Need statistical data for comparison with my simulation

In summary, the speaker is a student working on a program for their extended essay that simulates balls being thrown. They are seeking data from real-world experiments to compare with their simulation, but have been unable to find suitable data through online searches. They are asking for recommendations on where to find this data and mention that their program is in German.
  • #1
anotheruser
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Hello, I'm new to this forum so I don't really know if this is the correct section for this question, but I couldn't find anything that fits better.

I'm in my last year in school and writing a program for an extended essay (at least that is what google tells me is the translation for the german word "facharbeit"). It is able to simulate balls being thrown under varying circumstances. I can use either Newton's or Stoke's formula for friction and use either vacuum, air or water as a medium. The ball's size, mass and drag coefficient (this is assumed to be constant throughout the simulation, though) can also be set by the user.

The simulation works fine, but my teacher insists that I proof its precision.

I just need a bunch of data of balls being thrown to compare the results with my simulation.
I have googled a lot, but I can't find simple statistical data of real-world experiments anywhere.


Does anybody know where to find this?


I will upload the finished program if you want, but it's in german and may therefore be difficult to use.
 
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  • #2


Hello, welcome to the forum! It sounds like you are working on an interesting project for your extended essay. I would recommend that you look for scientific articles or studies that have been conducted on similar simulations or experiments. These articles should include data and results that you can use to compare with your simulation. You can search for these articles using scientific databases such as Google Scholar or ScienceDirect. Additionally, you can reach out to experts in the field of physics or ballistics to see if they have any relevant data or resources that could help you with your project. Good luck!
 

1. How do I find the appropriate statistical data for my simulation?

In order to find the appropriate statistical data for your simulation, you need to determine the specific variables and parameters you are looking to compare. This will help you narrow down your search and find relevant data from credible sources such as academic journals, government databases, or industry reports.

2. What methods can I use to analyze and compare my simulation data with statistical data?

There are various methods you can use to analyze and compare your simulation data with statistical data. These include descriptive statistics, inferential statistics, regression analysis, and hypothesis testing. It is important to choose the appropriate method based on your research questions and data.

3. How can I ensure the accuracy and reliability of the statistical data I am using for comparison?

To ensure the accuracy and reliability of the statistical data you are using for comparison, it is important to use data from reputable sources. You should also carefully evaluate the data collection methods and sample size used in the study. Additionally, conducting sensitivity analyses and cross-checking results with multiple sources can help validate the data.

4. What are some common pitfalls to avoid when comparing simulation data with statistical data?

One common pitfall to avoid when comparing simulation data with statistical data is assuming causation based on correlation. It is important to carefully consider the variables and potential confounding factors that may influence the results. Additionally, using inappropriate statistical methods or misinterpreting the data can lead to inaccurate conclusions.

5. How can I effectively communicate the results of my simulation and statistical data comparison?

To effectively communicate the results of your simulation and statistical data comparison, it is important to present the data in a clear and organized manner. This can include using charts, graphs, and tables to visually represent the data. It is also important to provide a thorough explanation of the methods used and the key findings of the analysis.

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