I just want to know more about algorithm, that is the steps followed when calc.?
548954
You haven't really asked a question, but ....\n\nAn algorithm is a procedure - think of it as a recipe - for performing a calculation or other process, such as searching for something in a list, or sorting a bunch of numbers.  If you know what programming is about, then you can think of an algorithm as a somewhat abstract version of what the program is doing, or perhaps, the program is just a specific statement of the algorithm.\n\nAlgorithms can be expressed in many ways, including in specific programming languages, or even in English.
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One property of fibonacci series is the following\n Take two consecutive fibonacci numbers and apply to them the euclidean division algorithm.\nThen they will get the maximum number of steps( or the maximum number of divisions).\n So a computer will require more time for division of big numbers if you use euclidean division algorithm.
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x^2 + 2x + 7 Remainder 10\n\ni can add the steps if you don't think i did it by hand
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This is actually elementary math. If you remember the order of operation, it helps. \n\nStep 1: Do the part of the problem in the parenthesis.\n  Example: (4/3)= 1.3333333333 (you get where this is going)\n\nStep 2: Take that answer and multiply it by the named multiplier.\n  Example: 1.33333 * 12= 16\n\nStep 3: Take the result of that transaction and devide it by the named devisor. For this method don't use the fraction way, and don't use a calculator. Do a basic devision problem like you were taught in the 3rd grade using the "bracket."\n  Example: 16/13 = 1  (13 goes into 16 1 time)\n\nStep 4: Subtract the 13 from the 16 and it will give you your remainder.\n  Example: 16/13 = 1   16-13= 3\n\nThe answer when written correctly isn't with a decimal but would look like this- 1 R3.\n\nAlso for a little note for this- Order of operation:\nP (parenthesis)\nE (exponents)\nM (multiply)\nD (devide)\nA (addition)\nS (subtraction)\n\nHope this helps!
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Use the calculator on your computer...
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(m)\n\nTwo important ways to characterize the effectiveness of an algorithm are its space complexity and time complexity. Time complexity of an algorithm concerns determining an expression of the number of steps needed as a function of the problem size. Since the step count measure is somewhat coarse, one does not aim at obtaining an exact step count. Instead, one attempts only to get asymptotic bounds on the step count. Asymptotic analysis makes use of the O (Big Oh) notation. Two other notational constructs used by computer scientists in the analysis of algorithms are Θ (Big Theta) notation and Ω (Big Omega) notation.\nThe performance evaluation of an algorithm is obtained by totaling the number of occurrences of each operation when running the algorithm. The performance of an algorithm is evaluated as a function of the input size n and is to be considered modulo a multiplicative constant.
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There's a very explicit algorithm which explains\nhow to handle number, operators (including left\nor right precedence), functions, etc. on the \nWikipedia site for RPN (see reference #1).\n\nMostly, it's very straight-forward.  If it's an operand\n(ie. a number), then push it on the stack.  If it's an\noperator, then pop off as many operands are needed and\nevaluate.\n\nBut do look at the full algorithm for the details.\n\nOh yeah, for a full-blown implementation, see the source\ncode to the Unix "dc" (desk calculator) program.  The\nSolaris source is at reference #2.
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this question will require calcs using logarithm.\nhence will take time
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hi,\ndo loop is first excecute the task and then its check the condition.\n\ntime 1:\n---------\nd=0, i=20.\n\nd=d+(1.0/i)\nd=0+(1.0/20)\nso new d=0.05\n\nand at the same time,\ni=i/(-2)\nso new i=20/(-2)\nnew i=(-10)\n\nnow the d=0.05\nand i=(-10)\n\nand then its check the condition.\ni<5\n(-10) < 5 is true\nso it wil run the loop again,\n\nso nw come to the 2nd level...\n\nTime 2:\n----------\nd=d+(1.0/i)\nso d=0.05+ (1.0 /(-10)\nnew d =0.05+ (-0.1)\nnew d=0.05-0.1\nd= (-0.05)\n\nand concider abt i,\ni=i/(-2)\ni=(-10)/(-2)\nso new i = (+5)\n\nnow lets checks the condition,\ni < 5\n+5 < 5 is fals, \nso the program s terminated.\n\nso now the value of d= (-0.05)\n\nr u clear?\nthis is a gud egsample for tha do while loop,\nHav fun bro,\ntc.
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When an iterative calculations with predefined conditions are to be done, the need of loop arises.\n\nThe following are the loop constructs...\n\n1. While Loop:\n\nSyntax: \n\nwhile( x < 100 ) {\n     if( x < 0 )\n       break;\n     cout << x << endl;\n     x++;\n   }   \n\n2. for loop\n\nSyntax: \n\nfor( initialization; test-condition; increment ) {\n  statement-list;\n  }\n\n   for( int i = 0; i < 10; i++ ) {\n     cout << "i is " << i << endl;\n   }\n   int j, k;\n   for( j = 0, k = 10;\n        j < k;\n        j++, k-- ) {\n     cout << "j is " << j << " and k is " << k << endl;\n   }\n   for( ; ; ) {\n     // loop forever!\n   }            \n\n3. do \n\nSyntax: \n  do {\n  statement-list;\n  } while( condition );
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Load the Analysis Toolpak add-in and then use this formula, it's shorter:\n\n=A1/GCD(A1, B1)&":"&B1/GCD(A1, B1)
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If you are usinf Windows, go to the Start menu and then click on Run and then enter Calc. It will bring up a calculator.
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Algorithm\n - a step by step description of a specific solution to a known problem.\n\nFor example, there are any number of algorithms (ways) of sorting information.  The bubble-sort algorithm isn't very efficient but is simple.  Binary sort is more efficient but more complex.\n\nBy understanding the way a solution works before even thinking about programming it you can identify the one most appropriate for your situation.  Different algorithms will require more space, more time, or more complexity.  \n\nYou can understand them and their trade-offs as concepts.  Then when you are ready to program the solution (apply the algorithm) you have a very good chance of getting it right.
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basically, think of a function as a machine:\n\ntake this an an example: f(x) = 2x +3\nsee the x in brackets?\n\nif x = 1, then f(1) = 2(1) + 3 = 5\nif x = 2, then f(2) = 2(2) + 3 = 7\nif x = 3, then f(3) = 2(3) + 3 = 9\n\nsee whats happening? the answer DEPENDS on number inputted in the brackets.\n\nso therefore, the definition you quoted "a consistent, predictable, relationship between the independant and dependant variable" is true.
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I just plugged this into my calculator.\n\n[1, 0, 2, 0, 2, 0 | 0\n0, 1, -3, 0, -2, 0 | 0\n0, 0, 0, 1, -1, 0 | 0\n0, 0, 0, 0, 0, 1 | 0\n0, 0, 0, 0, 0, 0 | 1 ]\n\nTake it however you want.
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I'd recommend graphing the function on a calculator (I use a TI-83) and use the 'trace' to find zeros.
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A simple algorithm is to first take all n(n-1)/2 pairs of points. Each pair defines a line, count how many of the remaining points lie on the line. This will be a cubic algorithm in n, the number of points.\n\nA clever algorithm using sorting takes time O( n^2 log n). See the Sources.