Short Bio
Ivan Arraut obtained his PhD graduated from the school of Science (Physics) at The University of Osaka in 2014. He is a Master in Science Physics from The University of Los Andes (2008) and a bachelor in Mechanical Engineering from Universidad del Norte in 2004. Between 2008 and 2010 and between 2018 and 2021, he worked as a professor and as a lecturer in different universities. Ivan Arraut is one of the Top10 active researchers at the University of Saint Joseph, in agreement with the information provided in the link: https://www.adscientificindex.com/h-index-rankings/?university=University+of+Saint+Joseph
The information about his research, can be found in the following serious academic sources:
1). Google Scholar: https://scholar.google.co.jp/citations?user=md3hpM4AAAAJ&hl=es and inside the link
2). Orcid identifier 0000-0002-2509-5048: https://orcid.org/0000-0002-2509-5048
3). Scopus number: 25823701800 https://www.scopus.com/authid/detail.uri?authorId=25823701800
4). Inspire-hep: https://inspirehep.net/authors/1059082?ui-citation-summary=true
5). Arxiv database: https://arxiv.org/search/?query=Ivan+Arraut&searchtype=author&source=header
6). NASA/ADS: https://ui.adsabs.harvard.edu/search/q=author%3A%22Arraut%2C%20Ivan%22&sort=date%20desc%2C%20bibcode%20desc&p_=0
7). Researchgate: https://www.researchgate.net/profile/Ivan-Arraut
His research areas include Fundamental Physics (General Relativity and Quantum Field Theory), Engineering Science, Game Theory, Quantum Finance and Machine Learning. Ivan Arraut likes to combine research in different areas. In fact, some of Ivan's best results came out by mapping some ideas from practical areas toward fundamental sciences and viceversa, namely, by mapping ideas from fundamental sciences into ideas related to practical areas. Ivan Arraut is then a multidisciplinary researcher, teaching Physics and Mathematics at USJ in Macau. His main research characteristic is originality and simplicity, trying to find the simplest explanation for unexplained phenomena. With this style, he has received 13 academic prizes and/or recognitions from different institutions around the world during his career, including grants, scholarships, commendable thesis awards, fellowships, recognitions coming from journals, among others. Among the most special recognitions to remark, Ivan Arraut was the third best student in the national exam (ECAES) in Colombia, receiving a recognition from the president of Colombia (Alvaro Uribe) by then. Ivan Arraut received a prize from the journal Nature, for his presentation at the conference "Horizons of Quantum Physics", organized in Taipei in 2012. He also received the prestigious JSPS fellow and the CAS PIFI fellow for Post-Doctoral studies, among other important recognitions.
Ivan Arraut is considered a respected scientist worldwide. All his achievements can be read in the Section "Publications", attached below this biography.
Ivan Arraut has a long history with 19 years of research experience and more than 8 years of teaching experience in different universities.
Publications
I.
REFEREED JOURNALS:
1).
Ivan Arraut, “Solving the Dark
Energy problem via symmetry constraints”, Eur.Phys.J.C 85 (2025) 5, 475.
2).
I. Arraut, D. Batic and M. Nowakowski, “Comparing two approaches to Hawking
radiation of Schwarzschild-de Sitter Black Holes”. Class.Quant.Grav.26:125006,
2009. (Q1), SJR=1.23. Impact Factor=3.5, H-index=188.
3).
I. Arraut, D. Batic and M. Nowakowski, “A noncommutative model for a
mini Black Hole”. Class.Quant.Grav.26:245006, 2009. (Q1), SJR=1.23. Impact Factor=3.5, H-index=188.
4).
Hideo Kodama and Ivan Arraut, “Stability of the Schwarzschild-de Sitter
black hole in the dRGT massive gravity theory”, Prog. Theor. Exp. Phys.
(2014)023E02. (Q1), SJR=2.48. Impact factor=7.492, H-index=52.
5).
Ivan Arraut, “Komar energy function in the de-Rham-Gabadadze-Tolley
non-linear theory of massive gravity”, Phys.Rev. D90 (2014) 12, 124082. (Q1), SJR=1.59. Impact factor=4.6, H-index=393.
6).
Ivan Arraut, “Path-integral derivation of black-hole radiance inside the
dRGT formulation of massive gravity”, Eur.Phys.J. C77 (2017) no.8, 501. (Q1), SJR=1.45. Impact factor=4.2, H-index=193.
7). Wilson
Rosado and Ivan Arraut, “Comment
on “Generalized James’effective Hamiltonian method””, Physical Review A 108 (6), 066201. (Q1), SJR=1.08. Impact factor=2.6, H-index=296.
8). Ivan Arraut, “The counting of
Nambu-Goldstone bosons in a non-Hermitian field theory”, Eur.Phys.J.C 80 (2020) 9, 873. (Q1),
SJR=1.45. Impact
factor=4.2, H-index=193.
9). Juan
Banda, Ariel Ruiz, Laura Montoya and Ivan Arraut, “Latin X in AI Research”,
Neural Comput &
Applic (2023).
(Q1),
SJR=1.26. Impact
factor=4.5, H-index=130.
10).
Ivan Arraut, “The astrophysical scales set by the cosmological constant,
black-hole Thermodynamics and non-linear massive gravity”, Universe 3 (2017)
no.2, 45. (Q1), SJR=0.78. Impact
factor=2.5, H-index=40.
11).
Ivan Arraut, “The black-hole radiation in massive gravity”, Universe 4
(2018) no.2, 27. (Q1), SJR=0.78. Impact factor=2.5, H-index=40.
12).
Ivan Arraut, “The dynamical origin of the graviton mass”, Universe 5 (2019) 166. (Q1), SJR=0.78. Impact factor=2.5, H-index=40.
13). Ivan
Arraut, Carlos Segovia and Wilson Rosado, “The Hawking Radiation in Massive Gravity: Path Integral
and the Bogoliubov Method”, Universe 9 (2023) 5, 228. (Q1),
SJR=0.78. Impact
factor=2.5, H-index=40.
14). Ivan
Arraut, Wilson Rosado and Victor
Leong, “Revenue management in airlines and External factors affecting
decisions”, Mathematics 2024, 12(6),
847. (Q1 in Mathematics),
SJR=0.48.
Impact factor=2.3, H-index=68.
15). Ivan Arraut, Alexandre
Lobo and Sergio Gomes, “The probability flow in the Stock market and Spontaneous
symmetry breaking in Quantum Finance”, Mathematics 2021, 9, 277. (Q1 in Mathematics), SJR=0.48.
Impact factor=2.3, H-index=68.
16). Ivan
Arraut, “Local equivalence of the Black Scholes and Merton-Garman
equations”, (Accepted for publication in
Axioms). Impact factor=1.9,
H-index=33.
17). Ivan Arraut, “The
Quantum Yang Baxter conditions: The fundamental relations behind the
Nambu-Goldstone theorem”, Symmetry 11 (2019) 803. (Q1),
SJR=0.49. Impact
factor=2.2, H-index=90.
18).
Ivan Arraut and Diana Diaz, “On the loss of learning capability inside
an arrangement of neural networks: The bottleneck effect in Black-Holes”, Symmetry 2020,
12, 1484. (Q1), SJR=0.49.
Impact factor=2.2, H-index=90.
19). Ivan Arraut, “Hawking radiation as a manifestation of spontaneous
symmetry breaking”,
Symmetry 16 (2024) 519. (Q1), SJR=0.49. Impact factor=2.2, H-index=90.
20).
M. Nowakowski and I. Arraut, “The minimum and maximum temperature of
Black Body radiation”. Mod. Phys. Lett. A, Vol. 24, No. 26 (2009) pp.
2133-2137. (Q2), SJR=0.4. Impact factor=1.5, H-index=89.
21).
I. Arraut, D. Batic and M. Nowakowski, “Maximal extension of the
Schwarzschild spacetime inspired by noncommutative geometry”. J.Math.Phys. 51
(2010) 022503. (Q2), SJR=0.57. Impact
factor=1.2, H-index=122.
22).
Ivan Arraut, “About the propagation of the Gravitational Waves in an
asymptotically deSitter space: Comparing 2 points of view”. Mod. Phys. Lett. A
28 (2013), 1350019. (Q2), SJR=0.4. Impact factor=1.5, H-index=89.
23).
Ivan Arraut, “Can a non-local model of gravity reproduce Dark Matter
effects in agreement with MOND?” Int. J. Mod. Phys. D 23, No. 1 (2014). (Q2), SJR0.614=. Impact factor=1.8, H-index=93.
24).
I. Arraut, “On the Black Holes in alternative theories of gravity: The
case of nonlinear massive gravity”, Int.J.Mod.Phys. D24 (2015) 1550022. (Q2), SJR=0.614. Impact factor=1.8, H-index=93.
25).
I. Arraut, “On the apparent loss of predictability inside the
de-Rham-Gabadadze-Tolley non-linear formulation of massive gravity: The Hawking
radiation effect”. Europhys.Lett. 109 (2015) 0002. (Q2), SJR=0.5. Impact factor=1.8,
H-index=174.
26).
I. Arraut, “The graviton Higgs mechanism”. Europhys.Lett. 111 (2015)
61001. (Q2), SJR=0.5. Impact factor=1.8, H-index=174.
27).
Ivan Arraut and Kaddour Chelabi, “Vacuum degeneracy: Multiplicity of
fundamental scales”, Mod.Phys.Lett. A32 (2017) no.21, 1750112. (Q2), SJR=0.4. Impact factor=1.5, H-index=89.
28).
Ivan Arraut and Kaddour Chelabi, “Non-linear massive gravity as a
gravitational sigma model”, Europhys.Lett. 115 (2016) no.3, 31001. (Q2), SJR=0.5. Impact factor=1.8, H-index=174.
29).
Ivan Arraut and Carlos Segovia, “A q-deformed Bogoliubov transformations”,
Phys.Lett. A382 (2018) 464-466. (Q2),
SJR=0.48. Impact factor=2.3,
H-index=189.
30).
Ivan Arraut, “The Nambu-Goldstone theorem in non-relativistic systems”, Int.J.Mod.Phys.
A32 (2017) 1750127. (Q2), SJR=051. Impact factor=1.4, H-index=108.
31).
Ivan Arraut, “The origin of the mass of the Nambu-Goldstone bosons”,
Int.J.Mod.Phys. A32 (2018) 1850041. (Q2),
SJR=051. Impact factor=1.4,
H-index=108.
32).
Ivan Arraut, “Black-Hole evaporation from the perspective of neural
networks”, 2018 EPL 124 50002. (Q2),
SJR=0.5. Impact factor=1.8,
H-index=174.
33). Ivan Arraut, Alan Au, Alan Tse and
Carlos Segovia, “The connection between multiple prices of an Option at a
given time with single prices defined at different times: The concept of
weak-value in quantum finance”, Physica A, Vol. 526, 121028, (2019). (Q2), SJR=0.66. Impact factor=2.8, H-index=187.
34).
Ivan Arraut, Alan Au and Alan Tse, “Spontaneous symmetry breaking in
Quantum Finance”, EPL 131
(2020) 6, 68003. (Q2), SJR=0.5. Impact
factor=1.8, H-index=174.
35). Ivan Arraut, “Black-Hole evaporation and
Quantum depletion in Bose-Einstein condensates”, Mod.Phys.Lett.A
2150006 2020. (Q2),
SJR=0.4. Impact
factor=1.5, H-index=89.
36). Ivan
Arraut, “Gauge symmetries and the Higgs Mechanism in Quantum Finance”, 2023 EPL 143 42001. (Q2),
SJR=0.5.
Impact factor=1.8, H-index=174.
37). Ivan
Arraut, “The Tully-Fisher’s law and dark matter effects derived via
modified symmetries”, 2023 EPL 144
29003. (Q2),
SJR=0.5.
Impact factor=1.8, H-index=174.
38). Ivan Arraut, “The cosmological constant
emerging from a symmetry invariant”, to appear at MPLA, (Q2), SJR=0.4. Impact factor=1.5, H-index=89.
39). Ivan Arraut, “Reply to the "Comment on The Tully-Fisher
law and dark matter effects derived via modified symmetries" by I. Arraut”, 2024 EPL https://doi.org/10.1209/0295-5075/ad6180. (Q2),
SJR=0.5. Impact
factor=1.8, H-index=174.
40). Ivan
Arraut and Wing Chi Yu, “Order
parameter conditions from mutual information and symmetry conditions”, Int. Journ. Mod. Phys. B (2025) 2550083. (Q3), SJR=0.3. Impact factor=2.6, H-index=81.
41).
M. Nowakowski and I. Arraut, “The fate of a gravitational wave in de-Sitter
spacetime”. Acta Phys.Polon. B41 (2010) 911-925. (Q3),
SJR=0.23. Impact factor=0.9, H-index=67.
42).
I. Arraut, D. Batic and M. Nowakowski, “Velocity and velocity bounds in
static spherically symmetric metrics”. Central Eur.J.Phys. 9 (2011) 926-938. Note: Journal changed its name to “Open
Physics”. (Q3), SJR=0.3. Impact factor=1.8, H-index=45.
43).
Ivan Arraut, “A possible solution to
the Black Hole information paradox”, AppliedMath 2025, 5(1),
4.
44).
Ivan Arraut, “MOND formulation
emerging from General Relativity”, Modern Physics
Letters A, 2550125.
45). Ivan
Arraut, “The solution to the Hardy’s paradox”, Condens. Matter 2025,
10(3), 45.
II.
PROCEEDING WORKS:
1).
M. Nowakowski and I. Arraut, “Local effects of the
Cosmological Constant”, in proceeding of the International Conference on
“Problems of practical Cosmology”, ST. PETESBURG, RUSSIA, 23-27 JUNE 2008,
Published by THE RUSSIAN GEOGRAPHICAL SOCIETY, SL. PETESBURG, 2008, ISBN
978-5-902632-06-1.
2).
M. Nowakowski and I. Arraut, “LIVING WITH LAMBDA”, BRAZILIAN JOURNAL OF
PHYSICS, 38 No. 3B. (2008). (Q4), SJR=0.19.
Impact factor=1.5, H-index=54.
3).
I. Arraut, “On the Black Holes in alternative theories of gravity: The
case of nonlinear massive gravity”, Springer Proc. Phys. 170 (2016) 63-68. SJR=0.14; H-index=23.
III.
OTHER PAPERS:
1).
Ivan Arraut, “The Planck Scale as a duality of the Cosmological Constant”,
arXiv:1205.6905[gr-qc]. (Poster presentation-Nature Prize winner, in the
conference Horizons for Quantum Physics, organized in Taipei, October, 2012).
2). JAL
Marques, SJ Fong, G Li, I Arraut, FNB Gois and JX Neto, “Research and Technology
Development Achievements During the COVID-19 Pandemic—An Overview”, Epidemic Analytics for
Decision Supports in COVID19 Crisis, 1-15.
3). I Arraut, JAL Marques, SJ Fong, G Li,
FNB Gois and JX Neto, “A quantum field formulation
for a pandemic propagation”, Epidemic Analytics for Decision
Supports in COVID19 Crisis, 141-158.
IV). INDEX h:
a). h=14 in agreement with Inspire hep:
http://inspirehep.net/search?ln=en&p=au+Ivan+Arraut&of=hb&action_search=Search&sf=earliestda te&so=d
b). h=15 in agreement with Google scholars: https://scholar.google.co.jp/citations?user=md3hpM4AAAAJ&hl=es
c). h=16 in Research Gate web page: https://www.researchgate.net/profile/Ivan_Arraut IV
d). h=13 in Scopus
V). GUEST EDITOR FOR THE FOLLOWING SPECIAL ISSUES:
1). Special Issue "Game and Decision Theory Applied to Business, Economy and Finance", https://www.mdpi.com/journal/mathematics/special_issues/Game_Decis_Theory
2). Special Issue "Topological Aspects of Quantum Gravity and Quantum Information Theory", https://www.mdpi.com/journal/symmetry/special_issues/Topological_Aspects_Quantum_Gravity_Quantum_Information_Theory
VI). REFEREE OF THE FOLLOWING JOURNALS:
1). Mathematics (MDPI).
2). Symmetry (MDPI).
3). Universe (MDPI).
4). Modern Physics Letters A (World Scientific).
5). Modern Physics Letters B (World Scientific).
6). Classical and Quantum Gravity (IOP).
7). Applied Soft Computing (Elsevier).
8). Physica A (Elservier).
9). Sustainability (MDPI).
10). Expert Systems With Applications (Elsevier).
VII). CONFERENCE CHAIR IN MACHINE LEARNING:
1). LXAI at ICML 2020, online, https://icml.cc/Conferences/2020/ScheduleMultitrack?event=7087
2). LXAI at Neurips 2020, online, https://neurips.cc/virtual/2020/public/affinity_workshop_19450.html
3). LXAI at ICML 2023, Honolulu-Hawaii, https://www.latinxinai.org/icml-2023
VIII). CONFERENCE CHAIR IN OTHER EVENTS:
Organizer of workshops and conferences in Physics in Japan.
IX). ACADEMIC ACHIEVEMENTS:
*2025 (October): Most read preprint in Macau, in agreement with the Researchgate database.
*2025 (June): Top100 cited author in Modern Physics Letters A (World Scientific).
*2023-2024 Top 100 cited scientists during March 2024 and December 2023 in agreement with EuroPhysicsLetters (IOP journal).
*2023: Editor's choice article from the journal EuroPhysics Letters from IOP.
*2019: Outstanding reviewer award from the journal Universe.
*2018: Top reviewer for the Journal Classical and Quantum Gravity.
*2015: Former CAS Post-Doctoral (PIFI) fellow at Beijing, China.
*2015: Former JSPS Post-Doctoral fellow at Tokyo, Japan.
*2013: Former-Research Assistant at KEK High-Energy Research Organization/Tsukuba (Japan).
*2012: Nature Physics Poster Prize, received in the conference “HORIZONS of QUANTUM PHYSICS” (Taipei: October 14th-18th, 2012).
*2010: PhD (Former MEXT fellow at Osaka University, Japan).
*2008: Commendable thesis Award (Equivalent to Laureate) from the Master's degree at Universidad de Los Andes (Colombia).
*2005: Scholarship for Postgraduate studies (Master degree), provided by Universidad de Los Andes (Colombia).
*2004: Third best student in Colombia in 2003 for the major of Mechanical Engineering, in agreement with ICFES (National institute for Education).
Modules
Year 2
Year 1 Bachelor
This learning background of Business Math is desirable. This module provides an introduction of basic concepts relates do probability and statistics, and motivates students to build skills in data collection and analysis. Topics covered include statistics and data analysis, probability, random variables and probability distributions, mathematical expectation, some discrete probability distributions, some continuous probability distributions, functions of random variables, fundamental sampling distributions and data descriptions, sample estimation problems, tests of hypotheses, simple linear regression and correlation, experiments and fractions, as well as statistical quality control.
General Physics provides an introduction to the basic principles, concepts, and methodologies required to understand the physical phenomena that govern everyday life.
Topics as kinematics, dynamics, gravitation, motion, momentum, energy, electricity and magnetism, wave motion, and optics will be covered.
This module has a laboratory-based experimentation component where students will explore natural phenomena by developing hypothesis, observing, measuring and collecting data, and interpreting and reporting the results. Students will work in groups on laboratory experiments to stimulate the thoughtful discussion and interpretation of their results and observations. The acquisition of science communication skills will also be promoted by written and oral reporting of results.
This module reviews and introduces important topics and theories in mathematics that are relevant to everyday science and engineering. In this module selected issues in Arithmatic and Number Theory; Algebra and Systems of equations; Trigonometry and Coordinate Systems; Functions and Series; Calculus and Partial Differential Equations are considered. In all cases, “real world” applications of mathematics are emphasized.
This module is provided as the first module on calculus. It starts with real-world examples of calculus, explains why calculus works, and introduces the two big ideas of calculus: differentiation and integration. The discussion also covers common functions and their graphs, limits and continuity, integration and approximating area.
Having the module “Calculus 1” as the prerequisite, this module continues the discussion on more advanced topics in calculus, such as parametric equations, differential equations, and infinite series sequences and series, polar coordinates and multivariable calculus.
This course is an introduction to computers and related technologies, including basic computer concepts/terminology and hands-on experience in the use of spreadsheets, programming language and database applications. The role of Information Systems in organizations is also discussed. In addition, an introduction to the use of data communications and other automation systems, including the study of local and wide area networks, voice and electronic mail, video conferencing, and other automation tools are examined.
This course is an introduction to computers and related technologies, including basic computer concepts/terminology and hands-on experience in the use of spreadsheets, programming language and database applications. The role of Information Systems in organizations is also discussed. In addition, an introduction to the use of data communications and other automation systems, including the study of local and wide area networks, voice and electronic mail, video conferencing, and other automation tools are examined.
This course is an introduction to computers and related technologies. Basic computer concepts, terminology and software applications will be discussed.
Year 2 Bachelor
This module requires a background of calculus as prerequisite. It provides an introduction to basic probability and statistics, and motivates students to build skills in data collection and analysis. Topics covered include statistics and data analysis, probability, random variables and probability distributions, mathematical expectation, some discrete probability distributions, some continuous probability distributions, functions of random variables, fundamental sampling distributions and data descriptions, sample estimation problems, tests of hypotheses, simple linear regression and correlation, experiments and fractions, as well as statistical quality control.
Probability and Statistics - LIS222 / LAR224
This module requires a background of calculus as prerequisite. It provides an introduction to basic probability and statistics, and motivates students to build skills in data collection and analysis. Topics covered include statistics and data analysis, probability, random variables and probability distributions, mathematical expectation, some discrete probability distributions, some continuous probability distributions, functions of random variables, fundamental sampling distributions and data descriptions, sample estimation problems, tests of hypotheses, simple linear regression and correlation, experiments and fractions, as well as statistical quality control.
This module introduces basic concepts of algorithmic problem solving and logical thinking. It covers problem solving strategies, basic data structures, as well as data and procedural abstraction. Through step-by-step practice, students learn basic skill to write their own code in an easy-to-master programming language for simple problem solving, and to perform simple debugging and testing. It serves as the first programming module and requires no prerequisite.
This module covers basic usages of the latest Web technologies and tools such as Dreamweaver, Flash, XML, and SMIL. It also helps students to discover what makes an attractive Web site, the traps to avoid in Web site design, and the keys to a successful Web site. Students will learn to create and customize their own Web pages, and will become competent on the basics of multimedia implementation on Web.
LIS229 Basic Web Development and Multimedia (1.5cr) / LIS248 Basic Web Development and Multimedia (2cr)
This module will focus on the study of web and multimedia technologies.
The students will be able to understand what is the web, what is multimedia and how do they work. It’s a hands-on module that requires the use of the computer as an artistic and creative tool.
This module will also prepare students, with the basic technical and aesthetical skills, on how to create web and multimedia products with visually dynamic and creative graphics through best working practices. Students will design web pages by using Adobe Photoshop, HTML and CSS files by editing them by using text editors and other tools. Usability principles will be one of the considerations when designing web pages.
Year 3 Bachelor
This module provides students a foundation in conducting business in the new economy. It presents a framework for the study and practice of electronic commerce with business strategy at the core surrounded by four infrastructures; the technology infrastructure that underlies the Internet, the media infrastructure that provides the content for businesses, public policy regulations that provide both opportunities and constraints, and the capital infrastructure that provides the money and capital to run the businesses. The latest information technologies and tools that can support E-commerce will be discussed.
This module provides students a foundation in conducting business in the new economy. It presents a framework for the study and practice of electronic commerce with business strategy at the core surrounded by four infrastructures; the technology infrastructure that underlies the Internet, the media infrastructure that provides the content for businesses, public policy regulations that provide both opportunities and constraints, and the capital infrastructure that provides the money and capital to run the businesses. The latest information technologies and tools that can support E-commerce will be discussed.
This module provides the basic ideas of information systems and their application in business and management areas. Topics covered include the strategic role of information systems in organizations and management, electronic commerce and electronic business, managing hardware and software assets, managing data resources, the Internet and the new information technology infrastructure, redesigning the organization with information systems, managing knowledge, enhancing management decision making, information system security and control, ethical and social impact of information systems.
Year 4 Bachelor
This course provides students with hands-on experience with marketing research. Marketing research is an organized way of developing and providing information for decision-making purposes. All steps involved in the marketing research process - problem definition, research design, data collection methods, questionnaire design, measurement, sampling, data analysis, data interpretation, and reporting - are discussed.
Year 1 Doctorate
This module provides an overview of methods and techniques for quantitative research, including the concepts and practical applications of descriptive and inferential statistics, with the aim to motivate the students to build skills in data collection and analysis for their Ph.D. research. The topics covered include general concepts such as sampling strategies, evaluations of reliability and validity of data, and the connection between the research question/hypothesis definition and quantitative data analysis. Different types of statistical tests and techniques are presented and computational tools (Excel, R, and SPSS) are used in practical workshops.
This module provides an overview of methods and techniques for quantitative research, including the concepts and practical applications of descriptive and inferential statistics, with the aim to motivate the students to build skills in data collection and analysis for their Ph.D. research. The topics covered include general concepts such as sampling strategies, evaluations of reliability and validity of data, and the connection between the research question/hypothesis definition and quantitative data analysis. Different types of statistical tests and techniques are presented and computational tools (Excel, R, and SPSS) are used in practical workshops.
This module provides an overview of methods and techniques for quantitative research, including the concepts and practical applications of descriptive and inferential statistics, with the aim to motivate the students to build skills in data collection and analysis for their Ph.D. research. The topics covered include general concepts such as sampling strategies, evaluations of reliability and validity of data, and the connection between the research question/hypothesis definition and quantitative data analysis. Different types of statistical tests and techniques are presented and computational tools (Excel, R, and SPSS) are used in practical workshops.
This module provides an overview of methods and techniques for quantitative research, including the concepts and practical applications of descriptive and inferential statistics, with the aim to motivate the students to build skills in data collection and analysis for their Ph.D. research. The topics covered include general concepts such as sampling strategies, evaluations of reliability and validity of data, and the connection between the research question/hypothesis definition and quantitative data analysis. Different types of statistical tests and techniques are presented and computational tools (Excel, R, and SPSS) are used in practical workshops.
This module provides an overview of methods and techniques for quantitative research, including the concepts and practical applications of descriptive and inferential statistics, with the aim to motivate the students to build skills in data collection and analysis for their Ph.D. research. The topics covered include general concepts such as sampling strategies, evaluations of reliability and validity of data, and the connection between the research question/hypothesis definition and quantitative data analysis. Different types of statistical tests and techniques are presented and computational tools (Excel, R, and SPSS) are used in practical workshops.
This module provides an overview of methods and techniques for quantitative research, including the concepts and practical applications of descriptive and inferential statistics, with the aim to motivate the students to build skills in data collection and analysis for their Ph.D. research. The topics covered include general concepts such as sampling strategies, evaluations of reliability and validity of data, and the connection between the research question/hypothesis definition and quantitative data analysis. Different types of statistical tests and techniques are presented and computational tools (Excel, R, and SPSS) are used in practical workshops.
This module provides an overview of methods and techniques for quantitative research, including the concepts and practical applications of descriptive and inferential statistics, with the aim to motivate the students to build skills in data collection and analysis for their Ph.D. research. The topics covered include general concepts such as sampling strategies, evaluations of reliability and validity of data, and the connection between the research question/hypothesis definition and quantitative data analysis. Different types of statistical tests and techniques are presented and computational tools (Excel, R, and SPSS) are used in practical workshops.
This module provides an overview of methods and techniques for quantitative research, including the concepts and practical applications of descriptive and inferential statistics, with the aim to motivate the students to build skills in data collection and analysis for their Ph.D. research. The topics covered include general concepts such as sampling strategies, evaluations of reliability and validity of data, and the connection between the research question/hypothesis definition and quantitative data analysis. Different types of statistical tests and techniques are presented and computational tools (Excel, R, and SPSS) are used in practical workshops.
This module provides an overview of methods and techniques for quantitative research, including the concepts and practical applications of descriptive and inferential statistics, with the aim to motivate the students to build skills in data collection and analysis for their Ph.D. research. The topics covered include general concepts such as sampling strategies, evaluations of reliability and validity of data, and the connection between the research question/hypothesis definition and quantitative data analysis. Different types of statistical tests and techniques are presented and computational tools (Excel, R, and SPSS) are used in practical workshops.
Year 1 Master
The purpose of this module is to provide the necessary skills to value and to employ options, futures, and related financial contracts. Topics covered include the valuation of futures contracts on stock indices, on commodities and Treasury instruments; the valuation of options; empirical evidence; strategies with respect to these assets; dynamic asset allocation strategies; swaps; and the use (and misuse) of derivatives in the context of corporate applications.
Students will become proficient in current methods of conducting research in the field: problem definition, construction of hypotheses, research design, sampling, data collection and evaluation, and interpretation of findings.
Students will become proficient in current methods of conducting research in Public Administration: problem definition, construction of hypotheses, research design, sampling, data collection and evaluation, and interpretation of findings.