Integration of Ideological and Political Education into the Probability Theory and Mathematical Statistics Course:A Teaching Design Based on Estimation and Hypothesis Testing

With the rapid development of higher education in China,colleges and universities are facing new challenges and impacts in talent training.Probability Theory and Mathematical Statistics is one of the important courses in higher education for science and engineering majors and economics and management majors.Its critical role in cultivating students’thinking skills and improving their problem-solving skills is self-evident.Course ideological and political education construction is an important link in college talent training work.Combining ideological and political education with course teaching can help students establish correct value concepts and play a certain role in improving their comprehensive ability and quality.At present,the construction of ideological and political education in the Probability Theory and Mathematical Statistics course still faces some problems,mainly manifested in the lack of attention paid by teachers to course ideological and political education,insufficient exploitation of ideological and political elements,and the simplification of ideological and political education implementation methods.In order to comprehensively deepen the construction of course ideological and political education in line with the actual needs of Probability Theory and Mathematical Statistics course teaching,we should strengthen the construction of teacher teams,improve teachers’ability to carry out course ideological and political education,integrate educational resources,develop educational resources for ideological and political education,and innovate teaching methods to improve the overall effect of ideological and political education integration.

Using Monte Carlo Simulation Technology to Improve Intuitive Effect of Teaching Probability and Mathematical Statistics Course

With the illustration of a specific problem, this paper demonstrates that using Monte Carlo Simulation technology will improve intuitive effect of teaching Probability and Mathematical Statistics course, and save instructors' effort as well.And it is estimated that Monte Carlo Simulation technology will be one of the major teaching methods for Probability and Mathematical Statistics course in the future.

Research on the Applications of Advanced Mathematics on Mathematical Modeling and the Inner Connections with Linear Algebra and Probability Statistics

In this paper, we conduct research on the applications of advanced mathematics on the mathematical modeling and the inner connections with linear algebra and the probability statistics. Aiming at model in mathematical modeling and solving and model of evaluation and promotion of the two links, put forward the ＂bystander＂ and ＂the authorities＂ this two characters, and points out that excellent mathematical modeling participants should have ＂from a bystander to the authorities＂ and ＂from the authorities to return to bystanders＂ two-way role transformation ability. Great situation in mathematics teaching, by means of the mathematical modeling formed in the development of the teachers, as well as the teaching thought, teaching experience and achievements, the onward march of mathematical experiment should be faster than mathematical modeling. Our research provides the new paradigm for the math development which will be meaningful.

Past and Future of Mathematical Geology

This is a brief review of alternative methods of problem-solving in geoscience with emphasis on the role of mathematical geology. It is desirable to maintain a clear-cut distinction between reliable facts which can be stored in data banks and concepts that can be incorporated in the specifications of statistical models designed for specific purposes. If possible, subjective probabilities should be incorporated in hypotheses that are to be tested by statistical inference.

Incomplete nonextensive statistics and the zeroth law of thermodynamics

On the basis of the entropy of incomplete statistics （IS） and the joint probability factorization condition, two controversial problems existing in IS are investigated： one is what expression of the internal energy is reasonable for a composite system and the other is whether the traditional zeroth law of thermodynamics is suitable for IS. Some new equivalent expressions of the internal energy of a composite system are derived through accurate mathematical calculation. Moreover, a self-consistent calculation is used to expound that the zeroth law of thermodynamics is also suitable for IS, but it cannot be proven theoretically. Finally, it is pointed out that the generalized zeroth law of thermodynamics for incomplete nonextensive statistics is unnecessary and the nonextensive assumptions for the composite internal energy will lead to mathematical contradiction.

Higher Variations of the Monty Hall Problem (3.0, 4.0) and Empirical Definition of the Phenomenon of Mathematics, in Boole’s Footsteps, as Something the Brain Does

In Advances in Pure Mathematics (www.scirp.org/journal/apm), Vol. 1, No. 4 (July 2011), pp. 136-154, the mathematical structure of the much discussed problem of probability known as the Monty Hall problem was mapped in detail. It is styled here as Monty Hall 1.0. The proposed analysis was then generalized to related cases involving any number of doors (d), cars (c), and opened doors (o) (Monty Hall 2.0) and 1 specific case involving more than 1 picked door (p) (Monty Hall 3.0). In cognitive terms, this analysis was interpreted in function of the presumed digital nature of rational thought and language. In the present paper, Monty Hall 1.0 and 2.0 are briefly reviewed (§§2-3). Additional generalizations of the problem are then presented in §§4-7. They concern expansions of the problem to the following items: (1) to any number of picked doors, with p denoting the number of doors initially picked and q the number of doors picked when switching doors after doors have been opened to reveal goats (Monty Hall 3.0;see §4);(3) to the precise conditions under which one’s chances increase or decrease in instances of Monty Hall 3.0 (Monty Hall 3.2;see §6);and (4) to any number of switches of doors (s) (Monty Hall 4.0;see §7). The afore-mentioned article in APM, Vol. 1, No. 4 may serve as a useful introduction to the analysis of the higher variations of the Monty Hall problem offered in the present article. The body of the article is by Leo Depuydt. An appendix by Richard D. Gill (see §8) provides additional context by building a bridge to modern probability theory in its conventional notation and by pointing to the benefits of certain interesting and relevant tools of computation now available on the Internet. The cognitive component of the earlier investigation is extended in §9 by reflections on the foundations of mathematics. It will be proposed, in the footsteps of George Boole, that the phenomenon of mathematics needs to be defined in empirical terms as something that happens to the brain or something that the brain does. It is generally assumed that mathematics is a property of nature or reality or whatever one may call it. There is not the slightest intention in this paper to falsify this assumption because it cannot be falsified, just as it cannot be empirically or positively proven. But there is no way that this assumption can be a factual observation. It can be no more than an altogether reasonable, yet fully secondary, inference derived mainly from the fact that mathematics appears to work, even if some may deem the fact of this match to constitute proof. On the deepest empirical level, mathematics can only be directly observed and therefore directly analyzed as an activity of the brain. The study of mathematics therefore becomes an essential part of the study of cognition and human intelligence. The reflections on mathematics as a phenomenon offered in the present article will serve as a prelude to planned articles on how to redefine the foundations of probability as one type of mathematics in cognitive fashion and on how exactly Boole’s theory of probability subsumes, supersedes, and completes classical probability theory. §§2-7 combined, on the one hand, and §9, on the other hand, are both self-sufficient units and can be read independently from one another. The ultimate design of the larger project of which this paper is part remains the increase of digitalization of the analysis of rational thought and language, that is, of (rational, not emotional) human intelligence. To reach out to other disciplines, an effort is made to describe the mathematics more explicitly than is usual.

The Monty Hall Problem and beyond: Digital-Mathematical and Cognitive Analysis in Boole’s Algebra, Including an Extension and Generalization to Related Cases

The Monty Hall problem has received its fair share of attention in mathematics. Recently, an entire monograph has been devoted to its history. There has been a multiplicity of approaches to the problem. These approaches are not necessarily mutually exclusive. The design of the present paper is to add one more approach by analyzing the mathematical structure of the Monty Hall problem in digital terms. The structure of the problem is described as much as possible in the tradition and the spirit—and as much as possible by means of the algebraic conventions—of George Boole’s Investigation of the Laws of Thought (1854), the Magna Charta of the digital age, and of John Venn’s Symbolic Logic (second edition, 1894), which is squarely based on Boole’s Investigation and elucidates it in many ways. The focus is not only on the digital-mathematical structure itself but also on its relation to the presumed digital nature of cognition as expressed in rational thought and language. The digital approach is outlined in part 1. In part 2, the Monty Hall problem is analyzed digitally. To ensure the generality of the digital approach and demonstrate its reliability and productivity, the Monty Hall problem is extended and generalized in parts 3 and 4 to related cases in light of the axioms of probability theory. In the full mapping of the mathematical structure of the Monty Hall problem and any extensions thereof, a digital or non-quantitative skeleton is fleshed out by a quantitative component. The pertinent mathematical equations are developed and presented and illustrated by means of examples.

Statistical Theory of Turbulence by the Late Lamented Dr. Shunichi TsugéCase Study on Flow through a Grid in Wind Tunnel

This paper is concerned with statistical theory of turbulence by the late lamented Dr. Shunichi Tsugé.? The theory has been applied to the primary flow through a grid fixed vertically with respect to the horizontal axis of the wind tunnel.?The first analytical solution has been obtained and explained the well-known “the inverse-linear decay law” of the turbulent intensity.? It is believed that the present result is the first exact solution in the theory of turbulence.

SOME ISSUES OF TURBULENCE STATISTICS

The issue of dropping the random force f(i) and the arbitrariness of choosing the basic variable in the variational approach to turbulence closure problem, pointed out recently by the Russian scientists Bazdenkov and Kukharkin, are discussed. According to the mean-square estimation method, the random force f(i) should be dropped in the error expression of the LFP (Langevin-Fokker-Planck) model. However, f(i) is not neglected, its effect has been taken into account by the variational approach. In order to optimize the perturbation solution of the Liouville equation, the LFP model requires that the basic variable is as near to Gaussian as possible. Hence, the velocity, instead of the vorticity, should be chosen as the basic variable in the three-dimensional turbulence. Although the LFP model and the zero-order Gaussian term of PDF (probability density function) imply whiteness assumption (zero correlation time of f(i)), the higher-order non-Gaussian terms of PDF correspond to the nonwhiteness of turbulence dynamics, the variational approach does calculate the nonwhiteness effect properly.

Applications of Mogulskii, and Kurtz-Feng Large Deviation Results to Risk Reserve Processes with Aggregate Claims

In this paper we examine the large deviations principle (LDP) for sequences of classic Cramér-Lundberg risk processes under suitable time and scale modifications, and also for a wide class of claim distributions including (the non-super- exponential) exponential claims. We prove two large deviations principles: first, we obtain the LDP for risk processes on D∈[0,1] with the Skorohod topology. In this case, we provide an explicit form for the rate function, in which the safety loading condition appears naturally. The second theorem allows us to obtain the LDP for Aggregate Claims processes on D∈[0,∞) with a different time-scale modification. As an application of the first result we estimate the ruin probability, and for the second result we work explicit calculations for the case of exponential claims.

Riemann Hypothesis, Catholic Information and Potential of Events with New Techniques for Financial and Other Applications

In this research we are going to define two new concepts: a) “The Potential of Events” (EP) and b) “The Catholic Information” (CI). The term CI derives from the ancient Greek language and declares all the Catholic (general) Logical Propositions () which will true for every element of a set A. We will study the Riemann Hypothesis in two stages: a) By using the EP we will prove that the distribution of events e (even) and o (odd) of Square Free Numbers (SFN) on the axis Ax(N) of naturals is Heads-Tails (H-T) type. b) By using the CI we will explain the way that the distribution of prime numbers can be correlated with the non-trivial zeros of the function ζ(s) of Riemann. The Introduction and the Chapter 2 are necessary for understanding the solution. In the Chapter 3 we will present a simple method of forecasting in many very useful applications (e.g. financial, technological, medical, social, etc) developing a generalization of this new, proven here, theory which we finally apply to the solution of RH. The following Introduction as well the Results with the Discussion at the end shed light about the possibility of the proof of all the above. The article consists of 9 chapters that are numbered by 1, 2, …, 9.

Multi-fractal analysis of highway traffic data

The purpose of the present study is to investigate the presence of multi-fractal behaviours in the traffic time series not only by statistical approaches but also by geometrical approaches. The pointwisc Hǒlder exponent of a function is calculated by developing an algorithm for the numerical evaluation of HSlder exponent of time series. The traffic time series observed on the Beijing Yuquanying highway are analysed. The results from all these methods indicate that the traffic data exhibit the multi-fractal behaviour.

Clarifications for the Published Article: “A Solution to the Famous Twin’s Problem” in the APM of SCIRP at 24 September of 2019

This article B is almost autonomous because it can be read independently from the first published article A [1] using only a few parts of the article A. Be-low are given instructions so to need the reader study only on few places of the article A. Also, in the part A of Introduction, here, you will find simple and useful definitions and the strategy we are going to follow as well useful new theorems (also and in Section 5, which have been produced in this solution). So the published solution of twin’s problem can now be easily understood. The inequalities (4.17), (4.18) of Article A are proved here in Section 4 by a new clear method, without the possible ambiguity of the text between the relations (4.14), (4.16) of the Article A. Also we complete the proof for the twin’s distri-bution which we use. At the end here are presented the Conclusions, the No-menclatures and the numerical control of the proof, which is probably useful as well in coding methods. For a general and convincing picture is sufficient, a study from the beginning of this article B until the end of the part A of the In-troduction here as well a general glance on the Section 5 and on the Conclu-sions below.

统计活动过程视角下小学“统计与概率”教材内容的分析与比较——以“苏教版”“北师版”为例

以“统计活动过程”视角为理论基础,从统计活动过程的各环节要素对苏教版和北师版小学数学教材中“统计与概率”内容进行分析和比较.研究发现:两版教材在统计活动过程的各环节上有所侧重,整体上各具风格;两版教材均直接突出对统计基础知识的重视,并间接蕴涵着对数据意识的培养.对教材使用的启示有:以“统计活动视角”为基础,注重对教材进行创生;将活动视角与统计教学间的“冲突”化为提升素养的机会;进而在统计活动中促进批判性思维的发展.对教材编写或修订提供启发:从学科角度厘清“统计”与“概率”的本质关系,整体把握统计活动的全过程,给予学生更多获取直接经验的机会.

新文科建设背景下《概率论与数理统计》课程教学创新实践

在新文科建设背景下,结合经济类专业《概率论与数理统计》课程现状,针对课程教学中出现的问题,从教学内容设计、教学手段模式和教学评价三方面实施了教学创新实践。构建了课前、课中和课后三阶段和课程思政引领的“三阶段一引领”教学内容,设计了课前课后阶段线上、课中阶段线下的混合式教学模式,对评价标准应用线上学习数据和期末考试结合的“全过程”评价模式创新,从多个方面多个角度提升课堂教学效果,改进教学质量,全面提升经济类专业学生数学科学素养。

工程教育认证下“概率论与数理统计”教学改革

“概率论与数理统计”是理工和经管类各专业的数学基础课程,课程中的方法在解决实际问题时应用广泛。但是该课程理论性强、学习难度大,课程教学中通常存在课时少、实践少、学用分离等教学痛点,不符合工程教育认证理念。分析了防灾科技学院地质工程专业工程教育认证对“概率论与数理统计”课程的要求,以及大学传统的数学课堂教学存在的问题,结合地质工程专业发展规划和应用型人才培养目标,探讨如何进行数学类课程的教学改革,以达到工程教育认证标准。

概率论与数理统计课程情境化教学模式探索与实践

概率论与数理统计是高校理工专业的核心基础课程,开展概率论与数理统计情境化教学模式探索与实践能够显著提升教学质量。该文首先从课程属性、智慧教学环境、教学理念等视角分析开展情境化教学模式的必要性,进而从情境案例准备、学习情境设定、自主探究学习、智能系统辅助和数据分析与评估等五个环节探讨情境化教学模式设计问题。最后,以条件概率为例,研究情境化教学模式的实施过程。情境化教学模式还可以向其他公共基础课程与专业课程推广应用,能够在学生创新实践能力培养方面发挥重要作用。

“少教多学”理念下国家级一流课程概率论与数理统计本校化混合式教学实践研究

“少教多学”倡导“先学后教,以学定教”,体现以学生为中心的现代教育理念。在该理念的指导下,引入国家级一流线上课程概率论与数理统计资源,并进行适合该校学生特点的本校化课程改造使之可以更好地服务于课程教学。基于BOPPPS的混合式教学设计和实施,有效地提高该课程的过关率和学生的学习能力,促进学生思维的发展。

新文科背景下面向财经类高校的“概率论与数理统计”课程建设与实践——以贵州财经大学为例

根据“新文科”建设的核心要义,分析了财经类高校在探索“概率论与数理统计”课程建设的现状与困境。重点以贵州财经大学为例,探讨了“概率论与数理统计”的课程建设与实践。以超星信息技术平台为依托,深入贯彻基于学习成果为导向的教学理念,以学科竞赛为抓手,着力提升人才培养质量为目标,按照一流课程建设要求,融入课程思政,助推统计学一流专业和一流学科建设。

基于“三全育人”理念的概率论与数理统计课程思政教学探索与实践

课程思政是实现有效育人的重要教学方式。根据当前概率论与数理统计课程思政的现状,并基于概率论与数理统计课程教学内容,从融入时机、思政元素类型两方面阐述课程思政教学的做法,挖掘案例中蕴含的“思政元素”及所承载的思想政治教育功能,以润物无声的方式将思政元素融入课堂教学,促成知识传授、思政教育、价值引领三者有机统一,做到全员、全程、全方位育人,以此实现概率论与数理统计课程立德树人的目标。