Create a standard normal distribution object with the mean $$\mu$$ equal to 0 and the standard deviation $$\sigma$$ equal to 1.

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The simplest way to create a matrix in MATLAB is to use the matrix constructor operator,. Create a row in the matrix by entering elements (shown as E below) within the brackets. Separate each element with a comma or space: row = E1, E2., Em row = E1 E2. Example: creating a handle to an anonymous function with one vector-valued input variable bowlVec = @(x)x(1)^2+(x(2)-2)^2; Example: creating a handle to a named function with two scalar-valued input variables bowlVecNamed = @(x)bowlNamed(x(1),x(2)); ezsurf cannot accept handles with vector-valued arguments (stick with examples on previous pages).

Define the input vector x to contain the values at which to calculate the pdf.

Compute the pdf values for the standard normal distribution at the values in x.

Each value in y corresponds to a value in the input vector x. For example, at the value x equal to 1, the corresponding pdf value y is equal to 0.2420.

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Alternatively, you can compute the same pdf values without creating a probability distribution object. Use the pdf function, and specify a standard normal distribution using the same parameter values for $$\mu$$ and $$\sigma$$.

The pdf values are the same as those computed using the probability distribution object.

Create a Poisson distribution object with the rate parameter, $$\lambda$$, equal to 2. Get mac serial number.

Define the input vector x to contain the values at which to calculate the pdf.

Compute the pdf values for the Poisson distribution at the values in x.

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Each value in y corresponds to a value in the input vector x. For example, at the value x equal to 3, the corresponding pdf value in y is equal to 0.1804.

Alternatively, you can compute the same pdf values without creating a probability distribution object. Use the pdf function, and specify a Poisson distribution using the same value for the rate parameter, $$\lambda$$.

The pdf values are the same as those computed using the probability distribution object.

Create a standard normal distribution object.

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Specify the x values and compute the pdf.

Plot the pdf.

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Create a Weibull probability distribution object.

Specify the x values and compute the pdf.

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Plot the pdf.