Please help me with Gaussian Distribution and central limit theorem in matlab

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SUMMARY

The discussion focuses on generating a Gaussian distribution using MATLAB, specifically utilizing the Central Limit Theorem and the rand function. A user seeks assistance in creating a random variable with an approximate Gaussian distribution and visualizing it through graphs. Key advice includes using the randn function for generating Gaussian random numbers, with an example provided for creating a 6x6 matrix with a specified mean and standard deviation.

PREREQUISITES
  • Understanding of Gaussian distribution and its properties
  • Familiarity with MATLAB programming environment
  • Knowledge of the Central Limit Theorem
  • Basic graphing techniques in MATLAB
NEXT STEPS
  • Learn how to use MATLAB's randn function for generating Gaussian random variables
  • Explore MATLAB's plotting functions to visualize distributions
  • Study the Central Limit Theorem and its applications in statistical analysis
  • Investigate the relationship between Gaussian amplitude distribution and instantaneous power
USEFUL FOR

Students, data analysts, and researchers working with statistical modeling and simulations in MATLAB, particularly those interested in Gaussian distributions and their graphical representations.

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please help me with Gaussian Distribution and central limit theorem in matlab!

:cry:I am trying to generate a random variable with a approximate gaussian distribution using the rand function and central limit theorem, got stuck when trying it. Please help me. Also want to know how to produce a graph showing the distribution of the values the
program generates and the graph of a Gaussian distribution.
If a signal has a Gaussian amplitude distribution, what is the distribution of the instantaneous power? Graph the power distribution generated using the Central Limit Theorem.

Help me!:cry::confused:
 
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Dear please provide the code you have developed till now so I can see what changes you should make or what you should add...
 


How can we know where you are stuck?

By simply guessing, maybe you are having problems with rand, that's a uniform distribution, try randn which will give you Gaussian with mean 0 and sd 1. You can element-wise multiply to adjust the parameters, eg 5 + 2.*randn(6,6) will give you a 6x6 matrix of Gaussian random numbers, each with mean 5 and standard deviation 2.
 

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