Is There a Simple Quantitative Technique for Projecting Values in a Series?

In summary, the conversation is about finding a general extrapolation formula or other simple quantitative technique for projecting values in a given series. The person is asking if there is a way to determine the final value of y in a series with the given data, and they suggest a possible value of -6.0. However, the expert suggests that there is no mathematical answer and cautions against using a polynomial fit for this data.
  • #1
AA Institute
21
0
Hi,

Is there a general extrapolation formula (or other *simple* quantitative technique) for projecting values in a given series?

I have these numbers in a certain series sequence:

x=1, y=-3.80, x=2, y=-4.15, x=3, y=-4.47, x=4, y=-4.77, x=5, y=-5.05, x=6, y=-5.27, -5.40

Question is: does y converge to a definite final value? What is that value likely to be? I would guess somewhere around -6.0, but I want to know with more precision.

Thanks for any pointers.

AA
 
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  • #3
Question is: does y converge to a definite final value? What is that value likely to be? I would guess somewhere around -6.0, but I want to know with more precision.
Given this data (values of y at a discrete set of x's), there is no mathematical answer to your question. If you were to graph it, you might see some useful trend. A polynomial fit is probably a bad idea, since it will very likely give you fluctuations that are not there.
 

What is an extrapolation formula?

An extrapolation formula is a mathematical equation that is used to estimate values beyond the range of known data points. It involves using the existing data points to predict what the values would be if the trend continues.

Why is extrapolation important in scientific research?

Extrapolation allows scientists to make predictions and draw conclusions even when there is limited data available. It can also help identify patterns and trends that may not be apparent in the existing data.

What are the limitations of extrapolation formulae?

Extrapolation formulae are based on the assumption that the trend observed in the existing data will continue. However, this may not always be the case, and the predictions made through extrapolation may not be accurate. It is also important to consider the potential for error and uncertainty in the data.

How can the accuracy of extrapolation be improved?

The accuracy of extrapolation can be improved by using more data points and a wider range of data. It is also important to account for any potential errors or biases in the data, and to use multiple extrapolation methods to compare results.

In what fields is extrapolation commonly used?

Extrapolation is commonly used in various scientific fields, such as economics, meteorology, and environmental science. It is also commonly used in engineering and technology to predict future trends and make projections for new products or technologies.

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