% Solution to Review question 1

% Assume variables nBig and nSm are given

% Outer loop to iterate from nBig to nSm
for num=  nBig:-1:nSm 

    % Check num to see if it is prime
      d=2;  % divisor
      % Iterate until first proper divisor is found
      while (mod(num,d) ~= 0);
          d = d + 1;
      end
      if (d == num)
          fprintf('%d is a prime\n',num);
      else
          fprintf('%d\n',num);
      end  

end

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% Solution to Review question 2

%Part A

function seconds = hms2s( h, m, s )
% Post: seconds=number os seconds in h:m:s
% Pre:  h,m,s>=0

seconds = 3600*h+60*m+s;

%Part B

function [h, m, s] = s2hms( seconds )
% Post: seconds is converted to h:m:s format
% Pre:  seconds>=0

h = floor( seconds/3600 );
m = floor( mod( seconds, 3600 )/60 );
s = mod( mod(seconds, 3600), 60 );

% Part C  Command Window entries and output
s  = hms2s( 7, 45, 13 )
s =
      27913
[h, m, s ] = s2hms( 3682 )
h =
    1
m =
    1
s =
   22


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% Solution to Review question 3

function [ volume, surfaceArea ] = myCylinder( ratio );
% Post: Calculate volume and surface area of a randomly generated cylinder
%   where diameter d of cirular end of the cylinder is random in range (0,1)
%   and height of the cylinder is d*ratio
% Pre: ratio>0

d = rand(1,1);    % generate diameter in the range (0, 1)
height = d*ratio;
surfaceArea = 2*0.25*pi*d^2 + pi*d*height;
volume = 0.25*pi*d^2*height;

% On an exam, these formulas would be given.

 

%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% Solution to Review question 4

%Part A

function ave = average(data)
% Post: ave= the average of all values in matrix data
% Pre:  data is at least 1-by-1

[rows,columns] = size(data);
sum = 0;
for i = 1:rows;
    for j = 1:columns;
        sum = sum + data(i,j);
    end
end
ave = sum/(rows*columns);

%Part B

function sd = stdDev(data)
% Post: sd=standard deviation of data (vectorized code)
% Pre:  data is at least 1-by-1

[rows,columns] = size(data);
av = average(data);
data = data - av;
data = data .^ 2;
Sum = sum(sum(data));
sd = Sum/(rows*columns);

%Alternate solution:  nonvectorized function
%function sd = stdDev(data)
% Post: sd=standard deviation of data (nonvectorized code)
% Pre:  data is at least 1-by-1
%
%[rows,columns] = size(data);
%av = average(data);
%sum = 0;
%for i = 1:rows
%   for j = 1:columns
%       data(i,j) = ((data(i,j) - av)^2);
%       Sum = Sum + (data(i,j));
%   end
%end
%sd = Sum/(rows*columns);