Embed Size (px)
Citation preview
List of Books on
Statistics (Available in the Library)
Library
Indian Institute of Technology Gandhinagar
Sr. No. Bibliography
1. Acevedo, M. F. (2013). Data analysis and statistics for geography, environmental science, and
engineering. Boca Raton: CRC Press.
519.5 ACE 020004
2. Agresti, A. (2009). Statistical methods for the social sciences. New Delhi: Pearson Education.
519.5024301 AGR 004848
3. Alefeld, G. (1983). Introduction to interval computations. New York: Academic Press.
519.4 ALE 003003
4. Allen, E. (2007). Modeling with to stochastic differential equations. Dordrecht: Springer.
519.2 ALL 014586
5. Allen, L. J. S. (2011). Introduction to stochastic processes with applications to biology. Boca
Raton: CRC Press.
519.23 ALL 017103
6. Allison, P. D. (2009). Fixed effects regression models. London: Sage Publications.
519.536 ALL 007727
7. Alvo, M. (2014). Statistical methods for ranking data. New York: Springer.
519.5 ALV 021836
8. Anderson, D. R. (2001). Statistics for business and economics. New Delhi: Cengage Learning.
519.5 AND 002531
9. Applebaum, D. (2004). Levy processes and stochastic calculus. Cambridge: Cambridge
University Press.
519.22 APP 004286
10. Arnold, B. C. (2008). First course in order statistics. Philadelphia: Society for Industrial and
Applied Mathematics (SIAM).
519.5 ARN 014124
11. Ash, R. B. (2000). Probability and measure theory. London: Elsevier Academic Press.
519.2 ASH 003071
12. Ash, R. B. (2008). Basic probability theory. New York: Dover Publication.
519.2 ASH 000808
13. Asmussen, S. (2010). Stochastic simulation: algorithms and analysis. New York: Springer.
519.23 ASM 014590
14. Athreya, K. B. (1972). Branching processes. New York: Springer-Verlag.
519.234 ATH 019374
15. Athreya, K. B. (2006). Measure theory and probability theory. New York: Springer Science.
515.42 MEA 019378
16. Athreya, K. B. (2006). Probability theory. New Delhi: Hindustan book agency.
519.2 ATH 020308
17. Athreya, S. (2008). Measure & probability. Hyderabad: CRC Press.
519.2 ATH 010843
18. Atkinson, K. E. (2004). Elementary numerical analysis. New Delhi: Wiley India.
519.4 ATK 003637
19. Attard, P. (2002). Thermodynamics and statistical mechanics: equilibrium by entropy
maximization. San Diego: Academic Press.
536.7 ATT 001129
20. Attouch, H. (2002). Variational analysis in Sobolev and BV spaces: applications to PDEs and
optimization. Philadelphia: Society for Industrial and Applied Mathematics (SIAM).
519.6 ATT 007514
21. Aubin, J. P. (2007). Mathematical methods of game and economic theory. New York: Dover
Publication.
519.3 AUB 004558
22. Ayyub, B. M. (2003). Probability, statistics and reliability for engineers and scientists. New
York: Champman and Hall.
519.502462 AYY 007702
23. Ayyub, B. M. (2011). Probability, statistics, and reliability for engineers and scientists. Boca
Raton: CRC Press.
519.502462 AYY 009794
24. Azzalini, A. (2014). Skew-normal and related families. Cambridge: Cambridge University
Press.
519.24 AZZ 019125
25. Baase, S. (2000). Computer algorithms: introduction to design and analysis. New Delhi:
Pearson Education.
519.7 BAA 005349
26. Babu, R. (2010). Numerical methods. New Delhi: Pearson Education.
519.4 BAB 015816
27. Baccelli, F. (2003). Elements of queueing theory: palm martingale calculus and stochastic
recurrences. New York: Springer.
519.82 BAC 015586
28. Bailey, N. T. J. (1995). Statistical methods in biology. Cambridge: Cambeidge University Press.
519.5024574 BAI 001916
29. Baisnab, A. P. (1993). Elements of probability and statistics. New Delhi: Tata McGraw Hill
Education.
519.2 BAI 005999
30. Baltagi, B. H. (2002). Econometrics. New Delhi: Springer.
330.015195 BAL 003169
31. Bansal, A. K. (2007). Bayesian parametric inference. New Delhi: Narosa Publishing House.
519.5 BAN 002674
32. Barlow, R. J. (1989). Statistics: a guide to the use of statistical methods in the physical
sciences. New York: Wiley India.
530.1595 BAR 018609
33. Baron, M. (2007). Probability and statistics for computer scientists. Boca Raton: Chapman &
Hall/CRC.
519.20113 BAR 009712
34. Basilevsky, A. (1983). Applied matrix algebra in the statistical sciences. New York: Dover
Publication.
519.5 BAS 004553
35. Basu, A. (2011). Statistical inference: the minimum distance approach. Boca Raton: CRC
Press.
519.544 BAS 013001
36. Basu, A. K. (2003). Introduction to Stochastic Process. New Delhi: Narosa Publishing House.
519.82 BAS 002811
37. Basu, A. K. (2010). Measure theory and probability. New Delhi: PHI Learning.
519.2 BAS 006668
38. Bazaraa, M. S. (2006). Nonlinear programming: theory and algorithms. New Delhi: Wiley
India.
519.76 BAZ 010307
39. Belegundu, A. D. (2011). Optimization concepts and applications in engineering. New Delhi:
Cambridge University Press.
519.602462 BEL 018166
40. Bendat, J. S. (1993). Engineering applications of correlation and spectral analysis. New York:
John Wiley & Sons.
519.53702462 BEN 012972
41. Bhatia, R. (2012). Collected papers of S.R.S. Varadhan; vol. 2: PDE, SDE, diffusions, random
media. New Delhi: Hindustan book agency.
519.2 BHA 020273
42. Bhatia, R. (2012). Collected papers of S.R.S. Varadhan; vol.1: limit theorems, review articles.
New Delhi: Hindustan book agency.
519.2 BHA 020272
43. Bhatia, R. (2012). Collected papers of S.R.S. Varadhan; vol.3: large deviations. New Delhi:
Hindustan book agency.
519.2 BHA 020274
44. Bhatia, R. (2012). Collected papers of S.R.S. Varadhan; vol.4: particle systems and their large
deviations. New Delhi: Hindustan book agency.
519.2 BHA 020275
45. Biegler, L. T. (2010). Nonlinear programming: concepts, algorithms, and applications to
chemical processes. Philadelphia: Society for Industrial and Applied Mathematics:
Mathematical Programming Society.
519.76 BIE 008152
46. Bierens, H. J. (2004). Introduction to the mathematical and statistical foundations of
econometrics. [s.l]: Cambridge University Press.
330.015195 BIE 002608
47. Billingsley, P. (2012). Probability and measure (3rd ed.). New Delhi: Wiley.
519.2 BIL 022017
48. Binmore, K. (2007). Game theory: a very short introduction. New Delhi: Oxford University
Press.
519.3 BIN 017514
49. Birge, J. R. (2011). Introduction to stochastic programming. New York: Springer.
519.7 BIR 011452
50. Bivand, R. S. (2013). Applied spatial data analysis with R (2nd ed.). New York: Springer
Science.
519.5 BIV 021833
51. Bloomfield, P. (2000). Fourier analysis of time series: an introduction. New York: Wiley.
519.55 BLO 014360
52. Blunch, N. J. (2008). Introduction to structural equation modelling using SPSS and AMOS.
New York: SAE International.
519.53502855369 BLU 007732
53. Brandt, S. (1999). Data analysis: statistical and computational methods for Scientists and
Engineers (3rd ed.). New York: Springer.
519.2 BRA 019228
54. Breiman, L....[et al.]. (1998). Classification and regression trees. Boca Raton: Chapman and
Hall/CRC Press.
519.536 BRE 017310
55. Brian S. E. (2010). Handbook of statistical analyses using R. Boca Raton: CRC Press.
519.502855133 BRI 003837
56. Bulmer, M. G. (1979). Principles of statistics. New York: Dover Publication.
519.5 BUL 004581
57. Burden, R. L. (2001). Numerical analysis. New Delhi: Cengage Learning.
519.4 BUR 002432
58. Calin, O. (2014). Geometric modeling in probability and statistics. New York: Springer.
519.5 CAL 020397
59. Capinski, M. (2001). Probability through problems. New York: Springer-Verlag.
519.2076 CAP 007646
60. Carmona, R. (1999). Stochastic partial differential equations: six perspectives. RI: American
Mathematical Society.
519.2 CAR 013629
61. Casella, G. (2002). Statistical inference. New Delhi: Cengage Learning.
519.5 CAS 002530
62. Chalmers, D.J. (2009). O level statistics. Cambridge: Cambridge University Press.
519.5 CHA 002165
63. Chambers, R. L. (2012). Introduction to model-based survey sampling with applications.
Oxford: Oxford University Press.
519.52 CHA 014258
64. Chandra, T. K. (1999). First course in asymptotic theory of statistics. New Delhi: Narosa
Publishing House.
519.5 CHA 002631
65. Chandra, T. K. (2001). First course in probability. New Delhi: Narosa Publishing House.
519 CHA 002630
66. Chandrasekhar, S. (1989). Stochastic, statistical, and hydromagnetic problems in physics and
astronomy. Chicago: University Of Chicago Press.
523.01 CHA 015548
67. Chung, K. L. (1967). Markov chains with stationary transition probabilities. New York:
Springer.
519.1 CHU 015591
68. Chung, K. L. (2003). Elementary probability theory: with stochastic processes and an
introduction to mathematical finance. . New York: Springer.
519.2 CHU 004594
69. Probability and stochastics. New York: Springer.
519.2 CIN 014589
70. Clarke, A. B. (1985). Probability and random processes: a first course with applications, (2nd
ed.). New York: John Wiley & Sons.
519.1 CLA 021489
71. Cooray, T. M. J. A. (2008). Applied time series: analysis and forecasting. New Delhi: Narosa
Publishing House.
519.55 COO 002668
72. Cowan, G. (1998). Statistical data analysis. New York: Oxford University Press.
519.5 COW 018549
73. Cox, D. R. (2006). Principles of statistical inference. New York: Cambridge University Press.
519.54 COX 003119
74. Cressie, N. A. C. (1993). Statistics for spatial data. New York: John Wiley & Sons.
519.535 CRE 021396
75. Dalgaard, P. (2008). Introductory Statistics with R. New York: Springer.
519.50285 DAL 012368
76. Das, N. G. (2009). Statistical methods. New Delhi: Tata McGraw Hill Education.
519.5 DAS 005782, 006015 and 005760
77. Das Gupta, A. (2008). Asymptotic theory of statistics and probability. New York: Springer.
519.5 DAS 020698
78. David (2009). Statistics. New Delhi: Viva Books.
300.151 DAV 004300
79. Deb, K. (2010). Multi-objective optimization using evolutionary algorithms. New Delhi: Wiley
India.
519.3 DEB 013382
80. Efron, B. (1993). An introduction to the bootstrap. New York: Chapman & Hall.
519.544 EFR 009787
81. Ethier, S. N. (2005). Markov processes: characterization and convergence. New York: Wiley
Interscience.
519.233 ETH 021744
82. Eubank, R. L. (2005). Kalman filter primer. Boca Raton: CRC Press.
519.23 EUB 019222
83. Feldman, R. M. (2010). Applied probability and stochastic processes. New York: Springer-
Verlag.
519.2 FEL 018290
84. Field, A. (2009). Discovering statistics using SPSS. London: Sage Publications.
519.50285536 FIE 011731
85. Field, A. (2013). Discovering statistics using IBM SPSS statistics (4th ed.). London: Sage
Publications.
519.502855 FIE 018777
86. Field, A. (2013). Discovering statistics using IBM SPSS statistics: and sex and drugs and rock
and roll. London: Sage Publications.
519.50285536 FIE 017025
87. Field, A. (2014). Discovering statistics using R. London: Sage Publications.
519.50285 FIE 018861
88. Field, A. P. (2009). Discovering statistics using SPSS: and sex and drugs and rock n roll.
Thousand oaks, calif.: Sage Publications.
519.50285536 FIE 011344
89. Field, A. P. (2010). Discovering statistics using SAS: and sex and drugs and rock n roll. London:
Sage Publications.
519.50285 FIE 007750
90. Fishback, P. E. (2010). Linear and nonlinear programming with Maple: an interactive,
applications-based approach. Boca Raton, FL: Chapman &Hall/CRC.
519.72 FIS 009791
91. Forst, W. (2010). Optimization: theory and practice. New York: Springer.
519.6 FOR 010130
92. Franke, J. (2008). Statistics of financial markets: an introduction. Berlin: Springer-Verlag.
332.015195 FRA 003552
93. Fuller, W. A. (1996). Introduction to statistical time series. New York: Wiley.
519.55 FUL 014211
94. Gallager, R. G. (2013). Stochastic processes: theory for applications. New York: Cambridge
University Press.
519.23 GAL 018672
95. Gardiner, C. (2009). Stochastic methods: a handbook for the natural and social sciences, (4th
ed.). New York: Springer.
519.23 GAR 021472
96. Gawarecki, L. (2011). Stochastic differential equations in infinite dimensions: with
applications to stochastic partial differential equations. New York: Springer.
519.2 GAW 011674
97. Gelman, A. (2006). Data analysis using regression and multilevel hierarchical models. New
York: Cambridge University Press.
519.536 GEL 015013
98. Gelman, A. (2014). Bayesian data analysis (3rd ed.). Boca Raton: CRC Press.
519.542 GEL 020692
99. Goldberg, S. (1960). Probability: an introduction. New York: Dover Publication.
519.2 GOL 011033
100. Goodman, J. W. (2000). Statistical optics. New York: Wiley.
535.0727 GOO 013740
101. Goodman, R. (2006). Introduction to stochastic models. New York: Dover Publication.
519.2 GOO 004583
102. Gorroochurn, P. (2012). Classic problems of probability. New York: John Wiley & Sons.
519.2 GOR 016932
103. Goswami, A. (2006). Course in applied stochastic processes. New Delhi: Hindustan book
agency.
519.2 GOS 020249
104. Gray, R. M. (2009). Probability, random processes, and ergodic properties (2nd ed.). New
York: Springer.
519.2 GRA 021344
105. Grimmett, G. (2001). One thousand exercises in probability. New York: Oxford University
Press.
519.2076 GRI 021810
106. Grimmett, G. R. (2001). Probability and random processes (3rd ed.). New York: Oxford
University Press.
519.2 GRI 021342 and 021343
107. Gubner, J. A. (2006). Probability and random processes for electrical and computer engineers.
Cambridge: Cambridge University Press.
519.2 GUB 021807
108. Gupta, S.C. (2002). Fundamentals of mathematical statistics. New Delhi: Sultan Chand.
519.2 GUP 000711
109. Haigh, J. (2012). Probability: a very short introduction. New Delhi: Oxford University Press.
519.2 HAI 017608
110. Hair, J. F. (2006). Multivariate data analysis. New Delhi: Pearson Education.
519.535 HAI 005061
111. Hajek, B. (2015). Random processes for engineers. Cambridge: Cambridge University Press.
519.23 HAJ 021607
112. Hamilton, J. D. (1994). Time series analysis. Princeton: Princeton University Press.
519.55 HAM 008011
113. Hamming, R. W. (1986). Numerical methods for scientists and engineers. New York: Dover
Publication.
519.4 HAM 010083
114. Hanagal, D. D. (2009). Introduction to applied statistics: a non-calculus based approach. New
Delhi: Narosa Publishing House.
519.5 HAN 002800
115. Hand, D. J. (2008). Statistics: a very short introduction. New Delhi: Oxford University Press.
519.5 HAN 017636
116. Hanneman, R. (2013). Basic statistics for social research. San Francisco: Jossey- Bass Inc Pub.
519.5 HAN 013181
117. Hilbe, J. M. (2009). Logistic regression models. Boca Raton: CRC Press.
519.536 HIL 003835
118. Hildebrand, F. B. (1987). Introduction to numerical analysis. New York: Dover Publication.
519.4 HIL 000759
119. Hill, T. (2006). Statistics: methods and applications: a comprehensive reference for science,
industry, and data mining. Tulsa, Okla: StatSoft.
519.5024658 HIL 002091
120. H es W W… [et ] 3 Probability and statistics in engineering. New Delhi: Wiley.
519.2 HIN 003992
121. Hodges, J. L. (2005). Basic concepts of probability and statistics. Philadelphia: Society for
Industrial and Applied Mathematics (SIAM).
519.2 HOD 014126
122. Hogg, R. V. (2005). Introduction to mathematical statistics. New Delhi: Pearson Education.
519.5 HOG 005047
123. Hogg, R. V. (2006). Probability and statistical inference. New Delhi: Pearson Education.
519.2 HOG 005071
124. Hojsgaard, S. (2012). Graphical models with R. New York: Springer.
519.535 HOJ 018656
125. Holden, H. (1996). Stochastic partial differential equations: a modeling, white noise
functional approach. Boston: Birkhauser.
519.2 HOL 011419
126. Huber, P. J. (2009). Robust statistics. Hoboken, N.J.: John Wiley & Sons.
519.5 HUB 013367
127. Huber, P. J. (2011). Data analysis: what can be learned from the past 50 years. New Jersey:
Wiley.
519.509 HUB 014210
128. Hughes, B. D. (1996). Random walks and random environments. New York: Oxford University
Press.
530.159282 HUG 013080
129. Hurlbert, G. H. (2009). Linear optimization; The simplex workbook. New York: Springer.
519.92 HUR 008225
130. Husson, F. F. (2011). Exploratory multivariate analysis by example using R. Boca Raton: CRC
Press.
519.535028551 HUS 017110
131. Hyvarinen, A. (2009). Natural image statistics: a probabilistic approach. New York: Springer.
006.37 HYV 018718
132. Infanger, G. (c201). Stochastic programming: the state of the art: in honor of George B.
Dantzig. New York: Springer.
519.7 INF 011459
133. Iosifescu, M. (1980). Finite Markov processes and their applications. New York: Dover
Publication.
519.23 IOS 000914
134. Isaacson, E. (1994). Analysis of numerical methods. New York: Dover Publication.
519.4 ISA 000760
135. Ito, K. (2008). Lagrange multiplier approach to variational problems and applications.
Philadelphia: Society for Industrial and Applied Mathematics (SIAM).
519.3 ITO 004470
136. Ivezic, Z...[et al]. (2014). Statistics, data mining, and machine learning in astronomy: a
practical python guide for the analysis of survey data. Princeton: Princeton University Press.
520.285631 IVE 017293
137. Jackman, S. (2009). Bayesian analysis for the social sciences. Chi Chester: Wiley.
519.542 JAC 014370
138. Jackson, E. (2003). Users guide to principal components. Canada: Jones & Bartlett Publishing.
519.5354 JAC 018655
139. Jacobs, K. (2010). Stochastic processes for physicists: understanding noisy systems. New York:
Cambridge University Press.
519.2302453 JAC 013575
140. Jacod, J. (2003). Limit theorems for stochastic processes. Berlin: Springer-Verlag.
519.287 JAC 011443
141. Jahn, J. (2011). Vector optimization: theory, applications, and extensions. Berlin: Springer-
Verlag.
519.7 JAH 011462
142. James, G. (2013). Introduction to statistical learning: with applications in R. New York:
Springer.
519.5 JAM 020074
143. Jaynes, E. T. (2003). Probability theory the logic of science. Cambridge: Cambridge University
Press.
519.2 JAY 017314
144. Jensen, F. V. (2007). Bayesian networks and decision graphs (2nd ed.). New York: Springer.
519.542 JEN 020658
145. Johnson, N. L. (1994). Continuous univariate distributions, v.1. Delhi: Wiley India.
519.24 JOH 001018
146. Johnson, N. L. (1997). Discrete multivariate distributions. New York: John Wiley.
519.24 JOH 001036
147. Johnson, R. A. (2009). Applied multivariate statistical analysis. New Delhi: PHI Learning.
519.535 JOH 006156
148. Jolliffe, I.T. (2002). Principal component analysis. New York: Springer.
519.535 JOL 018657
149. Jordan, M. I. (Ed.). (1999). Learning in graphical models. Cambridge: MIT Press.
519.5 JOR 021776
150. Joshi, M. C. (2004). Optimization: theory and practice. New Delhi: Narosa Publishing House.
519.7 JOS 002865
151. Jungnickel, D. (2005). Graphs, networks, and algorithms. New York: Springer-Verlag.
519.64 JUN 007905
152. Justesen, J. (2004). Course in error correcting codes. New Delhi: Hindustan book agency.
519.4 JUS 020251
153. Kailath, T. (1988). Lectures on Weiner and Kalman filtering. New York: Springer Science.
519.5 KAI 019850
154. Kailath, T. (2010). Linear estimation. London: Prentice Hall of India.
519.544 KAI 015906
155. Kaipio, J. (2005). Statistical and Computational Inverse Problems. New York: Springer.
515.357 KAI 019726
156. Kall, P. (2011). Stochastic linear programming: models, theory, and computation. Berlin:
Springer-Verlag.
519.72 KAL 011458
157. Kalyanmoy, D. (2012). Optimization for engineering design: algorithms and examples (2nd
ed.). New Delhi: PHI Learning.
519.602462 KAL 019798
158. Kampen, N. G. (2007). Stochastic processes in physics and chemistry. London: Elsevier.
519.202453 KAM 007774
159. Kandasamy, P. (2003). Probability, random variables and random processes. New Delhi: S.
Chand and Company.
519.2 KAN 001725
160. Kanji, G. K. (2006). 100 statistical tests. London: Sage Publications.
519.56 KAN 007722
161. Kaplan, M. (2007). Chances are: adventures in probability. New York: Penguin Books.
519.2 KAP 016707
162. Kapur, J. N. (1960). Mathematical statistics. New Delhi: S. Chand & Co.
519.5 KAP 010612
163. Karian, Z. A. (2011). Handbook of fitting statistical distributions with R. Boca Raton, FL: CRC
Press.
519.24 KAR 009708
164. Karlin, S. (1975). First course in stochastic processes (2nd ed.). New York: Academic Press.
519.2 KAR 020690
165. Karlin, S. (1981). Second course in stochastic processes. New York: Academic Press.
519.2 KAR 021799
166. Kay, S. M. (2005). Intuitive probability and random processes using MATLAB. New York:
Springer Science.
519.20113 KAY 015419
167. Kay, S. M. (2010). Modern spectral estimation: theory and application. New Delhi: Pearson
Education.
519.5 KAY 014416
168. Keen, K. J. (2010). Graphics for statistics and data analysis with R. Boca Raton: CRC Press.
515.50285 KEE 009789
169. Keller, G. (2009). Statistics for management and economics. New Delhi: Cengage Learning.
519.5 KEL 002532
170. Kelley, C. T. (1995). Iterative methods for linear and nonlinear equations. New Delhi: Society
for Industrial and Applied Mathematics (SIAM).
519.4 KEL 003005
171. Kelly, F. (2014). Stochastic networks. Cambridge: Cambridge University Press.
519.2 KEL 018841
172. Khasminskii, R. (2012). Stochastic stability of differential equations. Heidelberg: Springer.
519.22 KHA 011460
173. Kinney, J. J. (2015). Probability: an introduction with statistical applications (2nd ed.). New
York: John Wiley & Sons.
519.2 KIN 021832
174. Kirchgassner, G. (2007). Introduction to modern time series analysis. Berlin: Springer.
519.55 KIR 003171
175. Klafter, J. (2011). First steps in random walks: from tools to applications. Oxford: Oxford
University Press.
519.282 KLA 019310
176. Klebaner, F. C. (2005). Introduction to stochastic calculus with applications. London: Imperial
College Press.
519.23 KLE 011238
177. Kleinert, H. (2009). Path integrals in quantum mechanics, statistics, polymer physics, and
financial markets. New jersey: World Scientific.
530.12 KLE 001949
178. Kleinrock, L. (1975). Queueing systems. New York: Wiley.
519.82 KLE 013960
179. Koller, D. (2009). Probabilistic graphical models: principles and techniques. Cambridge: MIT
Press.
519.5420285 KOL 014899
180. Korb, K. B. (2011). Bayesian artificial intelligence. Boca Raton, FL: CRC Press.
519.542 KOR 010973
181. Korostelev, A. P. (2011). Mathematical statistics: asymptotic minimax theory. RI: American
Mathematical Society.
519.5 KOR 013617
182. Korte, B. H. (2012). Combinatorial optimization: theory and algorithms. New York: Springer.
519.64 KOR 014597
183. Krishnan, V. (2014). Probability and random processes. New Delhi: Wiley.
519.2 KRI 018896
184. Krzanowski, W. J. (2000). Principles of multivariate analysis: a users perspective. New York:
Oxford University Press.
519.535 KRZ 018566
185. Kubiak, T.M. (2009). Certified six sigma black belt handbook. New Delhi: Pearson Education.
658.4013 KUB 005427
186. Kuehl, R. O. (2000). Design of experiments: statistical principles of research design and
analysis. Pacific Grove: Duxbury/Thomson Learning.
519.5 KUE 011806
187. Kuhn, H. W. (1997). Classics in game theory. New Jersey: Princeton University Press.
519.3 KUH 007999
188. Kuhn, M. (2013). Applied predictive modeling. New York: Springer-Verlag.
519.5 KUH 018333
189. Kullback, S. (1997). Information theory and statistics. New York: Dover Publication.
519.5 KUL 017311
190. Kundu, D. (2004). Statistical computing: existing methods and recent developments. New
Delhi: Narosa Publishing House.
519.502 KUN 002932
191. Kushner, H. J (2003). Stochastic approximation and recursive algorithms and applications.
New York: Springer.
519.2 KUS 011446
192. Kwon, R. H. (2014). Introduction to linear optimization and extensions with MATLAB®. Boca
Raton: CRC Press.
519.72 KWO 017121
193. Lai, T. L. (2008). Statistical models and methods for financial markets. Berlin: Springer-Verlag.
332.501519 LAI 003732
194. Landau, L. D. (2011). Statistical physics. New Delhi: Elsevier.
530.13 LAN 009466
195. Landau, L.D. (2005). Statistical physics: course of theoretical physics (v.5). New Delhi:
Butterworth-Heinmann.
531.19 LAN 000415
196. Lange, K. (2004). Optimization. Berlin: Springer-Verlag.
519.6 LAN 001749
197. Lattin, J. M. (2003). Analyzing multivariate data. New Delhi: Thomson.
519.535 LAT 002249
198. Lauritzen, S. L. (1996). Graphical models. New York: Oxford University Press.
519.538 LAU 022041
199. Lawler, G. F. (2006). Introduction to stochastic processes. Boca Raton: CRC Press.
519.2 LAW 017123
200. Leon-Garcia, A. (1994). Probability, random variables and random processes. New Delhi:
Pearson Education.
519.2 LEO 005573
201. Leon-garcia, A. (2008). Probability, statistics, and random processes for electrical engineering.
Upper Saddle River: PHI Learning.
519.20246213 LEO 011645
202. Levin, R. I. (1998). Statistic for management. New Delhi: Pearson Education.
519.5 LEV 005077 and 000861
203. Levine, D. M. (2008). Statistics for Six Sigma green belts: with Minitab and JMP. New Delhi:
Pearson Education.
658.4013 005474
204. Liero, H. (2012). Introduction to the theory of statistical inference. Boca Raton: CRC Press.
519.54 LIE 017125
205. Liggett, T. M. (2010). Continuous time Markov processes: an introduction. RI: American
Mathematical Society.
519.233 LIG 013592
206. Lind, D. A. (2008). Statistical techniques in business and economics. New Delhi: Tata McGraw
Hill Education.
519.5 LIN 005835
207. Lipschutz, S. (1998). Schaums outline of theory and problems of introduction to probability
and statistics. New Delhi: Tata McGraw Hill Education.
519.2 LIP 005641
208. Lipschutz, S. (2010). Schaum`s outlines Probability. New Delhi: Tata McGraw Hill.
519.2 LIP 006071
209. Liptser, R. S. (2001). Statistics of random processes. Berlin: Springer Science.
519.2 LIP 015596
210. Liu, G. P. (2008). Multi objective optimisation and control. New Delhi: PHI Learning.
519.6 LIU 006727
211. Long, J. S. (1997). Regression models for categorical and limited dependent variables.
London: Sage Publications.
519.536 LON 020171
212. Luce, R. D. (1989). Games and decisions: introduction and critical survey. New York: Dover
Publication.
519.3 LUC 004559
213. Luderer, B. (2003). Multivalued analysis and nonlinear programming problems with
perturbations. Boston: Kluwer Academic Publishers.
519.76 LUD 015602
214. Luenberger, D. G. (1997). Optimization by vector space methods. New York: John Wiley &
Sons.
519 LUE 021847
215. Luenberger, D. G. (2008). Linear and nonlinear programming. New York: Springer.
519.72 LUE 010305
216. Madsen, H. (2008). Time series analysis. Boca Raton: Champman and Hall/CRC.
519.55 MAD 003834
217. Malliavan, P. (2006). Stochastic calculus of variations in mathematical finance. London:
Springer Science.
519.23 MAL 015599
218. Martinez, W. L. (2008). Computational statistics handbook with MATLAB. Boca Raton: CRC
Press.
519.50285 MAR 009526
219. Martinez, W. L. (2011). Exploratory data analysis with MATLAB. Boca Raton: CRC Press.
519.535 MAR 013709
220. Matloff, N. (2011). Art of R programming: a tour of statistical software design. San Francisco:
No Starch Press.
519.502855133 MAT 017179
221. Mazzocchi, M. (2008). Statistics for marketing and consumer research. London: Sage
Publications.
519.502 MAZ 007746
222. McCauley, J. L. (2013). Stochastic calculus and differential equations for physics and finance.
Cambridge: Cambridge University Press.
519.2 MCC 015383
223. McClave, J. T. (2009). First course in statistics. Upper Saddle River: Pearson Printice Hall.
519.5 MCC 007140
224. Mcgrayne, S. B. (2011). Theory that would not die: how Bayes` rule cracked the enigma code,
hunted down Russian submarines, & emerged triumphant from two centuries of controversy.
London: Yale University Press.
519.542 MCG 021680
225. Mead, R. (2012). Statistical principles for the design of experiments. Cambridge: Cambridge
University Press.
001.434 MEA 013404
226. Mendenhall, W. (2009). Probability and statistics. New Delhi: Cengage Learning.
519.5 MEN 002499
227. Mikosch, T. (1998). Elementary stochastic calculus with finance in view. Singapore: world
Scientific.
519.2 MIK 002620
228. Miller, I. (2004). John E. Freunds mathematical statistics with applications. New Delhi:
Pearson Education.
519.5 MIL 005056
229. Milton, J. S. (2003). Introduction to probability and statistics: principles and applications for
engineering and the computing sciences. New Delhi: Tata McGraw Hill Education.
519.5 MIL 005891
230. Mlodinow, L. (2009). Drunkard`s walk: how randomness rules our lives. New York: Vintage
books.
519.2 MLO 016709
231. Montgomery, D. C. (2003). Applied statistics and probability for engineers. New Delhi: Wiley
India.
519.5 MON 001326
232. Montgomery, D. C. (2006). Introduction to linear regression analysis. New Delhi: Wiley India.
519.536 MON 003644
233. Montgomery, D. C. (2013). Design and analysis of experiments, minitab Manual. Hoboken:
John Wiley &Sons, Inc..
519.57 MON 014890
234. Montgomery, D. C. (2013). Design and analysis of experiments. Hoboken: John Wiley & Sons,
Inc..
519.57 MON 014889
235. Mood, A. M. (2006). Introduction to the theory of statistics. New Delhi: Tata McGraw Hill
Publishing.
519.5 MOO 001444
236. Mukhopadhyay, P. (2004). Introduction to estimating functions. New Delhi: Narosa Publishing
House.
519.544 MUK 002656
237. Mukhopadhyay, P. (2007). Survey sampling. New Delhi: Narosa Publishing House.
519.52 MUK 002937
238. Mukhopadhyay, P. (2010). An introduction to the theory probability. New Jersey: world
Scientific.
519.2 MUK 009983
239. Myers, J. L. (2010). Research design and statistical analysis. New York: Psychology press.
519.5 MYE 011096
240. Nahin, P. J. (2008). Duelling idiots and other probability puzzlers. Princeton: Princeton
University Press.
519.2 NAH 012617
241. Nahin, P. J. (2013). Digital dice: Computational solutions to practical probability problems.
New Jersey: Princeton University Press.
519.2076 NAH 014168
242. Neumaier, A. (1990). Interval methods for systems of equations. Cambridge: Cambridge
University Press.
519.4 NEU 003007
243. Nocedal, J. (2006). Numerical optimization. New York: Springer.
519.6 NOC 014272
244. Norris, N. R. (1997). Markov chains. Cambridge: Cambridge University Press.
519.233 NOR 021469
245. Ogunnaike, B. A. (2010). Random phenomena: fundamentals of probability and statistics for
engineers. Boca Raton, FL: CRC Press.
519.5 OGU 011094
246. Oksendal, B. K. (2003). Stochastic differential equations: an introduction with applications.
New York: Springer-Verlag.
519.2 OKS 007883
247. Ortega, J. M. (1990). Numerical analysis: a second course. Philadelphia: SIAM.
519.4 ORT 018317
248. Pakshirajan, R. P. (2013). Probability theory: a foundational course. Haryana: Hindustan book
agency.
519.2 PAK 020309
249. Pal, M. (2007). Numerical analysis for scientists and engineers: theory and C programs. New
Delhi: Narosa Publishing House.
519.4 PAL 002855
250. Pallant, J. (2007). SPSS survival manual: a step by step guide to data analysis using SPSS for
Windows. Maidenhead: Open University Press.
519.50285536 PAL 003199
251. Papalambros, P. Y. (2000). Principles of optimal design: modeling and computation. New
York: Cambridge University Press.
519.3 PAP 012753
252. Papoulis, A. (2002). Probability, random variables, and stochastic processes. New Delhi: Tata
McGraw-Hill.
519.1 PAP 000704 and 004376
253. Pardo, L. (2006). Statistical inference based on divergence measures. Boca Raton: CRC Press.
519.54 PAR 013103
254. Parthasarathy, K. R. (2005). Introduction to probability and measure. New Delhi: Hindustan
book agency.
519.2 PAR 020297
255. Pathak, R. S. (2001). Course in distribution theory and applications. New Delhi: Narosa
Publishing House.
519.5 PAT 002622
256. Pathria, R. K. (2011). Statistical mechanics. Boston: Elsevier.
530.13 PAT 015197
257. Patil, P. B. (2006). Numerical computational methods. New Delhi: Narosa Publishing House.
519.40285 PAT 002600
258. Peebles, P. Z. (2001). Probability, random variables, and random signal principles. New Delhi:
Tata McGraw Hill Education.
519.2 PEE 005951
259. Peng, C. Y. J. (2009). Data analysis using SAS. London: Sage Publications.
519.50285 PEN 007747
260. Peterson, M. (2009). Introduction to decision theory. Cambridge: Cambridge University Press.
519.542 PET 002036
261. Pinsky, M. A. (2011). Introduction to stochastic modeling (4th ed.). Boston: Elsevier Academic
Press.
519.2 PIN 021770
262. Pinsky, R. G. (2014). Problems from the discrete to the continuous: probability, number
theory, graph theory, and combinatorics. New York: Springer Science.
519.64 PIN 021838
263. Platen, E. (2010). Numerical solution of stochastic differential equations with jumps in
finance. Berlin: Springer-Verlag.
519.2 PLA 011406
264. Pratt, J. W. (2009). Introduction to statistical decision theory. New Delhi: PHI Learning.
311.2 PRA 006599
265. Press, W. H. (1988). Numerical recipes in C++: the art of scientific computing. New Delhi:
Cambridge University Press.
519.40285 PRE 002975
266. Prieto-Rumeau, T. (2012). Selected topics on continuous time controlled Markov chains and
Markov games. London: Imperial College Press.
519.233 PRI 015874
267. Purohit, S. G. (2008). Statistics using R. New Delhi: Narosa Publishing House.
519.5 PUR 002935
268. Ralston, A. (2001). First course in numerical analysis. New York: Dover Publication.
519.4 RAL 000761
269. Ramachandran, K. M. (2012). Stochastic differential games: theory and applications. Paris:
Atlantis Press.
519.3 RAM 011457
270. Rangaiah, G. P. (2010). Stochastic global optimization: techniques and applications in
chemical engineering. Hackensack, NJ: World Scientific.
519.62 RAN 011752
271. Reif, F. (2009). Fundamentals of statistical and thermal physics. Long Grove: Waveland Press.
530.13 REI 010784
272. Renshaw, E. (2011). Stochastic population processes: analysis, approximations, simulations.
New York: Oxford University Press.
519.233 REN 014743
273. Renyi, A. (2007). Foundations of probability. New York: Dover Publication.
519.2 REN 004552
274. Resnick, S. (2002). Adventures in stochastic processes. Boston: Birkhauser.
519.2 RES 019750
275. Revuz, D. (2005). Markov chains. New York: Oxford University Press.
519.233 REV 021668
276. Rice, J. A. (2007). Mathematical statistics and data analysis. New Delhi: Book Cole.
519.5 RIC 002420
277. Rizzo, M. L. (2008). Statistical computing with R. Boca Raton: CRC Press.
519.502855133 RIZ 017658
278. Roberts, A. J. (2009). Elementary calculus of financial mathematics. Philadelphia: Society for
Industrial and Applied Mathematics (SIAM).
519.2 ROB 003793
279. Roberts, J. B. (2003). Random vibration and statistical linearization. New York: Dover
Publication.
620.3 ROB 014405
280. Rohatgi, V. K. (2001). An introduction to probability and statistics. . New York: Wiley.
519.2 ROH 009420
281. Rosenblatt, M. (1974). Random processes (2nd ed.). New York: Springer.
519.1 ROS 021490
282. Rosenblatt, M. (1985). Stationary sequences and random fields. Boston: Birkhauser.
519.55 ROS 014454
283. Rosenthal, J. S. (2006). Struck by lightning: the curious world of probabilities. Washington:
Joseph Henry Press.
519.2 ROS 017209
284. Ross, S. M. (1996). Stochastic processes. New Delhi: Wiley India.
519.2 ROS 003647
285. Ross, S. M. (2005). Introductory Statistics. New Delhi: Elsevier.
519.5 ROS 003026
286. Ross, S. M. (2007). Introduction to probability models. Boston: Elsevier.
519.2 ROS 003027
287. Ross, S. M. (2014). Introduction to probability and statistics for Engineers and Scientists (4th
ed.). New Delhi: Elsevier.
519.5 ROS 019957
288. Rotar, V. I. (2012). Probability and stochastic modeling. Boca Raton: CRC Press.
519.2 ROT 017135
289. Rotman, J. J. (1984). Introduction to the theory of groups. New York: Springer.
519.4 ROT 000724
290. Roussas, G. (2007). Introduction to probability. London: Elsevier Academic Press.
519.2 ROU 003075
291. Rousseeuw, P.J. (2003). Robust regression and outlier detection. Hoboken: Wiley-
Interscience.
519.536 ROU 017285
292. Rozanov, Y. A. (1969). Probability Theory A Concise Course. New York: Dover Publication.
519.2 ROZ 004557
293. Rue, H. (2005). Gaussian Markov random fields: theory and applications. Boca Raton: CRC
Press.
519.233 RUE 021667
294. Salamon, P. (2002). Facts, conjectures, and improvements for simulated annealing.
Philadelphia: Society for Industrial and Applied Mathematics (SIAM).
519.3 SAL 012864
295. Santos, D. A. (2011). Probability: an introduction. Boston: Jones & Bartlett Publishing.
519.2 SAN 013061
296. Sarma, K.V.S. (2010). Statistics made simple: Do it yourself on PC. New Delhi: PHI Learning.
519.5 SAR 006886
297. Sauro, J. (2012). Quantifying the user experience: practical statistics for user research.
Waltham: Elsevier Morgan Kaufmann.
004.019 SAU 014648
298. Schrijver, A. (2003). Combinatorial optimization: polyhedra and efficiency. Berlin: Springer.
519.3 SCH 018616
299. Schweizer, B. (2005). Probabilistic metric spaces. New York: Dover Publication.
519.2 SCH 004569
300. Scott, D. W. (1992). Multivariate density estimation: theory, practice, and visualization. New
York: Wiley-Interscience.
519.535 SCO 018460
301. Sharma, J. K. (2004). Numerical methods for engineers and scientists. New Delhi: Narosa
Publishing House.
519.4 SHA 002858
302. Sharma, J. K. (2007). Business statistics. New Delhi: Pearson Education.
519.5024658 SHA 005010
303. Sharma, J. K. (2010). Fundamentals of business statistics. Delhi: Pearson.
519.5 SHA 005026
304. Shi, J. Q. (2011). Gaussian process regression analysis for functional data. Boca Raton, FL: CRC
Press.
519.23 SHI 009788
305. Shikhman, V. (2012). Topological aspects of nonsmooth optimization. New York: Springer.
519.6 SHI 011461
306. Shirali, S. (2011). Multivariable analysis. London: Springer.
519.53 SHI 010128
307. Shumway, R.H. (2011). Time series analysis and its applications: with R examples (3rd ed.).
New York: Springer.
519.55 SHU 020395
308. Siegel, A. N. (2013). Combinatorial game theory. Providence: American Mathematical
Society.
519.3 SIE 018221
309. Silver, N. (2012). Signal and the noise: the art and science of prediction. London: Allen Lane.
519.542 SIL 014389
310. Sinha, S. M. (2006). Mathematics programming: theory and methods. New Delhi: Elsevier.
519.7 SIN 003029
311. Sivia, D. S. (2006). Data analysis: a Bayesian tutorial. London: Oxford University Press.
519.5 SIV 015047
312. Smith, R. C. (2014). Uncertainty quantification: theory, implementation, and applications.
Philadelphia: SIAM.
519.544 SMI 018192
313. Snyman, J. A. (2005). Practical mathematical optimization: an introduction to basic
optimization theory and classical and new gradient-based algorithms. New York: Springer.
519.6 SNY 002223
314. Soong, T. T. (2004). Fundamentals of probability and statistics for engineers. Hoboken, NJ:
John Wiley & Sons.
519.202462 SOO 012973
315. Spanos, A. (1986). Statistical foundations of econometric modelling. New York: Cambridge
University Press.
330.028 SPA 003120
316. Speyer, J. L. (2013). Stochastic processes, estimation, and control. New Delhi: PHI Learning.
519.23 SPE 013493
317. Spiegel, M. R. (2008). Schaums outlines of statistics. New Delhi: Tata McGraw-Hill Publishing.
519.5 SPI 005806
318. Spiegel, M. R. (2009). Problems of statistics. New Delhi: Tata McGraw-Hill Publishing.
519.2076 SPI 005696
319. Srivastava, M. K. (2009). Statistical inference: Testing of hypotheses. New Delhi: PHI Learning.
519.56 SRI 006884
320. Stark, H. (2002). Probability and random processes with applications to signal processing.
New Delhi: Pearson Education.
519.2 STA 004386
321. Stark, H. (2012). Probability, statistics and random processes for engineers (4th ed.). Boston:
Pearson Education.
621.3822 STA 021806
322. Staudte, R. G. (1990). Robust estimation and testing. New York: John Wiley & Sons.
519.544 STA 021491
323. Steele, J. M. (2001). Stochastic calculus and financial applications. New York: Springer
Science.
519.2 STE 015598
324. Stewart, W. J. (2009). Probability, Markov chains, queues and simulation: the mathematical
basis of performance modeling. Princeton: Princeton University Press.
519.20113 STE 014788
325. Stewartm, G. W. (1996). After notes on numerical analysis. Philadelphia: SIAM.
519.4 STE 016802
326. Stroock, D. Wd. (2005). An introduction to markov processes. New York: Springer-Verlag.
519.233 STR 009171
327. Stuart, A. (2004). Kendall’s advanced theory of statistics (Vol.2A). London: Wiley India.
519.5 STU 018608
328. Suhov, Yu. M. (2005). Probability and statistics by example. Cambridge: Cambridge University
Press.
519.2 SUH 015177
329. Sun, W. (2006). Optimization theory and methods: nonlinear programming. New York:
Springer.
519.76 SUN 009177
330. Sundar Rao, P.S. S. (2007). Introduction to biostatistics and research methods. New Delhi: PHI
Learning.
574.015195 SUN 006558
331. Sundaram, R. K. (1996). First course in optimization theory. [s.l]: Cambridge University Press.
519.3 SUN 002609
332. Sundarapandian, V. (2009). Probability, Statistics and Queuing Theory. New Delhi: PHI
Learning.
519.2 SUN 006806
333. Sveshnikov, A. A. (1968). Problems in probability theory, mathematical statistics and theory
of random functions. New York: Dover Publication.
519.2076 SVE 004584
334. Tadelis, S. (2013). Game theory: an introduction. Princeton: Princeton University Press.
519.3 TAD 013999
335. Takahashi, S. (2009). Manga guide to statistics. San Francisco: No Starch Press.
519.5 TAK 018065
336. Tanis, E. A. (2008). A brief course in mathematical statistics. New Delhi: Pearson Education.
519.5 TAN 014702
337. Thomas, L. C. (1986). Games, theory, and applications. New York: John Wiey.
519.3 THO 000658
338. Thompson, J. F. (1999). Handbook of grid generation. Boca Raton: CRC Press.
519.4 THO 003788
339. Tijs, S. (2003). Introduction to game theory. New Delhi: Hindustan book agency.
519.3 TIJ 020294
340. Trivedi, K. S. (2009). Probability and statistics with reliability, queuing, and computer science
applications. New Delhi: PHI Learning.
519.2 TRI 006805
341. Turkington, D.A. (2002). Matrix calculus and zero-one matrices: statistical and econometric
applications. Cambridge: Cambridge University Press.
512.9434 TUR 001699
342. Uan, S. C. (1997). Probability theory: independence, interchangeability, martingales. New
York: Springer-Verlag.
519.2 UAN 007901
343. Ulrich F. (2002). Algorithmic principles of mathematical programming. Boston: Kluwer
Academic Publishers.
519.7 ULR 015582
344. Unser, M. (2010). An introduction to sparse stochastic processes. Cambridge: Cambridge
University Press.
519.23 UNS 019329
345. Upreti, S. R. (2013). Optimal control for chemical engineers. Boca Raton: CRC Press.
519.6 UPR 014960
346. Urdan, T. C. (2010). Statistics in plain English. New York: Taylor & Francis.
519.5 URD 017294
347. Utts, J. M. (2014). Seeing through statistics (4th ed.). Stamford: Cengage Learning.
519.5 UTT 019118
348. Vadja, S. (2009). Mathematical programming. New York: Dover Publication.
519.7 VAD 000799
349. Vanmarcke, E. (2010). Random fields: analysis and synthesis. Singapore: World Scientific.
519.23 VAN 014362
350. Veerarajan, T. (2008). Probability, Statistic and random progresses. New Delhi: Tata McGraw
Hill.
519.2 VEE 006051
351. Viswanathan, P.K. (2003). Business statistics: an applied orientation. New Delhi: Pearson
Education.
519.5024658 VIS 005006
352. Walker, I. R. (2010). Reliability in scientific research: improving the dependability of
measurements, calculations, equipment, and software. Cambridge: Cambridge University
Press.
507.2 WAL 015179
353. Walpole, R. E...et al. (2007). Probability & statistics for engineers and scientists. New Delhi:
Prentice-Hall.
519.02462 WAL 008386
354. Wang, B. (2011). Harmonic analysis method for nonlinear evolution equations, I. Singapore:
World Scientific Pub. Co.
519.72 WAN 009987
355. Webb, A. R. (2011). Statistical pattern recognition (3rd ed.). New Delhi: Wiley.
006.4 WEB 018753
356. Webster, A. L. (1998). Applied statistics for business and economics. New Delhi: Tata McGraw
Hill Education.
519.502433 WEB 005661
357. Weinstein, L. (2008). Guesstimation: solving the world`s problems on the back of a cocktail
napkin. Princeton: Princeton University Press.
519.544 WEI 012044
358. Welkowitz, J. (2006). Introductory statistics for the behavioral sciences. New Jersey: Wiley.
519.50243 WEL 009399
359. Wheelan, C. (2013). Naked statistics: stripping the dread from the data. New York: W W
Norton.
519.5 WHE 015485
360. Whittaker, J. (1990). Graphical models in applied multivariate statistics. New York: John
Wiley & Sons.
519.535 WHI 022010
361. Wilcox, R. R. (2010). Fundamentals of modern statistical methods: substantially improving
power and accuracy (2nd ed.). New York: Springer.
519.5 WIL 021341
362. Wilcox, R. R. (2012). Introduction to robust estimation and hypothesis testing (3rd ed.).
Gurgaon: Elsevier.
519.544 WIL 021600
363. William, H. P. (2002). Numerical recipes in C++: the art of scientific computing. New Delhi:
Cambridge University Press.
519.40285 WIL 002005
364. Willink , R. (2013). Measurement uncertainty and probability. Cambridge: Cambridge
University Press.
519.2 WIL 015376
365. Winston, W. L. (2004). Probability Models. New Delhi: Cengage Learning.
519.2 WIN 002500
366. Yaglom, A. M. (1987). Correlation theory of stationary and related random functions. New
York: Springer-Verlag.
519.5 YAG 014452
367. Yates, R. D. (2005). Probability and stochastic processes: a friendly introduction for electrical
and computer engineers (2nd ed.). New York: John Wiley & Sons.
519.2 YAT 021578
368. Zhao. (2012). New trends in stochastic analysis and related topics. Hackensack, NJ: World
Scientific.
519.52 ZHA 011753
***
Compiled by Library
Date:10.08.2015
![List of Books In ‘Hindi Language · 2015-05-29 · List of Books In ‘Hindi Language’ [Available in the Library] Indian Institute of Technology Gandhinagar LIBARARY](https://img.dokumen.tips/doc/110x75/5e60e6de9341e93d1a64b99f/list-of-books-in-ahindi-language-2015-05-29-list-of-books-in-ahindi-languagea.jpg)
