MCQ Bank

Subjects
All Subjects 56097 ACC311
Fundamentals of Auditing
F:210
210 ACC31Q
F:97
97 ACC501
Business Finance
F:248
248 ACC707
F:33
33 BIF101
Introduction to Bioinformatics
F:37
37 BIF401
Bioinformatics I
F:27
27 BIF401P
Bioinformatics I (Practical)
F:53
53 BIF501
Bioinformatics II
F:63
63 BIF501P
Bioinformatics II (Practical)
F:49
49 BIF601
Bioinformatics Computing I
F:25
25 BIF601P
Bioinformatics Computing I (Practical)
F:35
35 BIF602
Bioinformatics Computing II
F:3
3 BIF604
Special Topics in Bioinformatics
F:67
67 BIO101
Basic I-Biology
F:17
17 BIO102
Basic II-Chemistry
F:38
38 BIO201
M:30
30 BIO203
M:42
42 BIO303
M:29
29 BIO401
Biostatistics
F:24
24 BIO502
Genomics
F:20
20 BIO503
Biological Physics
M:30 F:48
78 BIO504P
Biochemistry I (Practical)
F:23
23 BIO504T
Biochemistry I (Theory)
F:12
12 BIO505P
Essentials of Genetics (Practical)
F:71
71 BIO505T
Essentials of Genetics (Theory)
F:11
11 BIO506P
Biochemistry II (Practical)
F:35
35 BIO506T
Biochemistry II (Theory)
F:16
16 BIO5101
Introduction to Biotechnology
F:25
25 BIO5105
Cell Biology
F:18
18 BIO601
Proteomics
F:20
20 BIO732
Gene Manipulation and Genetic Engineering
F:49
49 BNK601
Banking Laws & Practices
F:129
129 BNK603
Consumer Banking
F:115
115 BNK610
Islamic Banking Practices
F:69
69 BNK611
Economic Ideology in Islam
F:102
102 BNK612
Financial Jurisprudence in Islam
F:29
29 BNK613
Islamic Ethics in Business
F:23
23 BT101
Ecology, Biodiversity & Evolution-I
F:80
80 BT102
M:31 F:53
84 BT201
F:246
246 BT301
F:30
30 BT302
Immunology
M:55 F:35
90 BT401
Genetic Resources & Conservation
F:163
163 BT402
F:37
37 BT403
F:43
43 BT404
M:9
9 BT405
Nano Biotechnology
F:41
41 BT406
Research Methodology & Skill Enhancement
F:106
106 BT501
Health Biotechnology
F:141
141 BT503
Environment Biotechnology
F:74
74 BT504
Genomics and Proteomics
F:67
67 BT505
Biosensors
F:68
68 BT511P
Introduction to Biotechnology (Practical)
F:25
25 BT511T
F:27
27 BT512P
Microbial Biotechnology (Practical)
F:74
74 BT512T
Microbial Biotechnology (Theory)
F:170
170 BT513P
Principles of Biochemical Engineering (Practical)
F:71
71 BT513T
Principles of Biochemical Engineering (Theory)
F:37
37 BT601
Virology
F:69
69 BT603
F:21
21 BT604
F:19
19 BT605
Biosafety & Bioethics
F:58
58 BT611P
Food Biotechnology (Practical)
F:52
52 BT611T
Food Biotechnology (Theory)
F:55
55 BT612P
Fermentation Technology (Practical)
F:31
31 BT612T
Fermentation Technology (Theory)
F:12
12 BT613T
Agriculture Biotechnology (Theory)
F:28
28 BT614P
Industrial Biotechnology (Practical)
F:28
28 BT614T
Industrial Biotechnology (Theory)
F:37
37 CHE201
Physical Chemistry
F:77
77 CHE301
M:28
28 CS001
F:58
58 CS101
Introduction to Computing
F:751
751 CS201
Introduction to Programming
M:97 F:247
344 CS201P
Introduction to Programming (Practical)
F:200
200 CS202
F:192
192 CS204
F:77
77 CS205
Information Security
F:87
87 CS206
F:57
57 CS301
Data Structures
F:141
141 CS301P
Data Structures (Practical)
F:63
63 CS302
Digital Logic Design
F:192
192 CS302P
F:64
64 CS304
Object Oriented Programming
F:89
89 CS304P
Object Oriented Programming (Practical)
F:147
147 CS306
Introduction to Python
F:75
75 CS306P
Introduction to Python (Practical)
F:88
88 CS311
Introduction to Web Services Development
F:132
132 CS312
F:47
47 CS314
Introduction to Cellular Networks
F:84
84 CS315
F:57
57 CS401
F:117
117 CS401P
F:94
94 CS402
M:67 F:140
207 CS403
Database Management Systems
F:162
162 CS403P
Database Management Systems (Practical)
F:120
120 CS405
Database Programming using Oracle 11g
F:70
70 CS406
F:28
28 CS407
Routing and Switching
F:70
70 CS408
Human Computer Interaction
M:94 F:76
170 CS409
Introduction to Database Administration
F:43
43 CS409P
F:59
59 CS411
Visual Programming
F:100
100 CS420
Web Development for Portable Devices
F:106
106 CS431
Wireless Communication
F:43
43 CS432
F:80
80 CS435
Cloud Computing
F:46
46 CS441
F:73
73 CS442
Introduction to Data Science
F:29
29 CS501
F:120
120 CS502
Fundamentals of Algorithms
F:156
156 CS504
Software Engineering - I
F:179
179 CS505
F:49
49 CS505P
F:96
96 CS506
Web Design and Development
F:196
196 CS507
Information Systems
M:87 F:165
252 CS508
F:227
227 CS510
F:63
63 CS513
Advanced Data Analytics and Business Intelligence
F:128
128 CS514
F:23
23 CS521
F:26
26 CS525
F:25
25 CS601
Data Communication
F:137
137 CS602
Computer Graphics
F:105
105 CS603
F:62
62 CS603P
F:54
54 CS604
F:177
177 CS604P
F:86
86 CS605
F:82
82 CS606
F:194
194 CS607
Artificial Intelligence
F:134
134 CS607P
Artificial Intelligence (Practical)
F:108
108 CS608
F:75
75 CS609
F:89
89 CS610
Computer Networks
F:126
126 CS610P
F:100
100 CS611
F:78
78 CS614
Data Warehousing
F:126
126 CS615
F:121
121 CS620
Modelling and Simulation
F:62
62 CS621
F:38
38 CS625
Professional Practices
M:30 F:27
57 CS626
F:30
30 CS627
F:39
39 CS628
F:30
30 CS636
F:40
40 ECE101
Introduction to Early Childhood Education
F:69
69 ECE201
Language Development of the Child
F:47
47 ECE202
Physical Development of the Child
F:29
29 ECE203
Children Literature and Educational Games
F:56
56 ECE204
Independence, Self-Management and Ethics in Early Years
F:24
24 ECE301
Psycho Social Development of the Child
F:19
19 ECE302
Education for Sustainable Development in Early Childhood Education
F:21
21 ECE402
Trends and Issues in Early Childhood Education
F:48
48 ECO302
Principles of Microeconomics
F:36
36 ECO303
Principles of Macroeconomics
F:20
20 ECO401
Economics
F:383
383 ECO402
Microeconomics
F:99
99 ECO403
Macroeconomics
F:137
137 ECO404
Managerial Economics
F:129
129 ECO501
Development Economics
F:32
32 ECO601
Business Econometrics
F:40
40 ECO603
International Economics
F:53
53 ECO604
F:64
64 ECO605
F:30
30 ECO606
Mathematical Economics I
F:108
108 ECO607
F:182
182 ECO608
F:57
57 ECO609
F:48
48 ECO610
F:74
74 ECO612
F:21
21 ECO613
F:50
50 ECO614
F:47
47 ECO615
F:55
55 ECO616
F:68
68 ECO622
F:29
29 EDU101
Foundations of Education
M:155 F:72
227 EDU201
Learning Theories
F:95
95 EDU301
General Methods of Teaching
F:20
20 EDU302
Human Development and Learning
F:57
57 EDU303
Child Development
F:113
113 EDU304
Introduction to Guidance and Counseling
F:33
33 EDU305
Classroom Management
M:120 F:88
208 EDU306
Teaching of Social Studies and Islamiat in Early Years of Education
F:48
48 EDU401
Contemporary Issues and Trends in Education
M:122 F:117
239 EDU402
Curriculum Development
F:46
46 EDU403
Art, Crafts and Calligraphy
F:37
37 EDU405
Classroom Assessment
F:87
87 EDU406
Critical Thinking and reflective Practice
M:45 F:75
120 EDU407
Research Methods in Education
F:24
24 EDU410
Teaching of Literacy Skills
M:37 F:65
102 EDU411
Teaching of Urdu
F:312
312 EDU430
ICT in Education
M:276 F:147
423 EDU431
Test Development & Evaluation
M:33 F:62
95 EDU433
Professionalism in Teaching
M:84 F:66
150 EDU501
School, Community and Teacher
M:135 F:42
177 EDU505
M:29 F:41
70 EDU510
Teaching of Mathematics
F:15
15 EDU512
Teaching of Islamic Studies
F:86
86 EDU515
Teaching of Geography
F:12
12 EDU516
Teaching of English
M:31 F:54
85 EDU601
Philosophy of Education
F:129
129 EDU602
Educational Leadership and Management
F:52
52 EDU604
Comparative Education
F:103
103 EDU654
Addressing problems of learning through technology and pedagogy
M:98 F:25
123 EDU705
F:26
26 EDUA305
Classroom Management for Young Learners
F:52
52 EDUA402
Curriculum Development for Early Childhood Education
F:10
10 EDUA403
Teaching of Arts, Crafts & Calligraphy
F:49
49 EDUA405
Assessment and Evaluation in Early Years of Education
F:16
16 EDUA406
Reflective Practices and Critical Thinking in Early Years
F:47
47 EDUA411
Teaching of Urdu in Early Childhood
F:55
55 EDUA430
Use of Information and Communication Technology for Early Childhood Education
F:77
77 EDUA501
Role of School, Community & Teacher in Early Years of Education
F:32
32 EDUA510
Teaching of Mathematics in Early Childhood
F:11
11 EDUA516
Teaching of English in Early Childhood
F:51
51 EDUA601
Philosophical Foundations of Early Childhood Education
F:20
20 EDUA602
Leadership and Management of Early Childhood Education Programs
F:22
22 ENG001
F:417
417 ENG101
English Comprehension
F:344
344 ENG201
Business and Technical English Writing
M:47 F:289
336 ENG301
Business Communication
M:53 F:340
393 ENG401
F:63
63 ENG501
History of English Language
M:53 F:73
126 ENG502
Introduction to Linguistics
M:61 F:55
116 ENG503
Introduction to English Language Teaching
M:396 F:31
427 ENG504
Second Language Acquisition
F:44
44 ENG505
F:68
68 ENG506
World Englishes
F:60
60 ENG507
Phonetics and Phonology
F:64
64 ENG508
Semantics and Pragmatics
F:61
61 ENG509
Morphology and Syntax
M:17 F:50
67 ENG510
Sociolinguistics
F:41
41 ENG511
F:102
102 ENG512
F:44
44 ENG513
F:35
35 ENG514
F:57
57 ENG515
F:37
37 ENG516
F:50
50 ENG517
M:141 F:38
179 ENG518
M:17 F:65
82 ENG519
M:247 F:64
311 ENG520
M:116 F:112
228 ENG522
Applied Linguistics
M:38 F:92
130 ENG523
M:44 F:76
120 ENG524
M:20 F:48
68 ENG527
F:78
78 ENG529
M:15 F:34
49 ETH100
Effective Citizenship
F:145
145 ETH201
F:20
20 ETH202
Ethics (for Non-Muslims)
F:54
54 FIN611
Advanced Financial Accounting
F:113
113 FIN621
Financial Statement Analysis
F:168
168 FIN622
Corporate Finance
F:162
162 FIN623
Taxation Management
F:203
203 FIN624
Islamic Modes of Finance
F:99
99 FIN625
Credit & Risk Management
F:96
96 FIN630
F:217
217 FIN702
F:56
56 FIN703
F:104
104 FIN711
F:73
73 GSC101
General Science
F:423
423 GSC201
Teaching of General Science
F:47
47 GSCA201
Teaching of General Science in Early Years of Education
F:28
28 HRM613
Performance Management
F:59
59 HRM617
Training and Development
F:70
70 HRM624
Conflict Management
F:220
220 HRM626
Recruitment and selection
F:56
56 HRM627
Human Resource Development
F:300
300 HRM733
F:19
19 HRM737
F:20
20 ISL1151
F:126
126 ISL1252
F:87
87 ISL1253
F:73
73 ISL201
F:39
39 ISL202
Islamic Studies
F:903
903 ISL2351
F:24
24 ISL2352
F:84
84 ISL2453
F:26
26 ISL2454
F:52
52 IT430
E-Commerce
F:280
280 IT601
F:31
31 IT602
F:33
33 MB501P
Cell Biology (Practical)
F:48
48 MB502P
Molecular Biology (Practical)
F:111
111 MB502T
Molecular Biology (Theory)
M:119 F:67
186 MB503T
F:35
35 MB504P
Methods in Molecular Biology (Practical)
F:46
46 MB504T
Methods in Molecular Biology (Theory)
F:53
53 MCD401
F:10
10 MCD403
F:20
20 MCD504
Acting and Performance
F:80
80 MCM101
Introduction to Mass Communication
F:98
98 MCM301
Communication skills
F:66
66 MCM304
Mass Media in Pakistan
F:52
52 MCM310
Journalistic Writing
F:114
114 MCM311
Reporting and Sub-Editing
F:96
96 MCM401
Fundamentals of Public Relations
F:108
108 MCM411
Introduction to Broadcasting
F:76
76 MCM431
F:118
118 MCM501
Advertising for Print and Electronic Media
F:105
105 MCM511
Theories of Communication
F:44
44 MCM514
F:21
21 MCM515
F:21
21 MCM516
F:55
55 MCM517
F:68
68 MCM520
F:67
67 MCM532
F:42
42 MCM601
Media Management
F:99
99 MCM604
F:115
115 MCM610
Mass Communication Law & Ethics
F:85
85 MGMT611
Human Relations (alt. code=HRM611)
F:205
205 MGMT614
Supply Chain Management
F:43
43 MGMT615
Transportation & Logistics Management
F:42
42 MGMT617
Production Planning and Inventory Control
F:44
44 MGMT622
Management Skills
F:149
149 MGMT623
Leadership & Team Management - MGMT623 (alt. code=HRM623)
M:87 F:160
247 MGMT625
F:126
126 MGMT627
Project Management
F:130
130 MGMT628
F:234
234 MGMT629
F:99
99 MGMT630
F:112
112 MGMT631
Enterprise Resource Planning
F:43
43 MGT101
Financial Accounting
F:330
330 MGT111
Introduction to Public Administration
F:197
197 MGT201
Financial Management
F:110
110 MGT211
Introduction To Business
F:175
175 MGT301
Principles of Marketing
F:215
215 MGT302
Digital Marketing
F:39
39 MGT401
Financial Accounting II
F:30
30 MGT402
Cost & Management Accounting
F:107
107 MGT404
F:135
135 MGT411
Money & Banking
F:194
194 MGT415
Introduction to Business Analytics
F:86
86 MGT501
Human Resource Management
F:396
396 MGT502
Organizational Behaviour
M:167 F:555
722 MGT503
Principles of Management
F:325
325 MGT504
F:214
214 MGT510
Total Quality Management (alt. code=MGMT510)
M:100 F:561
661 MGT513
Public Administration in Pakistan
F:80
80 MGT520
International Business
F:231
231 MGT522
Introduction to Public Policy
F:116
116 MGT601
F:121
121 MGT602
Entrepreneurship
F:270
270 MGT603
Strategic Management
F:330
330 MGT604
Management of Financial Institutions (alt. code=BNK604)
F:123
123 MGT605
F:66
66 MGT610
M:20 F:231
251 MGT611
Business & Labor Law
F:122
122 MGT612
F:77
77 MGT613
Production / Operations Management
F:220
220 MGT621
F:114
114 MGT701
F:52
52 MGT703
F:46
46 MGT713
F:44
44 MGT714
F:71
71 MGT717
F:42
42 MGT723
F:20
20 MGT725
F:67
67 MGTE630
Knowledge Management
M:34 F:19
53 MIC501P
Microbiology (Practical)
F:71
71 MIC501T
Microbiology (Theory)
F:40
40 MKT501
Marketing Management
F:250
250 MKT529
Export Marketing
F:53
53 MKT530
Consumer Behaviour
F:71
71 MKT610
Customer Relationship Management
F:83
83 MKT621
Advertising & Promotion
F:94
94 MKT624
Brand Management
F:114
114 MKT627
Sales Management
F:61
61 MKT630
International Marketing
F:127
127 MKT703
F:37
37 MKT726
F:20
20 MTH001
F:276
276 MTH100
General Mathematics
F:216
216 MTH101
Calculus And Analytical Geometry
F:1292
1292 MTH102
F:32
32 MTH104
Sets and Logic
F:64
64 MTH201
F:68
68 MTH202
Discrete Mathematics
F:238
238 MTH301
F:406
406 MTH302
Business Mathematics & Statistics
F:778
778 MTH303
Mathematical Methods
F:160
160 MTH304
F:35
35 MTH401
F:226
226 MTH403
F:147
147 MTH404
F:41
41 MTH405
F:132
132 MTH501
Linear Algebra
F:366
366 MTH5101
Calculus I
F:27
27 MTH5102
Calculus II
F:12
12 MTH601
F:266
266 MTH603
F:160
160 MTH621
F:105
105 MTH622
F:62
62 MTH631
F:167
167 MTH632
F:97
97 MTH633
F:54
54 MTH634
F:67
67 MTH641
F:179
179 MTH642
F:76
76 MTH643
F:22
22 MTH644
F:101
101 MTH645
F:63
63 MTH646
F:91
91 MTH647
F:53
53 PAD603
F:60
60 PAK301
Pakistan Studies
M:10 F:155
165 PAK302
Pakistan Studies
F:131
131 PAK522
Ideology and Constitution of Pakistan
F:51
51 PHY101
Physics
F:626
626 PHY301
F:95
95 PSC201
International Relations
F:85
85 PSC401
F:48
48 PSY101
Introduction to Psychology
F:409
409 PSY401
F:166
166 PSY402
F:43
43 PSY403
Social Psychology
F:262
262 PSY404
Abnormal Psychology
F:137
137 PSY405
Personality Psychology
F:174
174 PSY406
Educational Psychology
M:182 F:244
426 PSY407
F:175
175 PSY408
F:207
207 PSY409
F:143
143 PSY502
History & Systems of Psychology
F:264
264 PSY504
Cognitive Psychology
F:126
126 PSY505
Developmental Psychology
F:108
108 PSY510
F:179
179 PSY511
Environmental Psychology
F:69
69 PSY512
Gender Issues in Psychology
F:192
192 PSY513
F:175
175 PSY514
F:104
104 PSY515
Cross Cultural Psychology
F:140
140 PSY516
F:88
88 PSY610
F:81
81 PSY611
Ethical Issues in Psychology
F:132
132 PSY631
F:116
116 PSY632
F:180
180 PSYP402
F:90
90 PSYP610
F:171
171 PSYP631
F:185
185 SE601
F:21
21 SE601P
F:61
61 SE602
F:36
36 SOC101
Introduction to Sociology
M:121 F:1279
1400 SOC201
Social Statistics
F:191
191 SOC301
Introduction to Social Work
F:63
63 SOC302
Sociological Theories
F:94
94 SOC401
Cultural Anthropology
M:137 F:143
280 SOC402
F:59
59 SOC403
Gender Studies
F:80
80 SOC404
Pakistani Society and Culture
F:109
109 SOC509
F:89
89 SOC601
F:45
45 SOC602
Sociology of Education
F:50
50 SOC603
Sociology of Development
F:50
50 SOC604
Community Development
F:61
61 SOC605
Population Dynamics
F:51
51 SOC606
F:45
45 SOC607
F:90
90 SOC608
F:57
57 SOC609
F:82
82 SOC610
Electronic Media & Virtual Community
F:86
86 SOC611
F:58
58 SOC612
F:60
60 SOC613
F:70
70 SOC614
F:46
46 SOC615
F:65
65 SOC616
F:40
40 SOC617
F:59
59 STA301
Statistics and Probability
F:402
402 STA302
Data Analytics and Business Intelligence
F:34
34 STA621
F:64
64 STA630
Research Methods
M:76 F:298
374 STA631
Inferential Statistics
F:29
29 STA641
Statistical Packages and its Applications
F:87
87 STA642
Probability Distributions
F:59
59 STAT404
F:29
29 URD100
Urdu Language
F:42
42 URD101
Urdu
F:158
158 ZOO102
F:9
9 ZOO103
F:10
10 ZOO403
F:50
50 ZOO501
F:23
23 ZOO501P
F:44
44 ZOO501T
Developmental Biology (Theory)
F:115
115 ZOO502
F:9
9 ZOO503
F:153
153 ZOO504
F:139
139 ZOO505
F:27
27 ZOO507
F:21
21 ZOO510
Economic Zoology
F:136
136 ZOO511P
F:56
56 ZOO511T
F:27
27 ZOO512P
Animal Diversity: Invertebrates
F:25
25 ZOO512T
Animal Diversity: Invertebrates (Theory)
F:248
248 ZOO513P
Animal Diversity: Chordates (Practical)
F:34
34 ZOO513T
Animal Diversity: Chordates (Theory)
F:10
10 ZOO516P
F:36
36 ZOO516T
Animal Form & Function-I (Theory)
F:42
42 ZOO517P
F:29
29 ZOO517T
F:74
74 ZOO518P
F:71
71 ZOO518T
F:20
20 ZOO519P
F:55
55 ZOO519T
Physiology (Theory)
F:17
17 ZOO603T
Fish Biology (Theory)
F:13
13
Koi subject nahi mila
Clear
56097 result(s)
MTH646 Final Term Unsolved
Q7

Which of the following is a key disadvantage of the Crank–Nicolson scheme compared to Forward Time Central Space (FTCS) scheme?

  • A) It is only first-order accurate in time
  • B) It is conditionally stable
  • C) It cannot handle boundary conditions
  • D) It requires solving a system of equations at each time step
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q8

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 .

  • A) Liebmann's
  • B) Gauss Jordan
  • C) Newton's
  • D) Gauss elimination
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q9

The Crank-Nicolson scheme when applied on heat diffusion equation is ……

  • A) None of these
  • B) Unconditionally stable
  • C) Conditionally stable
  • D) Neither stable nor bounded
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q10

When applying Jacobi or Gauss–Seidel to the steady-state heat equation, which factor does not affect the number of iterations required for convergence?

  • A) Convergence tolerance
  • B) Physical units of temperature
  • C) Initial guess
  • D) Grid resolution (Δx, Δy)
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q11

Fourier analysis method is used to find the …………. of finite difference scheme.

  • A) None of these
  • B) Stability
  • C) Consistency
  • D) Convergence
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q12

Von Neumann stability analysis involves:

  • A) Minimizing the residual at each time step
  • B) Representing numerical errors as Fourier series and examining their growth
  • C) Analyzing the eigenvalues of the coefficient matrix
  • D) Checking the positivity of the solution
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q13

Laplace partial differential equation is a type of…………………. partial equation.

  • A) Elliptical
  • B) Parabolic
  • C) None of these
  • D) Hyperbolic
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q14

A finite difference method when applied on PDE will be stable if the amplification factor G is ……

  • A) Unrestrained
  • B) None of these
  • C) Bounded
  • D) Unbounded
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q15

For stability of an explicit scheme using Fourier analysis, the amplification factor G must satisfy:

  • A) ∣G∣≥1
  • B) ∣G∣≤1
  • C) ∣G∣=0
  • D) ∣G∣>1
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q16

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  • A) data:image/png;base64,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 .
  • B) data:image/png;base64,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 .
  • C) data:image/png;base64,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 .
  • D) data:image/png;base64,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 .
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q17

The Laplace equation describes which of the following physical phenomena?

  • A) Fluid flow with time dependence
  • B) Heat conduction over time
  • C) Wave propagation
  • D) Steady-state temperature distribution
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q18

Which of the following best describes the purpose of stability analysis in numerical solutions of PDEs?

  • A) To determine the exact solution of the PDE
  • B) To ensure that errors do not grow uncontrollably during iterations
  • C) To minimize computational time
  • D) To verify boundary conditions
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q19

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

  • A) Backward difference
  • B) Forward difference
  • C) Crank-Nicolson scheme
  • D) Central difference
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q20

In Gauss–Seidel’s method, the value of each grid point is updated using:

  • A) A weighted average of the original matrix values
  • B) Both newly updated values and some old values
  • C) Only boundary values
  • D) Only values from the previous iteration
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q21

A finite difference scheme will be stable if the amplification factor G satisfied the following condition,

  • A) data:image/png;base64,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.
  • B) data:image/png;base64,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.
  • C) data:image/png;base64,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.
  • D) data:image/png;base64,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.
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q22

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  • A) data:image/png;base64,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 .
  • B) data:image/png;base64,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 .
  • C) data:image/png;base64,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 .
  • D) data:image/png;base64,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 .
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q23

For Jacobi’s method applied to discretized PDEs, convergence is generally guaranteed when:

  • A) The grid spacing is uniform
  • B) The coefficient matrix is diagonally dominant
  • C) The coefficient matrix is symmetric
  • D) The boundary conditions are homogeneous
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q24

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 .

  • A) Secant method
  • B) Iterative method
  • C) Gauss Seidel method
  • D) Newton's
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q25

Which of the following mathematical expression represents the rotated five-point formula for 2D Laplace partial differential equation for the uniform step size in both x and y direction?

  • A) data:image/png;base64,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.
  • B) data:image/png;base64,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.
  • C) data:image/png;base64,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.
  • D) data:image/png;base64,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.
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
MTH646 Final Term Unsolved
Q26

When solving the heat diffusion equation using Gauss–Seidel iteration, the interior temperature value​ is updated using:

  • A) Only boundary values
  • B) Only values from the previous iteration
  • C) Randomly selected neighbor values
  • D) A mix of updated values from iteration k+1 and old values from iteration k
Answer abhi available nahi — is question ka AI/admin se answer milne ka intezar hai.
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