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Unformatted text preview: follows: prob = binocdf(3,25,0.2); We could also sum up the individual values of the probability mass function from to : prob2 = sum(binopdf(0:3,25,0.2)); Both of these commands return a probability of 0.234. We now show how to generate the binomial distributions shown in Figure 2.3. % Get the values for the domain, x. x = 0:6; % Get the values of the probability mass function. % First for n = 6, p = 0.3: pdf1 = binopdf(x,6,0.3); % Now for n = 6, p = 0.7: pdf2 = binopdf(x,6,0.7); Now we have the values for the probability mass function (or the heights of the bars). The plots are obtained using the following code. % Do the plots. subplot(1,2,1),bar(x,pdf1,1,'w') title(' n = 6, p = 0.3') xlabel('X'),ylabel('f(X)') axis square subplot(1,2,2),bar(x,pdf2,1,'w') title(' n = 6, p = 0.7') xlabel('X'),ylabel('f(X)') axis square...
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This note was uploaded on 11/29/2010 for the course ECE 302 taught by Professor Gelfand during the Spring '08 term at Purdue.
 Spring '08
 GELFAND

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