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Produce a discrete time series y(ti) by super positioning 5 cosinusoidal components,
for your own choice of the amplitudes (aj) and frequencies (fj).
Add some Gaussian noise to each digitised value. Experiment with amplitudes (including that of the noise term), and frequencies, showing results graphically. Then smooth your noisy time series with at least two different filters, e.g., a simple moving average smoother and an order two binomial filter.
Discuss the relative performance of the smoothers. You should consider quantifiable parameters such as; variance, r.m.s. deviations from the noise-free time series, and signal attenuation. Comment on the validity of the expression below, for your chosen smoother.
APPLICATIONS OF LAGRANGE''S MEAN VALUE THEORM?
(i) Test for the existence of regression (the F-test). Carefully de ne the null and alternative hypothesis, and explain the result of any R output you obtain. (ii) Which of the
A) Prove the following theorem by considering two distinct cases. For any integer n, n 2 + n is even. B) If x = r 2 - s 2 and y = 2rs for any integers r and s, then x 2 +
given sample A : HAS SIZE 6,MEAN 8,VARIANCE 16 AND SAMPLE B:has size 10,mean 20 and variance 36 .calculate pooled sample variance
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Answer the following set of simultaneous equations using elimination or substitution method. a) x-y +z= 10 b) 3x+y+2z=34 c) -5x+2y-z=-14
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