Verification of central limit theorem
AIM: Simulating the Central Limit Theorem with the Uniform Distribution in MATLAB.
OBJECTIVE: To verify Central limit theorem using MATLA
EQUIPMENT:
PC with windows (95/98/XP/NT/2007).
MATLAB Software
PROGRAM:
uniform_RVs = [];
sample_averages = [];
random_draw = [];
for i = 1:500
for j = 1:100
random_draw = [random_draw 1+rand];
end
sample_averages = [sample_averages mean(random_draw)];
uniform_RVs = [uniform_RVs random_draw];
random_draw = [];
end
figure(1)
hist(uniform_RVs, 25)
xlabel('Observation')
ylabel('Frequency')
figure(2)
hist(sample_averages, 25)
xlabel('Observation')
ylabel('Frequency')
sample_mean = mean(sample_averages)
sample_var = var(sample_averages)
CONCLUSION: Thus Cental limit theorem is verified using MATLAB
OUTCOME: The Student must be able to understand how to verify Central limit theorem using MATLAB
VIVA QUESTIONS:
? Define Central limit Theorem?
? List the applications of Central limit Theorem?

CreatedMar 03, 2020

UpdatedMar 03, 2020

Views52
Introduction
Basic operations on Matrices
Genaration of various signals and sequences
Operations on signals and sequences
Finding the even and odd parts of signal/sequence and real and imaginary parts of signal
Verification of Linearity and time invariance properties of a given continuous/discrete system
Linear Convolution
Auto correlation and cross correlation between signals and sequences
Computation of unit sample, unit step and sinusoidal response of the given LTI system and verifying its physical reliability and stability properties
GIBBS phenomenon
Sampling theorem verification
Finding the Fourier transform of a given signal and plotting its magnitude and phase spectrum
Laplace Transforms
Locating the zeros and poles and plotting the pole zero maps in zplane for the given transfer function
Gaussian Noise
Verification of Wiener Khinchin relation
Removal of noise by autocorrelation/crosscorrelation
Extraction of Periodic signal masked by noise using correlation.
Checking a Random process for stationarity in wide sense
To find a mean and variance of a discrete random variable
To find a moment generating function of a discrete random variable
Computation of Energy of sinusoidal signal
Computation of energy of rectangular pulse
Computation of Average Power
Waveform Synthesis
Find and plot the cumulative distribution and probability density functions of a random variable
Verification of central limit theorem