question 3 select the source distribution from which the sample used to plot this cumulative distribution function most likely was drawn. cdf3 in matlab

To determine the source distribution from which the data used to create a specific cumulative distribution function (CDF) was drawn, you can use the Quantile-Quantile (Q-Q) plot.

Here is an example of how to create a Q-Q plot in MATLAB to help you determine the source distribution:

main.m
% Define the sample data used to create cdf3
data = cdf3; % Assuming cdf3 is the cumulative distribution function data in MATLAB

% Generate a sample from a known distribution (e.g., Normal distribution for example)
known_distribution = 'Normal'; % You can replace this with another known distribution

rng(1); % Set random seed for reproducibility
sample_size = numel(data);
sample = random(known_distribution, sample_size, 1);

% Create the Q-Q plot
qqplot(sample, data);
title('Q-Q Plot');

% Determine the fit between the data distribution and the known distribution
disp('Fit between the data distribution and the known distribution:');
disp(adtest(data)); % Anderson-Darling test for distribution fit
707 chars
18 lines

After running this code, check the Q-Q plot generated. If the points fall roughly in a straight line, it suggests that the data (cdf3 in this case) was drawn from the assumed distribution (e.g., Normal). The Anderson-Darling test result will also provide more information about how good the fit is.

This approach can help you infer the source distribution from which the sample used to plot the cumulative distribution function was drawn in MATLAB.

related categories

gistlibby LogSnag