scientific report, are very hard to understand on its own. Often, you have to spend a lot of time looking at the details in a report to come to grips with the main points. Finally, if your report provides data, you need to do several things:
Look at your data carefully to gain an understanding of the concepts you learned.
Look at your data several times.
Ask questions to understand how the results are calculated.
The first three are the only parts that will really show the real process of learning. It’s easy to focus too much on the data and forget that the results might not fit your model. For example, if you were designing your study to find out that females have higher sex drive than males, you might overlook this fact, or you might try to answer the question by comparing the “sex drive” responses of men with those of women. These two examples aren’t wrong, but if you really think they’ll give you new insights into your study, they won’t.
As for the other two, the questions you ask and the questions you answer are crucial! There’s no simple answer to your questions. You’re going to need to figure out what your data means, what variables you actually measured, and how you can measure it. This will help answer the questions you have about how you collected your data (or maybe you want to take a new data collection method altogether). I recommend reading up on data analysis before your presentation so you’ll have an understanding of how to answer those questions correctly. You might have to read a couple hundred pages of data analysis before you figure out which questions you have. I know I did!
Finally, you will need to interpret the results. You must report what you observed in the data. A good way to do this is by