Guest TheMagical7 Posted March 2, 2018 Report Share Posted March 2, 2018 Hi everyone. I am working with string-coupled pendulums, as I am dealing with the relationship of two pendulum, I am becoming increasingly frustrated that that I have not been able to linearize anything - they are sin/cos graphs and it's just so frustrating. Why are we required to produce linear graphs? Why can't I just compare the theoretical equation for the displacement of a pendulum, with the equation obtained from graphing my results? I could compare multiple aspects to get indicators of systematic errors, random errors are just the spread from the sine wave, and as for uncertainties, I can use trigonometric identities. I am so so frustrated. DO WE NEED LINEAR GRAPHS and will I lose marks from not producing one? Reply Link to post Share on other sites More sharing options...
kw0573 Posted March 2, 2018 Report Share Posted March 2, 2018 To linearize, you can just graph the inverse function. For example, if graph looks like y = Aex, you can graph x vs ln y. IB wants you to find line of best fits of greatest and least slope, which can provide a quantitative estimate of random and systematic errors.Quantifying extent of such errors is useful in providing a stronger argument. For example, without finding uncertainty in y-intercept graphically, you cannot justify the presence or absence of a systematic error. Similarly, a line of best fit, if pass through all error bars, can indicate absence of random errors. Reply Link to post Share on other sites More sharing options...
Guest TheMagical7 Posted March 2, 2018 Report Share Posted March 2, 2018 5 hours ago, kw0573 said: To linearize, you can just graph the inverse function. For example, if graph looks like y = Aex, you can graph x vs ln y. IB wants you to find line of best fits of greatest and least slope, which can provide a quantitative estimate of random and systematic errors.Quantifying extent of such errors is useful in providing a stronger argument. For example, without finding uncertainty in y-intercept graphically, you cannot justify the presence or absence of a systematic error. Similarly, a line of best fit, if pass through all error bars, can indicate absence of random errors. It's a SINE or COS curve SINUSOIDAL graph :'( I can quantify uncertainties, but I can only give a qualitative estimate of random and systematic errors, by examining the components of the sine graph. Reply Link to post Share on other sites More sharing options...
kw0573 Posted March 4, 2018 Report Share Posted March 4, 2018 Yes I know. I said that linear plots allow much effective quantitative analysis of random and systematic errors. A hint I can give is you should only plot analyzed data. For example, if you only need amplitude, or frequency, or period, you can just plot those instead of the entire sinusoidal graphs. It should be easier to linearize once you reduce amount of data. Reply Link to post Share on other sites More sharing options...
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