gibson:teaching:fall-2014:math445:hw5

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Main concept for this homework: the `for`

loop.

1. Write a function `mymean`

that uses a `for`

loop to compute the mean of the elements of its input vector. Test that it's correct by comparing to Matlab's built-in `mean`

function on a random vector.

2. Write a function `mystd`

that uses a `for`

loop to computes the standard deviation of the elements of its input vector. Test by comparison to Matlab's built-in `std`

function on a random vector.

3. Write a script that produces a 10 x 10 multiplication table whose first three lines are

1 2 3 4 5 6 7 8 9 10 2 4 6 8 10 12 14 16 18 20 3 6 9 12 15 18 21 24 27 30 . . .

Try to get the output in **exactly** this form.

4. Write a function `y = matvecmult(A,x)`

that uses nested `for`

loops to compute the matrix-vector product
*y = Ax* according to the formula

where *N* is the number of columns of *A*. Be sure to check for compatibility between *A* and *x*. For an *M x N* matrix *A*, *x* must be an *N*-dimensional column vector, and *y* will be an *M*-dimensional column vector. If *A* and *x* do not have compatible dimensions, print an error message and return *0*-dimensional vector (a null vector).

5. Write a function `C = matmatmult(A,B)`

that uses nested `for`

loops to compute the matrix-vector product
*C=AB* according to the formula

where *N* is the number of columns of *A*. If A is *M x N* and *B* is *N x P*, then *C* is *M x P*. If *A* and *B* do not have compatible dimensions, print an error message and return a *0 x 0* matrix.

gibson/teaching/fall-2014/math445/hw5.1413229782.txt.gz · Last modified: 2014/10/13 12:49 by gibson