gibson:teaching:fall-2014:math445:hw5
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gibson:teaching:fall-2014:math445:hw5 [2014/10/13 12:47] gibson created |
gibson:teaching:fall-2014:math445:hw5 [2014/10/14 12:39] (current) gibson |
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| Main concept for this homework: the ''for'' loop. | 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. | + | 1. Write a function ''mymean'' that uses a ''for'' loop to compute the mean of the elements of its input vector, according to the formula |
| - | 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 Matlab's built-in ''std'' function on a random vector. | + | \begin{eqnarray*} |
| + | \text{mean}(x) = \frac{1}{N} \sum_{i=1}^N x_i | ||
| + | \end{eqnarray*} | ||
| + | |||
| + | where N is the number of elements in the vector. Test that your code is 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. | ||
| + | \begin{eqnarray*} | ||
| + | \text{std dev}(x) = \sqrt{\frac{1}{N-1} \sum_{i=1}^N (x_i - \bar{x})^2 | ||
| + | \end{eqnarray*} | ||
| + | where $\bar{x}$ is the mean of $x$. 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 in the form | + | 3. Write a script that produces a 10 x 10 multiplication table whose first three lines are |
| <code> | <code> | ||
| Line 24: | Line 34: | ||
| \begin{eqnarray*} | \begin{eqnarray*} | ||
| - | y_i = sum_{j=1^N} A_{ij} x_j | + | y_i = \sum_{j=1}^N A_{ij} x_j |
| \end{eqnarray*} | \end{eqnarray*} | ||
| Line 33: | Line 43: | ||
| \begin{eqnarray*} | \begin{eqnarray*} | ||
| - | C_{ij} = sum_{j=1^N} A_{ik} C_{kj} | + | C_{ij} = \sum_{k=1}^N A_{ik} C_{kj} |
| \end{eqnarray*} | \end{eqnarray*} | ||
| 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. | 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. | ||
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gibson/teaching/fall-2014/math445/hw5.1413229621.txt.gz · Last modified: 2014/10/13 12:47 by gibson
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