Working out the equation for coordinates on a graph

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Discussion Overview

The discussion revolves around determining an equation for a set of data points represented on a graph. Participants explore methods for fitting a trend line to the data, considering both linear and non-linear models, and discuss the application of software tools for analysis.

Discussion Character

  • Exploratory
  • Technical explanation
  • Mathematical reasoning
  • Homework-related

Main Points Raised

  • One participant presents a series of data points and seeks guidance on deriving a trend line equation.
  • Another participant suggests using a linear least-square fit unless a different underlying model is indicated.
  • A participant expresses uncertainty about how to apply the linear fitting method to their data.
  • A suggestion is made to calculate averages and use specific equations to derive slope and intercept for the linear model.
  • One participant anticipates that an exponential curve might better represent the trend and questions the feasibility of obtaining such an equation.
  • Concerns are raised about the complexity of non-linear fitting, indicating it may require multidimensional minimization techniques.
  • A suggestion is made to utilize existing software, such as Matlab, for fitting the data.
  • A participant indicates they have Matlab but is unsure how to program their data for analysis.

Areas of Agreement / Disagreement

Participants express differing views on the appropriate model for the data, with some advocating for linear fitting while others suggest an exponential trend may be more suitable. The discussion remains unresolved regarding the best approach to take.

Contextual Notes

There are limitations in the discussion regarding the assumptions made about the data distribution and the specific equations referenced without full context. The complexity of non-linear fitting is acknowledged but not fully explored.

Who May Find This Useful

This discussion may be useful for individuals interested in data analysis, particularly those working with trend line fitting in statistical or engineering contexts.

Saints-94
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I have a series of data points for X and Y points on a graph. The data is quite random and I am trying to work out a trend line so I can then form an equation for the line. How would I go about working out the equation for the data below.
(0, 580)
(6.7, 495)
(13.4, 445)
(18.7, 365)
(22.8, 350)
(27, 340)
upload_2017-3-6_20-7-31.png
 
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Unless there is an underlying model that would suggest otherwise, I would consider that to be a straight line and do a linear least-square fit.
 
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I'm not sure how I can apply that to the data that I have. Where would I start with working out an equation?
 
You need to first calculate the averages, ##\bar{x}## and ##\bar{y}##. Then use eqs. (16) and (20) in the link I gave you to get ##\mathrm{ss}_{xx}## and ##\mathrm{ss}_{xy}##. You then get the slope from eq. (27) and the intercept from eq. (28).
 
I was expecting to get a trend line that looked like an exponential curve. Is it possible to work out an equation that would give me an exponential curve?
 
Saints-94 said:
I was expecting to get a trend line that looked like an exponential curve. Is it possible to work out an equation that would give me an exponential curve?
The problem with the non-linear case is that you can't get a direct answer. It becomes a multidimensional minimization problem.

The best is to use existing software to do this. Most graphing programs can do this, as well as other software such as Matlab.
 
Ok, thanks. I have the Matlab software, but am unsure how to programme my data.
 

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