Plot normal distribution with measurement results

In summary, the process involves taking measurement results and visualizing them using a normal distribution curve. This entails calculating the mean and standard deviation of the data to represent the central tendency and variability. The normal distribution is then plotted on a graph, illustrating how the measurements are spread around the mean, allowing for analysis of trends, patterns, and the probability of different outcomes within the dataset.
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Plot normal distribution with measurement results
Hi,

I have completed an experiment at university as part of my internship and have now received several measurement results which I would like to analyze statistically and plot the results as a normal distribution in Mathematica. Is this even possible with Mathematica? Unfortunately, I haven't found anything about it on the Internet.
 
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  • #2
You can plot pretty much anything in Mathematica, but I am not sure what you mean by plot the results as a normal distribution
 
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Do you want to compare your data with a theoretical normal distribution graphically?
You could easily plot a histogram of your data and compare it to a normal distribution whose mean equals your data mean and whose standard deviation equals your data standard deviation.
You could similarly plot the cumulative distribution of your data and compare it to the CDF of a normal distribution whose mean equals your data mean and whose standard deviation equals your data standard deviation.

Alternatively, you can statistically compare your data with a normal distribution using the Chi-squared goodness of fit test. But I am not immediately sure how many degrees of freedom you would have if you use the sample data to estimate the parameters of the normal distribution. I think it would be reduced by 2.
 

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