An Evaluation on the Simplicity of Scientific Theories: A Study

This essay provides an evaluation of the simplicity of scientific theories, exploring the arguments for and against prioritizing simple theories over complex ones. It begins by introducing the concept of Occam's razor and its preference for simplicity, contrasting this with the Bayesian model of evidence, which considers uncertainties based on supporting evidence. The essay delves into criticisms of Occam's razor, the role of simplicity in scientific theories, and the Bayesian model's application. It discusses subjective viewpoints on probability, the influence of belief systems, and how these factors influence the complexity of scientific theories. The essay concludes by suggesting that while simplicity can be valuable, complex theories are also essential for scientific advancement and innovation. The student argues that a balanced approach considering both simple and complex theories is necessary for the best results.

Running head: AN EVALUATION ON THE SIMPLICITY OF SCIENTIFIC THEORIES
An evaluation on the simplicity of scientific theories
Name of the Student
Name of the University
Author Note

1AN EVALUATION ON THE SIMPLICITY OF SCIENTIFIC THEORIES
In this paper, I will argue that the simple theories should be preferred in science over
the complex ones from a subjective point of view using the Bayesian model of evidence in
science. In this paper, I will explore the various standpoints of people criticising the several
versions of the “Occam’s razor” that inherently talks about the preference of the simple
theories over the complex theories that are used in the field of science. As a notion of
conclusion, this assignment strives to reflect that the fact that simplicity in science is not
always justified and the complexity of the scientific theories are required to be considered as
well for deriving the best results.
The advancement of science and technologies has reached a certain height of
standards for over the years. Although the scientific theories have been provided with several
substantial evidences, there have been criticism as well about the level of complexity of these
theories. According to the theory stated by William of Ockham, the theories of science should
be of a level that is not beyond the understanding level of common human beings (Engström
et al.). The Bayesian model however categorises these uncertainties according to the
evidences that supports the level of simplicity in stating the scientific theories. The new
radical views of the confirmation and the evidences of the scientific theories forms a
viewpoint termed as Bayesianism.
The Occam’s razor is based upon the philosophy that was formulated by the William
of Ockham. According to the philosophy, simple theories in the field of science should be
preferred than the theories which are devoted in stating complex explanations as these
explanations require a lot of speculations to be made than the simple theories of science (Van
Den Berg). According to Ockham the abstractions and generalisations were mental concepts
that were basically derived from the perceiving of the particulars and categorising them
among the similarities, derivations, affinities and the kinds of such type (Vapnik). Conception
can be defined as the role of perception of the level of understanding of an individual object

2AN EVALUATION ON THE SIMPLICITY OF SCIENTIFIC THEORIES
in some ways that are corresponding on of the particular concept. However, the abstractions
on the other hand were to be regarded as the objects according to their own state. These
entities termed as universals were one problem among many that was confined towards
making the syllogistic logic more complex, unpretendingly huge and way less powerful than
the much more rationalised system that are used today (Van Den Berg). Ockham’s razor
principally was devised to provide with faith from the rational enquiries but the modern
elaborations of the Occam’s razor states that it is unwise to make a lot of speculations
keeping in mind the name of God (Valkenburg et al.).
There may be various ways in which the simplicity can be regarded as the most
demanding feature in the field of scientific theories. The simpler theories are often regarded
as the easily perceived ones or very much elegant than the theories that are complex in
comparison to these theories (Nola, Robert, and Sankey). The simpler theories of science are
much easier to understand and is more flexible to work with. However, many of the scientists
and the philosophers believe that simplicity is something that cannot be associated with the
relevance of the theories that described in the field of science (Rothe and Peter). Additionally
they believe that simplicity in the genre of science should not be taken into account every
time especially when the researches are taking place absolutely fine and are moving on the
right track of discovery. Instead of this, simplicity should be regarded as one of the main
criteria to evaluate and select from the theories that are in contradiction to the theory that is
being worked upon (Bhaskar and Roy). Simplicity considerations are also considered as the
integral to several methods of standardization that the scientists use to interfere with the
hypotheses from the empirical data that is the most common explanation of this being the
most fitted one.
The Bayesian model or Bayesianism is devoted upon the understanding of the
evidence using the theory of probability that is quite a popular ideology. There is a dedicated

3AN EVALUATION ON THE SIMPLICITY OF SCIENTIFIC THEORIES
formula for the justification of the Bayes’s theorem (Efron and Bradley. This theorem is very
much simple in the field of mathematics and this idea is very simple. Bayesianism is one of
the very best set of ideas that can be used for the explanation of the complexity level of the
scientific theories (Godfrey-Smith). There is one simplest form of the Bayes’s theorem and
the other formula is useful in depicting the benefits in the application of the scientific theories
(Morey et al). These two formulas is based upon the different types of hypotheses and thee
evidences. These two formulas are very much effective in explaining the complexity of the
theories using the theory of probability. The Bayesian model is entirely based upon the
concept about what the audience is about to be experienced with (Salmon and Wesley). The
probabilities for the probabilities of hypotheses are far more controversial since the
computation of these probabilities are based on the priorities of occurrence. Therefore,
although the it is wise to discuss the probabilities of evidence using the theory of probability
it would be unwise to use the same to discuss the probability of the hypotheses.
By going through all the above three definitions of the Occam’s razor, the simplicity
and the Bayesian model, it is understandable that these definitions play a vital role in shaping
up the justification about the interpretation of the complexity of theories in the field of
science and research (Van Den Berg). In due course of the investigation of this subjective
progress, this has been found out the that most of the attempts to analyse the probability have
taken the probabilities to few real and the objective feature of the events. The probability
value is considered as calibrating the opportunity for the happening of some particular event.
It may be that these opportunities somehow happens to be one of the aspects of the event or
its location the world (Popper and Karl). This has also been found out that according to the
subjectivist interpretation of the probabilities are the different degrees of belief. A probability
is confined towards the measurement of the person’s degree of confidence in the truth of
some proposition.

4AN EVALUATION ON THE SIMPLICITY OF SCIENTIFIC THEORIES
The subjectivist interpretation of the probability is not only important in the field of
philosophy but also is equally important in the field of science and economics since it is
central to the decision theory. This has been found that the majority of the philosophers who
are interested in the usage of the Bayes’s theorem to perceive the idea of an evidence, holds a
subjectivist point of view for the various types of probabilities (Berger and James). If not
then the point of view is configured towards the applications of the probability theory to these
set of problems and sometimes more in a generalised approach. Some of these probabilities
are considered as a subjectivist approach because the philosophers feel that the probabilities
are required to be in the order of the Bayes’s theorem. People, who are destined upon
countering these thoughts, think that the concept of subjectivism is the only interpretation of
the probabilities that makes a point anyway (Godfrey-Smith). The debates relating to the
philosophy about Bayesianism also links to the debates about the probability within thin the
mathematical statistics itself.
As mentioned earlier, the subjective interpretation of probability of a certain
individual is based upon the degree of his belief in the propositions or the hypotheses about
the world. The Bayesianism model sometimes treat the people as not the actual people but in
a form of idealized people (Gelman et al). According to the Bayesian point of view, all the
events occurring in the lives are somehow related with the various nodes of probability and as
probability is related with the measurement of chances created for the events there may be
several risks associated with these events. Even the scientific theories are based on the
probability of occurrence. Therefore, the complexity for setting up of each of them must be
considered according to the way they are being stated and not by the degree of complexity
they are associated with (Vehtari et al.). A person’s system of belief within a particular state
of time can be described as a collective mesh of the subjective probabilities. These subjective
probabilities are focussed towards the concern of the respective person’s behaviour.

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The people who strongly have a strong belief on the Bayesian’s model acclaims to
state one of the theory that is entirely based on the fact the a person’s total network for the
degrees of belief is confined to a certain standpoint and depicts the calculative implications of
reflecting a point that is rational in nature (Godfrey-Smith). These people who are strongly
agreeable to the Bayesian model argue that a coherent set of the degrees of belief is bound to
follow the standard rules of the mathematics of probability (Rigoux et al.). The treatment of
the probabilities are acted upon by the support of simple series axioms. These axioms say that
all the probabilities are in the number of 0 and 1. According to the second axiom, it says that
if a proposition is a tautology then it has the probability of 1. The third axiom say that if one
hypotheses h and h* are exclusive alternatives then P(h-or-h*) = P(h) + P(h*). The fourth
axiom say that P(h|j) = P(h&j)/P(j) if P(j) > 0. The Bayes’s theorem is the consequence of the
fourth axiom that has been mentioned here. The Bayes’s theorem can be broken down as P(h|
j)P(j) and as P(j|h)P(h). Therefore, these two equations are equal to one another and the
Bayes’s theorem follows trivially.
The argument that has been inferred from these two axioms state that if the degrees of
belief do not follow the principles of the probability of calculus then there are possible
gambling situations in which the person is guaranteed to fail no matter if the outcome of the
event is positive or negative. The notion of guarantee is there because these are the situations
in which an individual entirely depends upon the randomness of the event and not even a
slightest inclination is tilted towards the positive outcome of the event through which the
individual is capable of favouring himself (Marin et al.). Thus in the context of science it can
be said that the complexity of the scientific theories does not only depends on the
interpretation of thoughts but also on the methods through which these thoughts are being
arranged in a manner that will be suitable for the successful outcome of the scientific
research.

6AN EVALUATION ON THE SIMPLICITY OF SCIENTIFIC THEORIES
Thus in the summing up of this section in the most holistic approach, it can be said
that according to the subjective interpretation of probability, there is not a single way out.
These are the outlets that only a single set of degrees of belief can be considered as the belief
and has the capability of moving towards the ideal facts of probability of an event (Godfrey-
Smith). Therefore it is necessary to consider both of the degrees of probability. Relating with
the context of science, it can be said that the Occam’s razor is partially true where certain
simpler ideas of the theories can be preferred. In addition to all these, the wider concept
demands the consideration of the complex theories of science as well so as to go in par with
the development of new ideas and innovations in the field of scientific researches (Friston et
al.). These are ways by which the issues arising with the complexity of the theories can be
judged with a series of justification. Though some of the Bayesian people considers both the
objective and the subjective agreements of interpretation of the probability of the scientific
theories.
From the sections mentioned in the above parts of this essay, it can be said that the
Bayesian model is helpful in determining the randomness of the complexity level of the
several scientific theories. Accordingly, it also states that while working with the deductions
drawn by the Occam’s model are true but the model is not suitable for every cases in the field
of scientific research. The complexity level depends upon the level of perception of an
individual but along with that an extra effort should be made towards simplifying the
scientific theories to the possible maximum level.
The definitions of the Occam’s razor, the simplicity in the context of science along
with the Bayesian model has been discussed in the first section of this assignment. The
second section of the model is focussed towards the justification of the fact how the Bayesian
model of evidence impacts the level of simplicity in science. An approach has been taken to
show how the view of evidence is beneficial towards justifying the preference of simplicity in

7AN EVALUATION ON THE SIMPLICITY OF SCIENTIFIC THEORIES
the field of science. Thus, the assignment strives to reflect that the fact that simplicity in
science is not always justified.

8AN EVALUATION ON THE SIMPLICITY OF SCIENTIFIC THEORIES
References
Berger, James O. Statistical decision theory and Bayesian analysis. Springer Science &
Business Media, 2013.
Bhaskar, Roy. A realist theory of science. Routledge, 2013.
Efron, Bradley. "Bayes' theorem in the 21st century." Science340.6137 (2013): 1177-1178.
Engström, Kerstin, et al. "Applying Occam's razor to global agricultural land use
change." Environmental Modelling & Software 75 (2016): 212-229.
Friston, Karl J., et al. "Bayesian model reduction and empirical Bayes for group (DCM)
studies." Neuroimage 128 (2016): 413-431.
Gelman, Andrew, et al. Bayesian data analysis. Chapman and Hall/CRC, 2013.
Godfrey-Smith, Peter. "Bayesianism and modern theories of evidence." Theory and reality.
An introduction to the philosophy of science. The University of Chicago Press
Chicago/London, 2003. 202-218.
Marin, Jean‐Michel, et al. "Relevant statistics for Bayesian model choice." Journal of the
Royal Statistical Society: Series B (Statistical Methodology) 76.5 (2014): 833-859.
Morey, Richard D., et al. "Why hypothesis tests are essential for psychological science: A
comment on Cumming." Psychological science 25.6 (2014): 1289-90.
Nola, Robert, and Howard Sankey. Theories of scientific method: an introduction. Routledge,
2014.
Popper, Karl. Realism and the aim of science: From the postscript to the logic of scientific
discovery. Routledge, 2013.

9AN EVALUATION ON THE SIMPLICITY OF SCIENTIFIC THEORIES
Rigoux, Lionel, et al. "Bayesian model selection for group studies—
revisited." Neuroimage 84 (2014): 971-985.
Rothe, J. Peter. The scientific analysis of personality. Routledge, 2017.
Salmon, Wesley C. The foundations of scientific inference. University of Pittsburgh Press,
2017.
Valkenburg, Wessel, Valerio Marra, and Chris Clarkson. "Testing the Copernican principle
by constraining spatial homogeneity." Monthly Notices of the Royal Astronomical
Society: Letters 438.1 (2013): L6-L10.
Van Den Berg, Hugo A. "Occam's razor: from Ockham's via moderna to modern data
science." Science Progress 101.3 (2018): 261-272.
Vapnik, Vladimir. The nature of statistical learning theory. Springer science & business
media, 2013.
Vehtari, Aki, Andrew Gelman, and Jonah Gabry. "Practical Bayesian model evaluation using
leave-one-out cross-validation and WAIC." Statistics and Computing 27.5 (2017):
1413-1432.