Simple Pendelum - Help with Quadratic Regression on Excel?

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SUMMARY

This discussion focuses on performing quadratic regression in Excel to determine the gravitational constant (g) based on pendulum data. The user graphed a scatter plot with pendulum length (L) on the x-axis and period (P) on the y-axis, but encountered issues with obtaining a single trend line for multiple series. The equation derived from the small angle approximation is L = (G/((2π)^2)) P^2. The user seeks methods to ensure the quadratic regression approximates only in terms of ax² and to achieve a more accurate value for g.

PREREQUISITES
  • Understanding of quadratic regression analysis
  • Familiarity with Excel graphing tools
  • Knowledge of pendulum physics and the small angle approximation
  • Basic statistical concepts, including mean and trend lines
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  • Explore methods for combining multiple data series in Excel scatter plots
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USEFUL FOR

Students and educators in physics, data analysts using Excel for statistical modeling, and anyone interested in accurately modeling pendulum motion and gravitational calculations.

kmr159
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1.
I am trying to determine the value of g based on a simple pendulum.
I have graphed a scatter plot with the x-axis as L and the y-axis as P. I have 3 different series for different lengths of pendulum. When I try to find a line of best fit I get something like cx^2 + dx + e and this trend line is only for one series.

2 Parts - Is there any way to get the trend line to be the line of best fit for all my different series (different lengths)
- Is there any way to make my quadratic regression approximate only in terms of ax^2.





2.
The equation, for a small angle approximation works out to L=(G/((2pi)^2)) P^2. Where L is the length of the Pendulum in meters, G is Gravity and P is the period of the pendulum.




3. excel graph - the regression gives a wildly incorrect value of G. Attempt: Determined the formula and how to get the solution
 
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One series consists of a set of measurements of the period, all with the same length? If so, why would you fit a quadratic to that? Why isn't it just a matter of taking the mean? Or, throw all the data into one chart, using an XY plot?
 

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