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Mathematical Psychology

This project investigates mathematical psychology's historical and philosophical foundations to clarify its distinguishing characteristics and relationships to adjacent fields. Through gathering primary sources, histories, and interviews with researchers, author Prof. Colin Allen - University of Pittsburgh [1, 2, 3] and his students  Osman Attah, Brendan Fleig-Goldstein, Mara McGuire, and Dzintra Ullis have identified three central questions: 

  1. What makes the use of mathematics in mathematical psychology reasonably effective, in contrast to other sciences like physics-inspired mathematical biology or symbolic cognitive science? 
  2. How does the mathematical approach in mathematical psychology differ from other branches of psychology, like psychophysics and psychometrics? 
  3. What is the appropriate relationship of mathematical psychology to cognitive science, given diverging perspectives on aligning with this field? 

Preliminary findings emphasize data-driven modeling, skepticism of cognitive science alignments, and early reliance on computation. They will further probe the interplay with cognitive neuroscience and contrast rational-analysis approaches. By elucidating the motivating perspectives and objectives of different eras in mathematical psychology's development, they aim to understand its past and inform constructive dialogue on its philosophical foundations and future directions. This project intends to provide a conceptual roadmap for the field through integrated history and philosophy of science.



The Project: Integrating History and Philosophy of Mathematical Psychology



This project aims to integrate historical and philosophical perspectives to elucidate the foundations of mathematical psychology. As Norwood Hanson stated, history without philosophy is blind, while philosophy without history is empty. The goal is to find a middle ground between the contextual focus of history and the conceptual focus of philosophy.


The team acknowledges that all historical accounts are imperfect, but some can provide valuable insights. The history of mathematical psychology is difficult to tell without centering on the influential Stanford group. Tracing academic lineages and key events includes part of the picture, but more context is needed to fully understand the field's development.


The project draws on diverse sources, including research interviews, retrospective articles, formal histories, and online materials. More interviews and research will further flesh out the historical and philosophical foundations. While incomplete, the current analysis aims to identify important themes, contrasts, and questions that shaped mathematical psychology's evolution. Ultimately, the goal is an integrated historical and conceptual roadmap to inform contemporary perspectives on the field's identity and future directions.



The Rise of Mathematical Psychology



The history of efforts to mathematize psychology traces back to the quantitative imperative stemming from the Galilean scientific revolution. This imprinted the notion that proper science requires mathematics, leading to "physics envy" in other disciplines like psychology.


Many early psychologists argued psychology needed to become mathematical to be scientific. However, mathematizing psychology faced complications absent in the physical sciences. Objects in psychology were not readily present as quantifiable, provoking heated debates on whether psychometric and psychophysical measurements were meaningful.


Nonetheless, the desire to develop mathematical psychology persisted. Different approaches grappled with determining the appropriate role of mathematics in relation to psychological experiments and data. For example, Herbart favored starting with mathematics to ensure accuracy, while Fechner insisted experiments must come first to ground mathematics.


Tensions remain between data-driven versus theory-driven mathematization of psychology. Contemporary perspectives range from psychometric and psychophysical stances that foreground data to measurement-theoretical and computational approaches that emphasize formal models.


Elucidating how psychologists negotiated to apply mathematical methods to an apparently resistant subject matter helps reveal the evolving role and place of mathematics in psychology. This historical interplay shaped the emergence of mathematical psychology as a field.



The Distinctive Mathematical Approach of Mathematical Psychology



What sets mathematical psychology apart from other branches of psychology in its use of mathematics?


Several key aspects stand out:

  1. Advocating quantitative methods broadly. Mathematical psychology emerged partly to push psychology to embrace quantitative modeling and mathematics beyond basic statistics.
  2. Drawing from diverse mathematical tools. With greater training in mathematics, mathematical psychologists utilize more advanced and varied mathematical techniques like topology and differential geometry.
  3. Linking models and experiments. Mathematical psychologists emphasize tightly connecting experimental design and statistical analysis, with experiments created to test specific models.
  4. Favoring theoretical models. Mathematical psychology incorporates "pure" mathematical results and prefers analytic, hand-fitted models over data-driven computer models.
  5. Seeking general, cumulative theory. Unlike just describing data, mathematical psychology aspires to abstract, general theory supported across experiments, cumulative progress in models, and mathematical insight into psychological mechanisms.


So while not unique to mathematical psychology, these key elements help characterize how its use of mathematics diverges from adjacent fields like psychophysics and psychometrics. Mathematical psychology carved out an identity embracing quantitative methods but also theoretical depth and broad generalization.



Situating Mathematical Psychology Relative to Cognitive Science



What is the appropriate perspective on mathematical psychology's relationship to cognitive psychology and cognitive science? While connected historically and conceptually, essential distinctions exist.


Mathematical psychology draws from diverse disciplines that are also influential in cognitive science, like computer science, psychology, linguistics, and neuroscience. However, mathematical psychology appears more skeptical of alignments with cognitive science.


For example, cognitive science prominently adopted the computer as a model of the human mind, while mathematical psychology focused more narrowly on computers as modeling tools.


Additionally, mathematical psychology seems to take a more critical stance towards purely simulation-based modeling in cognitive science, instead emphasizing iterative modeling tightly linked to experimentation.


Overall, mathematical psychology exhibits significant overlap with cognitive science but strongly asserts its distinct mathematical orientation and modeling perspectives. Elucidating this complex relationship remains an ongoing project, but preliminary analysis suggests mathematical psychology intentionally diverged from cognitive science in its formative development.


This establishes mathematical psychology's separate identity while retaining connections to adjacent disciplines at the intersection of mathematics, psychology, and computation.



Looking Ahead: Open Questions and Future Research



This historical and conceptual analysis of mathematical psychology's foundations has illuminated key themes, contrasts, and questions that shaped the field's development. Further research can build on these preliminary findings.

Additional work is needed to flesh out the fuller intellectual, social, and political context driving the evolution of mathematical psychology. Examining the influences and reactions of key figures will provide a richer picture.

Ongoing investigation can probe whether the identified tensions and contrasts represent historical artifacts or still animate contemporary debates. Do mathematical psychologists today grapple with similar questions on the role of mathematics and modeling?

Further analysis should also elucidate the nature of the purported bidirectional relationship between modeling and experimentation in mathematical psychology. As well, clarifying the diversity of perspectives on goals like generality, abstraction, and cumulative theory-building would be valuable.

Finally, this research aims to spur discussion on philosophical issues such as realism, pluralism, and progress in mathematical psychology models. Is the accuracy and truth value of models an important consideration or mainly beside the point? And where is the field headed - towards greater verisimilitude or an indefinite balancing of complexity and abstraction?

By spurring reflection on this conceptual foundation, this historical and integrative analysis hopes to provide a roadmap to inform constructive dialogue on mathematical psychology's identity and future trajectory.


The SDTEST® 



The SDTEST® is a simple and fun tool to uncover our unique motivational values that use mathematical psychology of varying complexity.



The SDTEST® helps us better understand ourselves and others on this lifelong path of self-discovery.


Here are reports of polls which SDTEST® makes:


1) Izenzo zeenkampani ngokunxulumene nabasebenzi kwinyanga ephelileyo (ewe / hayi)

2) Izenzo zeenkampani ngokunxulumene nabasebenzi kwinyanga ephelileyo (inyani kwi%)

3) Uloyiko

4) Iingxaki ezinkulu ezijongene nelizwe lam

5) Zeziphi iimpawu kunye nobuchule obasebenzisa kakuhle xa wakha amaqela aphumeleleyo?

6) Google. Izinto ezinokuthi zenziwe ngeqela

7) Izinto eziphambili ngokubaluleka kwabafuna umsebenzi

8) Yintoni eyenza umphathi omkhulu?

9) Yintoni eyenza abantu baphumelele emsebenzini?

10) Ngaba ukulungele ukufumana umvuzo omncinci ukusebenza kude?

11) Ngaba Ubuncinci bukhona?

12) Ubudala bomsebenzi

13) Ubudala ebomini

14) Unobangela wobubi

15) Izizathu zokuba kutheni abantu benikezela (ngo-Anna kubalulekile)

16) Ukuthembana (#WVS)

17) Uvavanyo lwe-Oxford

18) Impilo yengqondo

19) Ingaba liphi ixesha lakho elinomdla?

20) Yintoni oza kuyenza kule veki ukhathalela impilo yakho yengqondo?

21) Ndihlala ndicinga ngexesha lam elidlulileyo, elikhoyo okanye elizayo

22) I-Meiritocy

23) Ubukrelekrele bokwenzela kunye nokuphela kwempucuko

24) Kutheni le nto abantu behlazela?

25) Umahluko wesini ekwakheni ukuzithemba (i-Allensbach)

26) Uvavanyo lwenkcubeko ye Xing.com

27) I-Patrick Lentance Lencn's

28) Uvelwano yi ...

29) Yintoni ebalulekileyo kuba ziingcali ze-IT ekukhetheni umsebenzi?

30) Isizathu sokuba abantu baxhathise utshintsho (nguSiobhán Mchale)

31) Uzilawula njani iimvakalelo zakho? (nge-nawal manafa m.a.)

32) 21 Izakhono ezikuhlawula ngonaphakade (nguYeremiya Teo / 赵汉昇)

33) Inkululeko yokwenyani ...

34) Iindlela ezili-12 zokwakha ukuthembana nabanye (nguJustin Wright)

35) Iimpawu zomsebenzi onetalente (ngeTelenter Institute)

36) Iindlela ezili-10 zokukhuthaza iqela lakho

37) IAlgebra yesazela (nguVladimir Lefebvre)

38) Amathuba amathathu Ahlukeneyo ekamva (nguGqr. Clare W. Graves)

39) Iintshukumo Zokwakha Ukuzithemba Okungagungqiyo (nguSuren Samarchyan)

40)


Below you can read an abridged version of the results of our VUCA poll “Fears“. The full version of the results is available for free in the FAQ section after login or registration.

Uloyiko

iitshatiUkuhlanganisa
?
Lo msebenzi ubala ngokuzenzekelayo ulungelelwaniso lomgca nolungenamda. Ngaphambi kokwenza uhlalutyo lokulungelelanisa, yenza i-scatterplot ukuqinisekisa ubunjani bobudlelwane. I-Coefficients yokunxibelelana inentsingiselo kuphela ukuba uhlobo lobudlelwane obucingelwayo luqinisekisiwe ngokubonakalayo okanye ngohlalutyo.
VUCA
?
Nantsi imbonakalo yojongano olutsha lwe-Correlation kwitheyibhile ngokwamanqanaba e-Spiral Dynamics apho ukuguquguquka, ukungaqiniseki, ukuntsokotha, kunye nokungaqondakali (V.U.C.A.) kuboniswa ngokuxhomekeka okuhle nokubi phakathi kweempendulo zovoto kunye nemibala yeSpiral Dynamics
Country
Language
-
Mail
Phinda
Uhlobo loNxibelelwano
Linear (Pearson)
Linear (Pearson)
Ayingomgca (Spearman)
Ixabiso elibalulekileyo lomlinganiso wolungelelwaniso
Ukuhanjiswa okuqhelekileyo, nge-william gosset (umfundi)
Ukuhanjiswa okuqhelekileyo, nge-william gosset (umfundi)
Ukusasazwa okuqhelekileyo, nge-spearman
UkuhanjiswaAyiqhelekangaAyiqhelekangaAyiqhelekangaEqhelekileyoEqhelekileyoEqhelekileyoEqhelekileyoEqhelekileyo
Yonke imibuzo
Yonke imibuzo
Olona loyiko lwam lukhulu
Olona loyiko lwam lukhulu
Answer 1-
HIV amandla
0.0475
HIV amandla
0.0258
Emibi amandla
-0.0256
HIV amandla
0.0985
HIV amandla
0.0334
Emibi amandla
-0.0109
Emibi amandla
-0.1483
Answer 2-
HIV amandla
0.0217
HIV amandla
0.0011
Emibi amandla
-0.0409
HIV amandla
0.0616
HIV amandla
0.0461
HIV amandla
0.0126
Emibi amandla
-0.0965
Answer 3-
Emibi amandla
-0.0021
HIV amandla
0.0041
Emibi amandla
-0.0478
Emibi amandla
-0.0436
HIV amandla
0.0431
HIV amandla
0.0759
Emibi amandla
-0.0233
Answer 4-
HIV amandla
0.0432
HIV amandla
0.0328
Emibi amandla
-0.0305
HIV amandla
0.0180
HIV amandla
0.0342
HIV amandla
0.0241
Emibi amandla
-0.0973
Answer 5-
HIV amandla
0.0211
HIV amandla
0.1282
HIV amandla
0.0022
HIV amandla
0.0834
HIV amandla
0.0006
Emibi amandla
-0.0097
Emibi amandla
-0.1816
Answer 6-
HIV amandla
0.0045
HIV amandla
0.0164
Emibi amandla
-0.0636
Emibi amandla
-0.0123
HIV amandla
0.0150
HIV amandla
0.0881
Emibi amandla
-0.0366
Answer 7-
HIV amandla
0.0109
HIV amandla
0.0437
Emibi amandla
-0.0683
Emibi amandla
-0.0352
HIV amandla
0.0444
HIV amandla
0.0750
Emibi amandla
-0.0517
Answer 8-
HIV amandla
0.0615
HIV amandla
0.0843
Emibi amandla
-0.0293
HIV amandla
0.0103
HIV amandla
0.0353
HIV amandla
0.0195
Emibi amandla
-0.1367
Answer 9-
HIV amandla
0.0721
HIV amandla
0.1600
Emibi amandla
-0.0010
HIV amandla
0.0613
Emibi amandla
-0.0084
Emibi amandla
-0.0468
Emibi amandla
-0.1753
Answer 10-
HIV amandla
0.0743
HIV amandla
0.0621
Emibi amandla
-0.0159
HIV amandla
0.0222
HIV amandla
0.0390
Emibi amandla
-0.0040
Emibi amandla
-0.1335
Answer 11-
HIV amandla
0.0632
HIV amandla
0.0557
Emibi amandla
-0.0096
HIV amandla
0.0093
HIV amandla
0.0236
HIV amandla
0.0230
Emibi amandla
-0.1245
Answer 12-
HIV amandla
0.0392
HIV amandla
0.1053
Emibi amandla
-0.0396
HIV amandla
0.0354
HIV amandla
0.0269
HIV amandla
0.0279
Emibi amandla
-0.1515
Answer 13-
HIV amandla
0.0739
HIV amandla
0.1015
Emibi amandla
-0.0382
HIV amandla
0.0266
HIV amandla
0.0325
HIV amandla
0.0158
Emibi amandla
-0.1607
Answer 14-
HIV amandla
0.0816
HIV amandla
0.0912
Emibi amandla
-0.0077
Emibi amandla
-0.0161
HIV amandla
0.0041
HIV amandla
0.0119
Emibi amandla
-0.1125
Answer 15-
HIV amandla
0.0547
HIV amandla
0.1296
Emibi amandla
-0.0305
HIV amandla
0.0115
Emibi amandla
-0.0211
HIV amandla
0.0260
Emibi amandla
-0.1180
Answer 16-
HIV amandla
0.0671
HIV amandla
0.0320
Emibi amandla
-0.0347
Emibi amandla
-0.0451
HIV amandla
0.0627
HIV amandla
0.0196
Emibi amandla
-0.0698


Rhweba ngaphandle ku MS Excel
Lo msebenzi uza kufumaneka kwi-vuca yakho yeVUCA
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[1] https://twitter.com/wileyprof
[2] https://colinallen.dnsalias.org
[3] https://philpeople.org/profiles/colin-allen

2023.10.13
FearpersonqualitiesprojectorganizationalstructureRACIresponsibilitymatrixCritical ChainProject Managementfocus factorJiraempathyleadersbossGermanyChinaPolicyUkraineRussiawarvolatilityuncertaintycomplexityambiguityVUCArelocatejobproblemcountryreasongive upobjectivekeyresultmathematicalpsychologyMBTIHR metricsstandardDEIcorrelationriskscoringmodelGame TheoryPrisoner's Dilemma
I-Valerii Kosenko
uMnini weMveliso i-SaaS SDTEST®

U-Valerii wayefaneleka njenge-social pedagogue-psychologist ngo-1993 kwaye ukususela ngoko uye wasebenzisa ulwazi lwakhe kulawulo lweprojekthi.
UValerii wafumana isidanga seMasters kunye neprojekthi kunye nesiqinisekiso somphathi weprogram ngo-2013. Ngexesha lenkqubo yakhe ye-Master, waqhelana neProjekthi yeNdlela yeNdlela (GPM Deutsche Gesellschaft für Projektmanagement e. V.) kunye ne-Spiral Dynamics.
UValerii ngumbhali wokuphonononga ukungaqiniseki kweV.U.C.A. Ingqiqo kusetyenziswa iSpiral Dynamics kunye nezibalo zezibalo kwipsychology, kunye ne-38 yokuvota kumazwe ngamazwe.
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