Estimate Acceleration of Gravity

The acceleration of gravity can be obtained by measuring a pendulum's period and its length using . The uncertainty in the average of five repeated measurements of the period is modeled with a BatesDistribution.

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\[Mu]T = Quantity[2, "Seconds"]; \[CapitalDelta]T = Quantity[0.01, "Seconds"]; period\[ScriptCapitalD] = BatesDistribution[ 5, {\[Mu]T - \[CapitalDelta]T/2, \[Mu]T + \[CapitalDelta]T/2}]

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The pendulum's length has been measured using a ruler with resolution of 1 mm, so its uncertainty is modeled with a UniformDistribution.

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\[Mu]len = Quantity[1, "Meters"]; \[CapitalDelta]len = UnitConvert[Quantity[1, "mm"], "Meters"]; len\[ScriptCapitalD] = UniformDistribution[{\[Mu]len - \[CapitalDelta]len/ 2., \[Mu]len + \[CapitalDelta]len/2.}]

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The uncertainty in the measurement of the acceleration of gravity.

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g\[ScriptCapitalD] = TransformedDistribution[ (2 \[Pi])^2 len/T^2, {len \[Distributed] len\[ScriptCapitalD], T \[Distributed] period\[ScriptCapitalD]}]

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Compare to the linear approximation.

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lin[e_, {x_, x0_}, {y_, y0_}] := Block[{f = Function @@ {{x, y}, e}}, f[x0, y0] + \!\(\*SuperscriptBox[\(f\), TagBox[ RowBox[{"(", RowBox[{"1", ",", "0"}], ")"}], Derivative], MultilineFunction->None]\)[x0, y0] (x - x0) + \!\(\*SuperscriptBox[\(f\), TagBox[ RowBox[{"(", RowBox[{"0", ",", "1"}], ")"}], Derivative], MultilineFunction->None]\)[x0, y0] (y - y0)]

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lin\[ScriptCapitalD][\[ScriptCapitalD]_] := NormalDistribution[Mean[\[ScriptCapitalD]], StandardDeviation[\[ScriptCapitalD]]]

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gApprox\[ScriptCapitalD] = TransformedDistribution[ lin[(2 Pi)^2 len/ T^2, {len, \[Mu]len}, {T, \[Mu]T}], {len \[Distributed] lin\[ScriptCapitalD][len\[ScriptCapitalD]], T \[Distributed] lin\[ScriptCapitalD][period\[ScriptCapitalD]]}]

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Compute the average acceleration using the exact and the linearized distributions.

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{\[Mu]g, \[Mu]gApprox} = {NExpectation[g, g \[Distributed] g\[ScriptCapitalD]], NExpectation[g, g \[Distributed] gApprox\[ScriptCapitalD]]}

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Compute the scales of uncertainty.

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{\[Sigma]g, \[Sigma]gApprox} = {Sqrt[ NExpectation[(g - \[Mu]g)^2, g \[Distributed] g\[ScriptCapitalD]]], StandardDeviation[gApprox\[ScriptCapitalD]]}

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Find the sampling estimate of the 90% confidence interval for the measured acceleration.

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confidenceInterval = Quantile[RandomVariate[g\[ScriptCapitalD], 10^6], {0.05, 0.95}]

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NProbability[First[confidenceInterval] < x < Last[confidenceInterval], x \[Distributed] g\[ScriptCapitalD]]

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