Uncertainty of Average Acceleration

AI Thread Summary
The discussion focuses on calculating the uncertainty in average acceleration, σ_{a,avg}, for an object in free fall over multiple time intervals. Participants clarify that the uncertainty should be derived from the data set rather than from other variables. The correct approach involves using the formula for variance, specifically σ_x^2 = ∑(x_i - x̄)^2/N, where x_i represents the individual accelerations and x̄ is the average acceleration. There is frustration expressed regarding the lack of reference material in the textbook for this specific calculation. Ultimately, the correct expression for σ_{a,avg} is confirmed, despite the initial confusion.
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Homework Statement



You have determined the acceleration a_{i} of an object in free fall for i = 1 to n different time intervals. What is the algebraic expression for the uncertainty σ_{a,avg} in a_{avg}? (Use any variable or symbol stated above as necessary.)

The answer box is formatted as such: σ_{a,avg} = \sqrt{\sum^{i=1}_{n}}

and I have to fill in the space after the summation under the square root.

No variables or symbols were specifically given for the problem outside of the ones in the question, but I had written the formula for average acceleration previously (in the relevant equations section) that may have variables I can use.

Homework Equations



a_{avg} = \frac{v_{23} - v_{12}}{t_{23} - t_{12}}

The Attempt at a Solution



I honestly have no clue where to begin. I don't really have much knowledge of uncertainty calculations and so I am pretty lost here. I tried one method first that I realized is incorrect.

Any help would be extremely appreciated.
 
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Do you know the definition of the standard deviation \sigma or the variance \sigma^2? It seems unusual to be asked such a question without at least some reference to the definition in the text.
 
Yeah, I know the definitions. They are given to me. I can usually apply the formulas, but I am not sure how to do it for this question.

After some thinking, I believe I could write the formula a = Δv/Δt, since I can calculate σ_{Δv} and σ_{Δt} using basic addition. So σ_{Δv} = σ_{v_{12}} + σ_{v_{23}} and σ_{Δt} = σ_{t_{12}} + σ_{t_{23}}. So I can then apply it to the multiplication formula to find the uncertainty for a. Using the formula given in the text, I would think the uncertainty for the basic formula I gave in my original post would be

σ_{a_{avg}} = a_{avg}\sqrt{(\frac{σ_{Δv}}{Δv})^{2} + (\frac{-σ_{Δt}}{Δt})^{2}}

I don't know whether this is correct or not. And if it is, I am stuck trying to figure out how to use the summation that is given in the answer area.

For ease of reference, here is the answer area:

c76x1.png
 
Yeah, you're kind of going off into space here. This problem isn't about dealing with uncertainties from other variables, just from the data set that you have.

Something like this formula should look familiar:

\sigma_x^2 = \sum_i (x_i - \bar x)^2/N
 
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It's been about 2.5 years since I did real standard deviation or variance calculations. The two formulas given in the text are both about uncertainties from other variables. One is for addition of uncertainties and one is for products of uncertainties. And in previous assignments, all the calculations we did dealt with these formulas. This is what is throwing me off because the book doesn't include anything regarding the answer formula. And as such, I do not fully understand your formula. I believe it looks familiar from my previous math experience though.

So I am guessing x_{i} would be a_{i} and /bar{x} would be a_{avg}?
 
Yes. You might also see \sigma^2_x = \langle x^2 \rangle - \langle x \rangle^2. Also note that I neglected a factor of N which is necessary to to get it right.
 
Muphrid said:
\sigma_x^2 = \sum_i (x_i - \bar x)^2/N

Alright, this is the answer after all. Even though there is not a single reference to this in the book! Thanks very much for your help!
 
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