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This problem introduces to Statistics Toolbox and functions in Matlab and perform statistical analysis on
provided data to: 1) fit distribution to "experimental" data; 2) conduct simple probability analysis using the
"fitted" model and compare the results obtained from the "experimental" data.
You need to download the data file MAE 301 - [url removed, login to view] posted on Blackboard. It
saves random values of a normal distribution variable with unknown mean and variance.
1. Load the data into Matlab workspace as a vector and estimate the mean and variance of the random
variable using the built-in functions mean and var. Because the data size is very large, the estimated
mean and variance can be assumed to be the population mean μ and variance σ
2. Using Z-table analytically determine the probability P X 2 , and "experimentally"
determine the probability by inspecting the original data (i.e., sort the values and count the number of
the values within the range). Compare the results.
3. Start the Distribution Fitting Toolbox in Matlab by typing dfittool in the command window, import the
data vector, and fit it with normal distribution. Save the figure displaying both the data histogram and fit
function. Find the fit normal distribution mean and variance via the Fit Manager (Save screen shot)
timeline = 10 hours
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