Calculating R Square of an Exponential Function

In summary, the conversation discusses the use of R^2 to measure the fit of a data set to a known function. To find the R^2, one can calculate one minus the sum of squared errors over the sum of squares about the mean. This can be done manually or by using the Pearson product moment correlation coefficient and squaring it.
  • #1
prof.DK
2
0
Hi there,

I have googled for the R square formula, but it's very confusing, so I need some help. Please come up with an example on how to use it, if I have a exponential function on how i want to calculate its R square.

Thanks:cry:
 
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  • #2
[itex]R^2[/itex] is used to gauge the "goodness" of "fit" of a data set to some known function. So you need a data set and a function, you cannot meaningfully speak of [tex]R^2[/itex] of a function by itself.
 
  • #3
If I then have a table of data:

0 2
40 6
80 8
120 12
160 18
200 24
240 42
280 82
320 110
360 190
400 300
440 500
480 800

... and I want to find the R^2, what should I do (I don't want to use software)?
 
  • #4
Last edited:
  • #5
google: "Pearson product moment correlation coefficient"

multiply PPMCC by itself for R^2

http://mathbits.com/Mathbits/TISection/Statistics2/correlation.htm

sorry it's 4 years late...
 
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FAQ: Calculating R Square of an Exponential Function

What is an exponential function?

An exponential function is a mathematical function where the independent variable (usually denoted as x) is an exponent. It can be written in the form y = ab^x, where a and b are constants and b is the base of the exponential function.

How do you calculate R Square of an exponential function?

To calculate R Square of an exponential function, you first need to fit the data points to the exponential function using a regression analysis tool. Once the curve is fitted, you can use the formula R^2 = 1 - (SSres/SStot), where SSres is the sum of squares of residuals and SStot is the total sum of squares. This will give you the R Square value, which represents the goodness of fit of the exponential function to the data.

What does R Square tell us about an exponential function?

R Square is a statistical measure that represents the proportion of variation in the dependent variable (y) that can be explained by the independent variable (x). In the case of an exponential function, a high R Square value indicates that the curve fits well to the data points and the relationship between x and y is strong. On the other hand, a low R Square value indicates a poor fit and a weak relationship between x and y.

Can R Square be negative for an exponential function?

No, R Square cannot be negative for an exponential function. Since R Square is calculated as the square of the correlation coefficient (r), which ranges from -1 to 1, the R Square value will always be between 0 and 1 for an exponential function. A negative value of r indicates a negative correlation between x and y, but when squared, it becomes positive and thus the R Square cannot be negative.

How can R Square be used to compare different exponential functions?

R Square can be used to compare the goodness of fit of different exponential functions to the same set of data points. A higher R Square value indicates a better fit and a stronger relationship between x and y, while a lower R Square value indicates a weaker fit. However, it is important to note that R Square should not be the only factor considered when comparing different models, as it can be influenced by the number of data points and the complexity of the model.

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