Free Essay

Numerical Methods Chapter 2

In:

Submitted By amills1980
Words 2927
Pages 12
CHAPTER 2

2.1 Two possible versions can be developed:

|IF x ( 10 THEN |IF x ( 10 THEN |
|DO |DO |
|x = x – 5 |x = x – 5 |
|IF x < 50 EXIT |IF x < 50 EXIT |
|END DO |END DO |
|ELSE |ELSEIF x < 5 |
|IF x < 5 THEN |x = 5 |
|x = 5 |ELSE |
|ELSE |x = 7.5 |
|x = 7.5 |ENDIF |
|END IF | |
|ENDIF | |

2.2

DO i = i + 1 IF z > 50 EXIT x = x + 5 IF x > 5 THEN y = x ELSE y = 0 ENDIF z = x + y ENDDO

2.3 Note that this algorithm is made simpler by recognizing that concentration cannot by definition be negative. Therefore, the maximum can be initialized as zero at the start of the algorithm.

Step 1: Start Step 2: Initialize sum, count and maximum to zero Step 3: Examine top card. Step 4: If it says “end of data” proceed to step 9; otherwise, proceed to next step. Step 5: Add value from top card to sum. Step 6: Increase count by 1. Step 7: If value is greater than maximum, set maximum to value. Step 7: Discard top card Step 8: Return to Step 3. Step 9: Is the count greater than zero? If yes, proceed to step 10. If no, proceed to step 11. Step 10: Calculate average = sum/count Step 11: End

2.4 Flowchart: [pic]

2.5 Students could implement the subprogram in any number of languages. The following Fortran 90 program is one example. It should be noted that the availability of complex variables in Fortran 90 would allow this subroutine to be made even more concise. However, we did not exploit this feature, in order to make the code more compatible with languages such as Visual BASIC or C.

PROGRAM Rootfind IMPLICIT NONE INTEGER::ier REAL::a, b, c, r1, i1, r2, i2 DATA a,b,c/1.,6.,2./ CALL Roots(a, b, c, ier, r1, i1, r2, i2) IF (ier == 0) THEN PRINT *, r1,i1," i" PRINT *, r2,i2," i" ELSE PRINT *, "No roots" END IF END

SUBROUTINE Roots(a, b, c, ier, r1, i1, r2, i2) IMPLICIT NONE INTEGER::ier REAL::a, b, c, d, r1, i1, r2, i2 r1=0. r2=0. i1=0. i2=0. IF (a == 0.) THEN IF (b /= 0) THEN r1 = -c/b ELSE ier = 1 END IF ELSE d = b**2 - 4.*a*c IF (d >= 0) THEN r1 = (-b + SQRT(d))/(2*a) r2 = (-b - SQRT(d))/(2*a) ELSE r1 = -b/(2*a) r2 = r1 i1 = SQRT(ABS(d))/(2*a) i2 = -i1 END IF END IF END

The answers for the 3 test cases are: (a) (0.3542, (5.646; (b) 0.4; (c) (0.4167 + 1.4696i; (0.4167 ( 1.4696i.

Several features of this subroutine bear mention:
The subroutine does not involve input or output. Rather, information is passed in and out via the arguments. This is often the preferred style, because the I/O is left to the discretion of the programmer within the calling program.
Note that an error code is passed (IER = 1) for the case where no roots are possible.

2.6 The development of the algorithm hinges on recognizing that the series approximation of the cosine can be represented concisely by the summation,

[pic]

where i = the order of the approximation. The following algorithm implements this summation:

Step 1: Start Step 2: Input value to be evaluated x and maximum order n Step 3: Set order (i) equal to one Step 4: Set accumulator for approximation (approx) to zero Step 5: Set accumulator for factorial product (factor) equal to one Step 6: Calculate true value of cos(x) Step 7: If order is greater than n then proceed to step 13 Otherwise, proceed to next step Step 8: Calculate the approximation with the formula [pic] Step 9: Determine the error [pic] Step 10: Increment the order by one Step 11: Determine the factorial for the next iteration [pic] Step 12: Return to step 7 Step 13: End

2.7 (a) Structured flowchart

[pic]

(b) Pseudocode:

SUBROUTINE Coscomp(n,x) i = 1 approx = 0 factor = 1 truth = cos(x) DO IF i > n EXIT approx = approx + (-1)i-1•x2(i-2 / factor error = (true - approx) / true) * 100 DISPLAY i, true, approx, error i = i + 1 factor = factor•(2•i-3)•(2•i-2) END DO END

2.8 Students could implement the subprogram in any number of languages. The following MATLAB M-file is one example. It should be noted that MATLAB allows direct calculation of the factorial through its intrinsic function factorial. However, we did not exploit this feature, in order to make the code more compatible with languages such as Visual BASIC and Fortran.

function coscomp(x,n) i = 1; tru = cos(x); approx = 0; f = 1; fprintf('\n'); fprintf('order true value approximation error\n'); while (1) if i > n, break, end approx = approx + (-1)^(i - 1) * x^(2*i-2) / f; er = (tru - approx) / tru * 100; fprintf('%3d %14.10f %14.10f %12.8f\n',i,tru,approx,er); i = i + 1; f = f*(2*i-3)*(2*i-2); end

Here is a run of the program showing the output that is generated:

>> coscomp(1.25,6)

order true value approximation error 1 0.3153223624 1.0000000000 -217.13576938 2 0.3153223624 0.2187500000 30.62655045 3 0.3153223624 0.3204752604 -1.63416828 4 0.3153223624 0.3151770698 0.04607749 5 0.3153223624 0.3153248988 -0.00080437 6 0.3153223624 0.3153223323 0.00000955

2.9 (a) The following pseudocode provides an algorithm for this problem. Notice that the input of the quizzes and homeworks is done with logical loops that terminate when the user enters a negative grade:

INPUT WQ, WH, WF nq = 0 sumq = 0 DO INPUT quiz (enter negative to signal end of quizzes) IF quiz < 0 EXIT nq = nq + 1 sumq = sumq + quiz END DO AQ = sumq / nq nh = 0 sumh = 0 DO INPUT homework (enter negative to signal end of homeworks) IF homework < 0 EXIT nh = nh + 1 sumh = sumh + homework END DO AH = sumh / nh DISPLAY "Is there a final grade (y or n)" INPUT answer IF answer = "y" THEN INPUT FE AG = (WQ * AQ + WH * AH + WF * FE) / (WQ + WH + WF) ELSE AG = (WQ * AQ + WH * AH) / (WQ + WH) END IF DISPLAY AG END

(b) Students could implement the program in any number of languages. The following VBA code is one example.

Sub Grader() Dim WQ As Double, WH As Double, WF As Double Dim nq As Integer, sumq As Double, AQ As Double Dim nh As Integer, sumh As Double, AH As Double Dim answer As String, FE As Double Dim AG As Double

'enter weights WQ = InputBox("enter quiz weight") WH = InputBox("enter homework weight") WF = InputBox("enter final exam weight") 'enter quiz grades nq = 0 sumq = 0 Do quiz = InputBox("enter negative to signal end of quizzes") If quiz < 0 Then Exit Do nq = nq + 1 sumq = sumq + quiz Loop AQ = sumq / nq 'enter homework grades nh = 0 sumh = 0 Do homework = InputBox("enter negative to signal end of homeworks") If homework < 0 Then Exit Do nh = nh + 1 sumh = sumh + homework Loop AH = sumh / nh 'determine and display the average grade answer = InputBox("Is there a final grade (y or n)") If answer = "y" Then FE = InputBox("final grade:") AG = (WQ * AQ + WH * AH + WF * FE) / (WQ + WH + WF) Else AG = (WQ * AQ + WH * AH) / (WQ + WH) End If MsgBox "Average grade = " & AG End Sub

The results should conform to:

AQ = 437/5 = 87.4 AH = 541/6 = 90.1667

without final [pic]

with final [pic]

2.10 (a) Pseudocode:

IF a > 0 THEN tol = 10–5 x = a/2 DO y = (x + a/x)/2 e = ((y – x)/y( x = y IF e < tol EXIT END DO SquareRoot = x ELSE SquareRoot = 0 END IF

(b) Students could implement the function in any number of languages. The following VBA and MATLAB codes are two possible options.

|VBA Function Procedure |MATLAB M-File |
|Option Explicit |function s = SquareRoot(a) |
|Function SquareRoot(a) |if a > 0 |
|Dim x As Double, y As Double |tol = 0.00001; |
|Dim e As Double, tol As Double |x = a / 2; |
|If a > 0 Then |while(1) |
|tol = 0.00001 |y = (x + a / x) / 2; |
|x = a / 2 |e = abs((y - x) / y); |
|Do |x = y; |
|y = (x + a / x) / 2 |if e < tol, break, end |
|e = Abs((y - x) / y) |end |
|x = y |s = x; |
|If e < tol Then Exit Do |else |
|Loop |s = 0; |
|SquareRoot = x |end |
|Else | |
|SquareRoot = 0 | |
|End If | |
|End Function | |

2.11 A MATLAB M-file can be written to solve this problem as

function futureworth(P, i, n) nn = 0:n; F = P*(1+i).^nn; y = [nn;F]; fprintf('\n year future worth\n'); fprintf('%5d %14.2f\n',y);

This function can be used to evaluate the test case,

>> futureworth(100000,0.06,5)

year future worth 0 100000.00 1 106000.00 2 112360.00 3 119101.60 4 126247.70 5 133822.56

2.12 A MATLAB M-file can be written to solve this problem as

function annualpayment(P, i, n) nn = 1:n; A = P*i*(1+i).^nn./((1+i).^nn-1); y = [nn;A]; fprintf('\n year annual payment\n'); fprintf('%5d %14.2f\n',y);

This function can be used to evaluate the test case,

>> annualpayment(55000,0.066,5)

year annual payment 1 58630.00 2 30251.49 3 20804.86 4 16091.17 5 13270.64

2.13 Students could implement the function in any number of languages. The following VBA and MATLAB codes are two possible options.

|VBA Function Procedure |MATLAB M-File |
|Option Explicit |function Ta = avgtemp(Tm,Tp,ts,te) |
|Function avgtemp(Tm, Tp, ts, te) |w = 2*pi/365; |
|Dim pi As Double, w As Double |t = ts:te; |
|Dim Temp As Double, t As Double |T = Tm + (Tp-Tm)*cos(w*(t-205)); |
|Dim sum As Double, i As Integer |Ta = mean(T); |
|Dim n As Integer | |
|pi = 4 * Atn(1) | |
|w = 2 * pi / 365 | |
|sum = 0 | |
|n = 0 | |
|t = ts | |
|For i = ts To te | |
|Temp = Tm+(Tp-Tm)*Cos(w*(t-205)) | |
|sum = sum + Temp | |
|n = n + 1 | |
|t = t + 1 | |
|Next i | |
|avgtemp = sum / n | |
|End Function | |

The function can be used to evaluate the test cases. The following show the results for MATLAB,

>> avgtemp(22.1,28.3,0,59)

ans = 16.2148

>> avgtemp(10.7,22.9,180,242)

ans = 22.2491

2.14 The programs are student specific and will be similar to the codes developed for VBA, MATLAB and Fortran as outlined in sections 2.4, 2.5 and 2.6. The numerical results for the different time steps are tabulated below along with an estimate of the absolute value of the true relative error at t = 12 s:

|Step |v(12) |((t( (%) |
|2 |49.96 |5.2 |
|1 |48.70 |2.6 |
|0.5 |48.09 |1.3 |

The general conclusion is that the error is halved when the step size is halved.

2.15 Students could implement the subprogram in any number of languages. The following Fortran 90 and VBA/Excel programs are two examples based on the algorithm outlined in Fig. P2.15.

|Fortran 90 |VBA/Excel |
|Subroutine BubbleFor(n, b) |Option Explicit |
| | |
|Implicit None |Sub Bubble(n, b) |
| | |
|!sorts an array in ascending |'sorts an array in ascending |
|!order using the bubble sort |'order using the bubble sort |
| | |
|Integer(4)::m, i, n |Dim m As Integer |
|Logical::switch |Dim i As Integer |
|Real::a(n),b(n),dum |Dim switch As Boolean |
| |Dim dum As Double |
|m = n - 1 | |
|Do |m = n - 1 |
|switch = .False. |Do |
|Do i = 1, m |switch = False |
|If (b(i) > b(i + 1)) Then |For i = 1 To m |
|dum = b(i) |If b(i) > b(i + 1) Then |
|b(i) = b(i + 1) |dum = b(i) |
|b(i + 1) = dum |b(i) = b(i + 1) |
|switch = .True. |b(i + 1) = dum |
|End If |switch = True |
|End Do |End If |
|If (switch == .False.) Exit |Next i |
|m = m - 1 |If switch = False Then Exit Do |
|End Do |m = m - 1 |
| |Loop |
|End | |
| |End Sub |

For MATLAB, the following M-file implements the bubble sort following the algorithm outlined in Fig. P2.15:

function y = Bubble(x) n = length(x); m = n - 1; b = x; while(1) s = 0; for i = 1:m if b(i) > b(i + 1) dum = b(i); b(i) = b(i + 1); b(i + 1) = dum; s = 1; end end if s == 0, break, end m = m - 1; end y = b;

Notice how the length function allows us to omit the length of the vector in the function argument. Here is an example MATLAB session that invokes the function to sort a vector:

>> a=[3 4 2 8 5 7]; >> Bubble(a)

ans = 2 3 4 5 7 8

2.16 Here is a flowchart for the algorithm:

[pic]

Students could implement the function in any number of languages. The following VBA and MATLAB codes are two possible options.

|VBA Function Procedure |MATLAB M-File |
|Option Explicit |function Vol = tankvolume(R, d) |
|Function Vol(R, d) |if d < R |
|Dim V1 As Double, V2 As Double |Vol = pi * d ^ 3 / 3; |
|Dim pi As Double |elseif d 0 th(i) = atan(y(i) / x(i)) + pi; elseif y(i) < 0 th(i) = atan(y(i) / x(i)) - pi; else th(i) = pi; end else if y(i) > 0 th(i) = pi / 2; elseif y(i) < 0 th(i) = -pi / 2; else th(i) = 0; end end th(i) = th(i) * 180 / pi; end ou=[x;y;r;th]; fprintf('\n x y radius angle\n'); fprintf('%8.2f %8.2f %10.4f %10.4f\n',ou);

This function can be used to evaluate the test cases.

>> x=[1 1 1 -1 -1 -1 0 0 0]; >> y=[1 -1 0 1 -1 0 1 -1 0]; >> polar(x,y)

x y radius angle 1.00 1.00 1.4142 45.0000 1.00 -1.00 1.4142 -45.0000 1.00 0.00 1.0000 0.0000 -1.00 1.00 1.4142 135.0000 -1.00 -1.00 1.4142 -135.0000 -1.00 0.00 1.0000 180.0000 0.00 1.00 1.0000 90.0000 0.00 -1.00 1.0000 -90.0000 0.00 0.00 0.0000 0.0000

2.18 Students could implement the function in any number of languages. The following VBA and MATLAB codes are two possible options.

|VBA Function Procedure |MATLAB M-File |
|Function grade(s) |function grade = lettergrade(score) |
|If s >= 90 Then |if score >= 90 |
|grade = "A" |grade = 'A'; |
|ElseIf s >= 80 Then |elseif score >= 80 |
|grade = "B" |grade = 'B'; |
|ElseIf s >= 70 Then |elseif score >= 70 |
|grade = "C" |grade = 'C'; |
|ElseIf s >= 60 Then |elseif score >= 60 |
|grade = "D" |grade = 'D'; |
|Else |else |
|grade = "F" |grade = 'F'; |
|End If |end |
|End Function | |

2.19 Students could implement the functions in any number of languages. The following VBA and MATLAB codes are two possible options.

|VBA Function Procedure |MATLAB M-File |
|(a) Factorial | |
|Function factor(n) |function fout = factor(n) |
|Dim x As Long, i As Integer |x = 1; |
|x = 1 |for i = 1:n |
|For i = 1 To n |x = x * i; |
|x = x * i |end |
|Next i |fout = x; |
|factor = x | |
|End Function | |
| | |
|(b) Minimum | |
|Function min(x, n) |function xm = xmin(x) |
|Dim i As Integer |n = length(x); |
|min = x(1) |xm = x(1); |
|For i = 2 To n |for i = 2:n |
|If x(i) < min Then min = x(i) |if x(i) < xm, xm = x(i); end |
|Next i |end |
|End Function | |
| | |
|(c) Average | |
|Function mean(x, n) |function xm = xmean(x) |
|Dim sum As Double |n = length(x); |
|Dim i As Integer |s = x(1); |
|sum = x(1) |for i = 2:n |
|For i = 2 To n |s = s + x(i); |
|sum = sum + x(i) |end |
|Next i |xm = s / n; |
|mean = sum / n | |
|End Function | |

2.20 Students could implement the functions in any number of languages. The following VBA and MATLAB codes are two possible options.

|VBA Function Procedure |MATLAB M-File |
|(a) Square root sum of squares | |
|Function SSS(x, n, m) |function s = SSS(x) |
|Dim i As Integer, j As Integer |[n,m] = size(x); |
|SSS = 0 |s = 0; |
|For i = 1 To n |for i = 1:n |
|For j = 1 To m |for j = 1:m |
|SSS = SSS + x(i, j) ^ 2 |s = s + x(i, j) ^ 2; |
|Next j |end |
|Next i |end |
|SSS = Sqr(SSS) |s = sqrt(s); |
|End Function | |
| | |
|(b) Normalization | |
|Sub normal(x, n, m, y) |function y = normal(x) |
|Dim i As Integer, j As Integer |[n,m] = size(x); |
|Dim max As Double |for i = 1:n |
|For i = 1 To n |mx = abs(x(i, 1)); |
|max = Abs(x(i, 1)) |for j = 2:m |
|For j = 2 To m |if abs(x(i, j)) > mx |
|If Abs(x(i, j)) > max Then |mx = x(i, j); |
|max = x(i, j) |end |
|End If |end |
|Next j |for j = 1:m |
|For j = 1 To m |y(i, j) = x(i, j) / mx; |
|y(i, j) = x(i, j) / max |end |
|Next j |end |
|Next i | |
|End Sub |Alternate version: |
| | |
| |function y = normal(x) |
| |n = size(x); |
| |for i = 1:n |
| |y(i,:) = x(i,:)/max(x(i,:)); |
| |end |

Similar Documents

Free Essay

Numerical Recipes in C

...Sample page from NUMERICAL RECIPES IN C: THE ART OF SCIENTIFIC COMPUTING (ISBN 0-521-43108-5) Copyright (C) 1988-1992 by Cambridge University Press. Programs Copyright (C) 1988-1992 by Numerical Recipes Software. Permission is granted for internet users to make one paper copy for their own personal use. Further reproduction, or any copying of machinereadable files (including this one) to any server computer, is strictly prohibited. To order Numerical Recipes books or CDROMs, visit website http://www.nr.com or call 1-800-872-7423 (North America only), or send email to directcustserv@cambridge.org (outside North America). Numerical Recipes in C The Art of Scientific Computing Cambridge New York Port Chester Melbourne Sydney EXXON Research and Engineering Company Harvard-Smithsonian Center for Astrophysics Department of Physics, Cornell University CAMBRIDGE UNIVERSITY PRESS William T. Vetterling Saul A. Teukolsky Brian P. Flannery Second Edition William H. Press Polaroid Corporation Published by the Press Syndicate of the University of Cambridge The Pitt Building, Trumpington Street, Cambridge CB2 1RP 40 West 20th Street, New York, NY 10011-4211, USA 477 Williamstown Road, Port Melbourne, VIC, 3207, Australia Copyright c Cambridge University Press 1988, 1992 except for §13.10 and Appendix B, which are placed into the public domain, and except for all other computer programs and procedures, which are Copyright c Numerical Recipes Software 1987, 1988, 1992...

Words: 24819 - Pages: 100

Premium Essay

Capstone

...Lovely Professional University, Punjab Course Code MGT519 Course Category Course Title OPERATIONS MANAGEMENT Courses with numerical and conceptual focus Course Planner 16031::Gurpreet Kaur Lectures 3.0 Tutorials Practicals Credits 1.0 0.0 4.0 TextBooks Sr No T-1 Title Operations Management Reference Books Sr No R-1 R-2 Other Reading Sr No OR-1 OR-2 OR-3 OR-4 OR-5 OR-6 OR-7 OR-8 OR-9 OR-10 OR-11 OR-12 Journals articles as Compulsary reading (specific articles, complete reference) The four things that a service Business must get right HBR Article , Bang & Olufsen Design Driven Innovation : HBR , Smart Product Design : HBR , Mishina, Kazuhiro. Toyota Motor Manufacturing, U.S.A., Inc. HBS Case No. 9-693-019. Harvard Business School Publishing, Boston, 1995. , Hammond, Janice H. Barilla SpA (A). HBS Case No. 9-694-046. Harvard Business School Publishing, Boston, 1994. , Latour, Almar. Nokia Handles Supply Shock with Aplomb as Ericsson of Sweden Gets Burned. The Wall Street Journal. Dow Jones & Company, Inc., 2001. , National Cranberry Cooperative HBS #688122. From Case Map , John Crane UK Ltd Case : The CAD CAM Link . HBS #691021,24p , To Move or not to Move .Case of Cathay Pacific Airways . University of Hong Kong HBS #HKU003,22p , Note on Quality: The Views of Deming, Juran, and Crosby HBS .687011 , Process Control at Polaroid , HBS, #693047 , LL Bean Item Forecasting and Inventory Management HBS, #893003, 5p , Johson Control Automotive Systems , HBS,#69308623p , Title Operations...

Words: 3895 - Pages: 16

Free Essay

Scaling of Symmetric Rank One Method in Solving Unconstrained Optimization Problem

...CHAPTER 1 INTRODUCTION Background Of the Study In mathematics, optimization problem is a problem where it consists of maximizing or minimizing a real function by systematically choose an input values within an allowed set and compute the value of the function. An additional, it also means solve the problem so that we can the goal as quickly as possible without wasting a lot of resources. Optimization also can be deviating from a target by the smallest possible margin. Generally, a large area of applied mathematics is comprised by the optimization theory and techniques to other formulations. In the simple case, optimization is like finding a good value or a best available value of some problems given a defined domain, including a many of different types of objectives functions and different types of domains. In vector calculus, the gradient of a scalar field is a vector field that points in the direction of the scalar field, and whose the magnitude is that rate of increase. The variation in space of any quantity can be represented by a slope in simple terms. The gradient is like represents the steepness and the direction of the slope. The gradient or gradient of a scalar function f〖:R〗^n→R^1 is denoted by ∇f or ∇ ⃗f where ∇ denotes the vector of the differential operator. Hessian matrix was developed in the 19th century by the German mathematician Ludwig Otto Hesse and this matrix is later named after him. Hessian matrix is the matrix of second derivatives...

Words: 2895 - Pages: 12

Free Essay

Linear Progr

...362 Chapter 9. Root Finding and Nonlinear Sets of Equations } a=b; fa=fb; if (fabs(d) > tol1) b += d; else b += SIGN(tol1,xm); fb=(*func)(b); Move last best guess to a. Evaluate new trial root. Sample page from NUMERICAL RECIPES IN C: THE ART OF SCIENTIFIC COMPUTING (ISBN 0-521-43108-5) Copyright (C) 1988-1992 by Cambridge University Press. Programs Copyright (C) 1988-1992 by Numerical Recipes Software. Permission is granted for internet users to make one paper copy for their own personal use. Further reproduction, or any copying of machinereadable files (including this one) to any server computer, is strictly prohibited. To order Numerical Recipes books or CDROMs, visit website http://www.nr.com or call 1-800-872-7423 (North America only), or send email to directcustserv@cambridge.org (outside North America). } nrerror("Maximum number of iterations exceeded in zbrent"); return 0.0; Never get here. } CITED REFERENCES AND FURTHER READING: Brent, R.P. 1973, Algorithms for Minimization without Derivatives (Englewood Cliffs, NJ: PrenticeHall), Chapters 3, 4. [1] Forsythe, G.E., Malcolm, M.A., and Moler, C.B. 1977, Computer Methods for Mathematical Computations (Englewood Cliffs, NJ: Prentice-Hall), §7.2. 9.4 Newton-Raphson Method Using Derivative Perhaps the most celebrated of all one-dimensional root-finding routines is Newton’s method, also called the Newton-Raphson method. This method is distinguished from the methods of previous sections by the fact that...

Words: 3328 - Pages: 14

Premium Essay

Management Accounting

...and budgetary control mechanism Activity based costing, Responsibility Accounting Target costing Objective Objective of this course is to help student understand: 1. The essence of management accounting-effective use of the accounting information for planning, control and business decision making. 2. To use cost accounting as a managerial tool for business strategy and implementation. 3. To understand analyse the costing tools and their business application for enhancing revenue and profitability of a firm,. 4. To analyse various aspects of costing such as, marginal costing, absorption costing, allocation of costs, standard costing and variance analysis, activity based costing, target costing etc. 5. To understand the process of decision making, planning and budgeting in a business organisation. Pedagogy Lectures Discussions on case studies Term Projects and presentations Discussion and presentation on published research papers on related topics. Text book: Management Accounting: Paresh Shah, OXFORD UNIVERSITY Press, Edition, Eighth impression 2012. Reference Books: 1. Managerial Accounting, by James Jiambalvo, third edition, pub. Wiley 2. Management Accounting, M Y Khan & P K Jain, Pub. Tata McGraw-Hill 3. Managerial Accounting, Ronald W Hilton/ G Ramesh Pub.Tata McGraw Evaluation and Weightage (Total 100 Marks) Class Quiz : 10 Marks Class Assignment...

Words: 601 - Pages: 3

Free Essay

Cholesky Decomposition

...2.9 Cholesky Decomposition 89 compared to N 2 for Levinson’s method. These methods are too complicated to include here. Papers by Bunch [6] and de Hoog [7] will give entry to the literature. CITED REFERENCES AND FURTHER READING: Golub, G.H., and Van Loan, C.F. 1989, Matrix Computations, 2nd ed. (Baltimore: Johns Hopkins University Press), Chapter 5 [also treats some other special forms]. Forsythe, G.E., and Moler, C.B. 1967, Computer Solution of Linear Algebraic Systems (Englewood Cliffs, NJ: Prentice-Hall), §19. [1] Westlake, J.R. 1968, A Handbook of Numerical Matrix Inversion and Solution of Linear Equations (New York: Wiley). [2] von Mises, R. 1964, Mathematical Theory of Probability and Statistics (New York: Academic Press), pp. 394ff. [3] Levinson, N., Appendix B of N. Wiener, 1949, Extrapolation, Interpolation and Smoothing of Stationary Time Series (New York: Wiley). [4] Robinson, E.A., and Treitel, S. 1980, Geophysical Signal Analysis (Englewood Cliffs, NJ: PrenticeHall), pp. 163ff. [5] Bunch, J.R. 1985, SIAM Journal on Scientific and Statistical Computing, vol. 6, pp. 349–364. [6] de Hoog, F. 1987, Linear Algebra and Its Applications, vol. 88/89, pp. 123–138. [7] Sample page from NUMERICAL RECIPES IN FORTRAN 77: THE ART OF SCIENTIFIC COMPUTING (ISBN 0-521-43064-X) Copyright (C) 1986-1992 by Cambridge University Press. Programs Copyright (C) 1986-1992 by Numerical Recipes Software. Permission is granted for internet users to make one paper copy for their own personal...

Words: 1638 - Pages: 7

Premium Essay

Doc Remove Delibitablement

...2,5 | 32 | Advanced Maintenance | 2,5 | 32 | Numerical Analysis | 2,5 | 32 | Operations Research | 2,5 | 32 | Servo (Tuto) | 2,5 | 32 | Servo (Courses) | 2,5 | 32 | Algorithm (Data Structure) | 2,5 | 32 | Algorithm oriented object (Tuto, C++ Language) | 3 | 40 | Operating System (Theories and Fundamental) | 2,5 | 32 | WAN (courses + Tuto) | 4,5 | 60 | Method of Analysis 1 | 3 | 40 | Programming Workshop C | 2,5 | 32 | Software Engineering workshop (Access, VB) | 3 | 40 | Management Workshop for Science Engineer | 2 | 24 | Entrepreneurship | 1,5 | 20 |   |   |   | TOTAL | 63,5 | 832 | ------------------------------------------------- OBJECT ORIENTED ALGORITHM ------------------------------------------------- (Hands-On in Language C + +) CHAPTER I: GENERAL ON CLASS I. Notion of class • Generality of P.O.O • Incompatibility C / C + + II. Property of the member functions • Defaults • Member functions in-line • Transmission of object as argument III. Object assignment IV. Object Constructors and Destructors V. Object initialization VI. The copy constructor VII. Tables to Objects CHAPTER II: THE OPERATOR SURDEFINITION I. The mechanism surdéfinition II. The possibilities and limits of surdéfinition CHAIPTRE III: FUNCTIONS FRIENDS I. Principle of Friendship II. Independent functions of a class friends III. Other situations of Friendship CHAPTER IV: THE LEGACY I. Definition and implementation ...

Words: 2262 - Pages: 10

Free Essay

Management

...DIFFERENTIAL PROTECTION SCHEME FOR POWER TRANSFORMER iii CONTENTS Page no. * ACKNOWLEDGEMENT (i) * CERTIFICATE (ii) * CONTENTS (iii) * ABSTRACT (iv) CHAPTER 1: 1.1 INTRODUCTION. 1.2 MOTIVATION FOR UNDERTAKING THE PROJECT. 1.3 AIMS AND OBJECTIVES OF THE PROJECT. CHAPTER 2: REVIEW OF LITERATURE. CHAPTER 3: IMPLEMENTATION OF THE PROJECT. CHAPTER 4: DATA COLLECTION AND ANALYSIS OF THE RESULT. CHAPTER 5: 5.1 DISCUSSION OF THE RESULT AND CONCLUSION. 5.2 DISCUSSION OF THE RESULT AND CONCLUSION. REFERENC iv ABSTRACT The power transformer is an essential component of electrical power system that needs continuous monitoring and effective protection scheme. As, it is very...

Words: 2833 - Pages: 12

Free Essay

Pdf, Docx

...Introduction to Statistics Statistical Problems 1. A pharmaceutical Co. wants to know if a new drug is superior to already existing drugs, or possible side effects. 2. How fuel efficient a certain car model is? 3. Is there any relationship between your GPA and employment opportunities? 4. If you answer all questions on a (T, F) (or multiple choice) examination completely randomly, what are your chances of passing? 5. What is the effect of package designs on sales? 6. ………………….. Question??? 1. What is Statistics? 2. Why we study Statistics? Larson & Farber, Elementary Statistics: Picturing the World, 3e 2 STA 13- SYLLABUS Instructor Phone: MsC. Pham Thanh Hieu mobile:0917.522.383, email: hieuphamthanh@gmail.com Goals of  To learn how to interpret statistical summaries appearing the course in journals, newspaper reports, internet, television …..and many real-world problems.  To learn about the concepts of probability and probabilistic reasoning  Understand variability and sampling distributions  To learn how to interpret and analyze data arising in your own work (coursework and research) STA 13- SYLLABUS Grading: - One Midterms : 30% total, multiple choice exams, closed book exam, one sheet with handwritten notes (no larger than 9 ½ x 11, two sided) is allowed - Final Exam : 50% (multiple choice + short answer exam) comprehensive; closed book exam, two sheets with handwritten notes (no larger than 9 ½ x 11, two...

Words: 2522 - Pages: 11

Premium Essay

Geospatial Science

...qxd 1/30/2006 12:17 PM Page 35 CHAPTER 3 Data Collection in Geography Overview Learning Objectives: • • • What is the distinction between primary and secondary data sources? What are the five major types of data collection in geography? What are some of the ways geographers and others have made a distinction between quantitative and qualitative methods, and how do they relate to scientific and humanistic approaches in geography? I n the previous chapter, we explained that the empirical part of scientific research involves systematically observing cases in order to record measurements of variables that reflect properties of those cases. Researchers analyze the resulting set of data (usually numbers) graphically, verbally, and mathematically in order to learn something about the properties of the cases. Data collection efforts do not generally go on continuously but are grouped into periods of activity focused on particular research issues or questions. Such a focused period of data collection and analysis is a study (in Chapter 7, we learn that there are two major categories of scientific studies, experimental and nonexperimental). In this chapter, we introduce some basic characteristics of data collection in geography, including the distinction between primary and secondary data sources, the five major types of data collection, and the distinction between quantitative and qualitative methods. 35 03-Montello-4862.qxd 1/30/2006 ...

Words: 3668 - Pages: 15

Premium Essay

Double Pipe Heat Exchanger

...5.4 Boundary conditions given in Problem setup in ANSYS Workbench Fluent TABLE 5.5 Boundary Conditions S. No Boundary type Annulus Pipe Inside Pipe 1 Mass flow rate at Inlets 0.134 kg/s 0.134 to 0.267 kg/s 2 Temperatures 333 K 300 K 3 Constant heat flux at pipe wall (Insulation) 0 W/m2 --- 5.8 Method of Solution The CFD method follows the use of commercial software ANSYS FLUENT 15.0 to solve the problem. The specified solver in FLUENT uses a pressure correction based iterative SIMPLE algorithm with 2nd order upwind scheme for discretizing the convective transport terms. The convergence criteria for dependent variables are specified as 0.001. The default values of under-relaxation factors are used in the simulation work. In the present analysis, the analytical values of heat transfer coefficients are calculated. The heat transfer coefficients are also obtained using CFD methods and compared with analytical values. Fig. 5.5 Solution methods in ANSYS Workbench Fluent Fig. 5.6 Initialization of Solution in ANSYS Workbench Fluent After determining the important features of the problem following procedure is followed for solving the...

Words: 7433 - Pages: 30

Free Essay

134 Afe Weekly Study Plan

... | | | |Weeks 1-2 |Introduction to Statistics|Business Statistics (BS) (Selvanathan |Module lecture recordings & lecture |Learning Statistics and Excel in |Introduce yourself to | | | |and Data Collection |et al): Chapter 1, Chapter 2 |workbook (A1, A2, A3, A4) |Tandem (LSET), Chapter 1: |the class | | |2 Mar – 15 Mar | | | |Introduction to Microsoft EXCEL & | | | | | |Video recordings: |Set up your account to the APLIA site|Chapter 1 (BS): Appendix 1.A | | | | | |A1 |so you can access the online practice| | | | | | ...

Words: 729 - Pages: 3

Free Essay

Biology

...Centre For Foundation Studies Department of Sciences and Engineering Content 1.1 What is Statistics? 1.2 Population Versus Sample 1.3 Basic Terms 1.4 Types of Variables FHMM1214 Mathematics for Social Science Chapter 1 Introduction of Statistics 1st Meaning of Statistics 1.1 What is Statistics ? The word ‘statistics’ has 2 meanings. 1. Statistics refers to numerical facts.     The age of a student. The number of students enrolled in UTAR. The income of a family. The percentage of passes in a statistics class. 1 2nd Meaning of Statistics 2. Statistics refers to the field or discipline of study. Statistics is a group of methods used to collect, analyze, present, and interpret data and to make decisions. 1.2 Population Versus Sample Population Versus Sample Population and Sample Population or Target Population Consists of all elements (individuals, items, or objects) whose characteristics are being studied. Sample A portion of the population selected for study. Illustration 2 Definition 1.3 Basic Terms Element or Member An element or member of a sample or population is a specific subject or object (e.g. a person, firm, item, state, or country) about which the information is collected. Variable A variable is a characteristics under study that assumes different value for different elements. Definition Observation or Measurement The value of a variable for an element is called an observation measurement. Data Set A data...

Words: 462 - Pages: 2

Premium Essay

Guideline

...1. Preparation and submission guide 1.1How many copies to submit? Two copies (one hard copy and one soft copy in rewriteable DVD) of report should be submitted to the supervisor, one copy to the program office and another duplicate copy should be treasured by the student for future reference and for defense preparation. So, at least three copies of report should be printed. 1.2 Binding of report: The “Book binding” method should be preferred. 1.3 Submission date: Usually there would be a predetermined submission date from the authority. You should submit the case on or before that particular stipulated date. Please note: I can't extend the date of submission. It is strictly in the discretion of the authority that controls the BBA program. 1.4 Paper quality: 80 gram paper (minimum) 2. Overall alignment of the report:  Title Fly page: This is the front page of the report. This page should only contain the title of the work and nothing else. Artistic presentation would be appreciated here.  Title Page: This phase should contain the title of the work, details of submitted by / prepared by / supervised and details of submitted to / prepared for / supervisor. Name of the university, department name, and Faculty name may be pointed out here. Extra care should be taken to correctly mention the ID of the student and the name along with the designation of the supervisor.  Declaration of originality: It should be declared by the student that the work / study is a original...

Words: 1488 - Pages: 6

Premium Essay

Edfdfde

...Part I (Chapters 1 – 11) MBA 611 STATISTICS AND QUANTITATIVE METHODS Part I. A. Review of Basic Statistics (Chapters 1-11) Introduction (Chapter 1) Uncertainty: Decisions are often based on incomplete information from uncertain events. We use statistical methods and statistical analysis to make decisions in uncertain environment. Population: Sample: A population is the complete set of all items in which an investigator is interested. A sample is a subset of population values. & Example: Population - High school students - Households in the U.S. Sample - A sample of 30 students - A Gallup poll of 1,000 consumers - Nielson Survey of TV rating Random Sample: A random sample of n data values is one selected from the population in such a way that every different sample of size n has an equal chance of selection. & Example: Random Selection - Lotto numbers - Random numbers Random Variable: A variable takes different possible values for a given subject of study. Numerical Variable: A numerical variable takes some countable finite numbers or infinite numbers. Categorical Variable: A categorical variable takes values that belong to groups or categories. Data: Data are measured values of the variable. There are two types of data: quantitative data and qualitative data. 1 Part I (Chapters 1 – 11) Quantitative Data: Qualitative Data: & Example: 1. 2. 3. 3. 4. 5. 6. 7. 8. Statistics: Quantitative data are data measured on a numerical scale. Qualitative data are non-numerical...

Words: 3688 - Pages: 15