Webpage title: How to Calculate Mean Error: A Step-by-Step Guide

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In summary, the conversation is about obtaining the mean error and how it differs from the mean absolute deviation. The speaker suggests two possible interpretations of the mean error - the absolute difference between the data and the mean, or the difference between the experimental and actual values. They also suggest looking up the exact definition of mean error.
  • #1
smither777
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hi,

can you help me in obtaining the mean error? I was able to obtain the standard deviation for my data, but i don't know how to get the mean error..
thank you very much!
 
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  • #2
smither777 said:
hi,

can you help me in obtaining the mean error? I was able to obtain the standard deviation for my data, but i don't know how to get the mean error..
thank you very much!
The error is
|x-mean(x)|
so the mean error is
mean(|x-mean(x)|)
I think this is what is intended, but usually this quantity is called the mean absolute deviation.
The other posibility is if you knew for each sample what should have resulted then it could mean
mean(x_experimental-x_actual)
or
mean(|x_experimental-x_actual|)
Can't you look up exactly what was "mean error" means?
 
  • #3


Sure, I'd be happy to help! The mean error is a measure of the average difference between the observed values and the predicted values. To calculate it, you can use the following formula:

Mean error = (sum of absolute errors) / (number of data points)

To obtain the sum of absolute errors, you can take the absolute value of the difference between each observed value and its corresponding predicted value, and then add these values together. The number of data points is simply the total number of values in your dataset.

I hope this helps! Let me know if you have any further questions. Good luck!
 

What is mean error?

Mean error is a measure of the average difference between a set of data points and a predicted value. It is used to assess the accuracy of a prediction or model.

How is mean error calculated?

The formula for mean error is the sum of all the errors (the difference between each data point and the predicted value) divided by the total number of data points. It can also be calculated by taking the average of the absolute values of the errors.

What is the difference between mean error and mean square error?

Mean error is calculated by taking the average of the errors, while mean square error is calculated by taking the average of the squared errors. Mean square error gives more weight to larger errors, making it a more sensitive measure of accuracy.

What does a positive or negative mean error value indicate?

A positive mean error value indicates that the predicted value is on average higher than the actual data points, while a negative mean error value indicates that the predicted value is on average lower than the actual data points.

How is mean error used in scientific research?

Mean error is commonly used in scientific research to evaluate the accuracy of mathematical models and predictions. It can also be used to compare the performance of different models or to assess the effectiveness of data collection methods.

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