The Probability Concept

1941 ◽  
Vol 8 (2) ◽  
pp. 204-232 ◽  
Author(s):  
Edwin C. Kemble
Keyword(s):  
Probability Concept

Development of the Probability Concept in Children

1965 ◽  
Vol 36 (3) ◽  
pp. 779 ◽  
Author(s):  
Carolyn M. Davies
Keyword(s):  
Probability Concept

scholarly journals Computing under-ice discharge: A proof-of-concept using hydroacoustics and the Probability Concept

2018 ◽  
Vol 562 ◽  
pp. 733-748 ◽  
Author(s):  
John W. Fulton ◽  
Mark F. Henneberg ◽  
Taylor J. Mills ◽  
Michael S. Kohn ◽  
Brian Epstein ◽  
...  
Keyword(s):  
Proof Of Concept ◽  
Probability Concept

scholarly journals Subjective Probability and Geometry: Three Metric Theorems Concerning Random Quantities

2018 ◽  
Vol 10 (3) ◽  
pp. 7
Author(s):  
Pierpaolo Angelini ◽  
Angela De Sanctis
Keyword(s):  
Random Quantity ◽  
Real Space ◽  
Geometric Interpretation ◽  
Extensive Study ◽  
Dimensional Structure ◽  
Interpretation Of Probability ◽  
Straight Line ◽  
Probability Concept ◽  
Deep Meaning ◽  
Unit Vectors

Affine properties are more general than metric ones because they are independent of the choice of a coordinate system. Nevertheless, a metric, that is to say, a scalar product which takes each pair of vectors and returns a real number, is meaningful when $n$ vectors, which are all unit vectors and orthogonal to each other, constitute a basis for the $n$-dimensional vector space $\mathcal{A}$. In such a space $n$ events $E_i$, $i = 1, \ldots, n$, whose Cartesian coordinates turn out to be $x^i$, are represented in a linear form. A metric is also meaningful when we transfer on a straight line the $n$-dimensional structure of $\mathcal{A}$ into which the constituents of the partition determined by $E_1, \ldots, E_n$ are visualized. The dot product of two vectors of the $n$-dimensional real space $\mathbb{R}^n$ is invariant: of these two vectors the former represents the possible values for a given random quantity, while the latter represents the corresponding probabilities which are assigned to them in a subjective fashion.We deduce these original results, which are the foundation of our next and extensive study concerning the formulation of a geometric, well-organized and original theory of random quantities, from pioneering works which deal with a specific geometric interpretation of probability concept, unlike the most part of the current ones which are pleased to keep the real and deep meaning of probability notion a secret because they consider a success to give a uniquely determined answer to a problem even when it is indeterminate.Therefore, we believe that it is inevitable that our references limit themselves to these pioneering works.

A probability concept about size distributions of sonicated lipid vesicles

1985 ◽  
Vol 816 (1) ◽  
pp. 122-130 ◽  
Author(s):  
B.G. Tenchov ◽  
T.K. Yanev ◽  
M.G. Tihova ◽  
R.D. Koynova
Keyword(s):  
Lipid Vesicles ◽  
Size Distributions ◽  
Probability Concept

scholarly journals Measuring Students’ Understanding in Probability Concept between Two Different Cohort using Rasch Measurement

2019 ◽  
Vol 8 (2S11) ◽  
pp. 613-620
Keyword(s):  
Conceptual Knowledge ◽  
High Reliability ◽  
Rasch Measurement ◽  
Counting Rule ◽  
Branch Group ◽  
Probability Concept ◽  
Group A ◽  
Mathematical Sciences ◽  
The Difference ◽  
Group B

The students’ level of proficiency in any particular course is individually distinctive. Therefore, it is necessary for the educators to be able to address their student’s level of ability in understanding of the course they enrolled. Particularly, educators should be able to design a set of questions which suits the level of their students’ ability. For this reason, this study is concentrated on identifying the level of student’s ability in understanding probability concepts that has been included in the statistics course (STA150: Probability and Statistics 1). This course was enrolled by two groups of students (Group A and Group B) from the Faculty of Computer and Mathematical Sciences, Universiti Teknologi MARA Perak branch. Group A enrolled the course in December 2015 until March 2016 whilst Group B enrolled in June until November 2016 sessions. Since the aims of this study are to investigate the difference in students’ conceptual knowledge and understanding of probability concepts, as well as to examine which concepts were found most difficult by the students, hence the Rasch measurement approach was used to explore those aims. An instrument consists of 20 items in a test based on the “Counting Rule” topic was formed by an experienced lecturer to measure the level of student’s ability between the two groups. Based on the findings, it was found that there is a high reliability index of 0.93 (Group A) and 0.88 (Group B) which suggests the suitability of the instrument developed in this study to be replicated to the other samples, even though, the person student’s responses to the items for both groups appeared differently in terms of their difficulties in understanding the probability concepts which represents the student’s ability on this particular topic.

scholarly journals Target miss using PTV-based IMRT compared to robust optimization via coverage probability concept in prostate cancer

2020 ◽  
Vol 59 (8) ◽  
pp. 911-917
Author(s):  
Zoulikha Outaggarts ◽  
Daniel Wegener ◽  
Bernhard Berger ◽  
Daniel Zips ◽  
Frank Paulsen ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Robust Optimization ◽  
Coverage Probability ◽  
Probability Concept
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