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Introduction and Purpose In the lectures and tutorials you have been introduced to a number of probability distributions. You have also learned that modelling any system (such
Curve Fitting: The data is fundamentally either discrete or continuous. In most of the applications, data is sampled, for illustration, The temperature recorded every ho
Run-time or execution-time error: The Run-time, or execution-time, errors are found whenever a script or function is executing. With most of the languages, an illustration of
Nested Functions: We have seen that the loops can be nested, that means that one inside of the other, functions can be nested. The terminology for nested functions is that an
Illustration of Input in a for loop: In this illustration, the loop variable iv iterates through the values 1 through 3, therefore the action is repeated three times. The acti
Working of Editor and debugger: Editor/Debugger, or commands can be typed from Command Window. For illustration, the dbstop command below will set a breakpoint in the fifth li
Sequential Search: A sequential search is completed by looping through the vector element-by-element starting from the beginning, looking for the key. Usually the index of the
Determine sequence weights for the sequences ACTA, ACTT, CGTT, and AGAT in problem 1 by using Thompson, Higgins, and Gibson method a) compute pairwise distances between sequences
Example of Median For the vector [1 4 5 9 12 33], the median is the average of the 5 & 9 in the middle: >> median([1 4 5 9 12 33]) ans = 7
Vectorizing: In most of the cases in MATLAB, loops are not essential. As MATLAB is written specifically to work with the vectors and matrices, most operations can be completed
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