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Arts-integration is a promising approach to building students’ abilities to create and critique arguments with data, also known as informal inferential reasoning (IIR). However, differences in disciplinary practices and routines, as well as school organization and culture, can pose barriers to subject integration. The purpose of this study is to describe synergies and tensions between data science and the arts, and how these can create or constrain opportunities for learners to engage in IIR.

The authors co-designed and implemented four arts-integrated data literacy units with 10 teachers of arts and mathematics in middle school classrooms from four different schools in the USA. The data include student-generated artwork and their written rationales, and interviews with teachers and students. Through maximum variation sampling, the authors identified examples from the data to illustrate disciplinary synergies and tensions that appeared to support different IIR processes among students.

Aspects of artistic representation, including embodiment, narrative and visual image; and aspects of the culture of arts, including an emphasis on personal experience, the acknowledgement of subjectivity and considerations for the audience’s perspective, created synergies and tensions that both offered and hindered opportunities for IIR (i.e. going beyond data, using data as evidence and expressing uncertainty).

This study answers calls for humanistic approaches to data literacy education. It contributes an interdisciplinary perspective on data literacy that complements other context-oriented perspectives on data science. This study also offers recommendations for how designers and educators can capitalize on synergies and mitigate tensions between domains to promote successful IIR in arts-integrated data literacy education.

To develop an overview of generalized scales based on pansystems‐relative quantification.

This is a discussion paper exploring the key issues surrounding generalized measures.

The concrete contents of the study include generalized measure views, dimension theory, concepts, logic, theories, Einstein's relativity, quality‐quantity‐degree, methodology of physics, theorems in pansystems mathematics and physics explained within the framework of pan‐scale transformations.

Provides an overview of generalized scales based on pansystems‐relative quantification.

THE accountant is the latest competitor for management power. The Institute of Cost & Works Accountants—the value of whose Associate qualification we acknowledge—has re‐cast its requirements for the grade of Fellowship. Cost Accountants' or for that matter many other kinds of accountant, are now invited to sit for the Fellowship examination, the syllabus for which has just been published. This comprises the now familiar: Management—Factory and Distribution, Statistical Method, Advanced Cost Accountancy, Company Law, Management Accountancy and the Economic Aspects of Industry and Commerce. (The Management Section includes Motion & Time Study). Assuming that they are successful in this and that they satisfy a Reviewing Board of the adequacy of their experience, they may then call themselves “Management Accountants”.

The intent of this paper is to discuss the use of statistical mathematics in property valuation and the wider question concerning the role of mathematics in the field of economics.

This paper reviews the evolution of the application of mathematics, including statistics in economics and drawing conclusions about applicability and effectiveness of quantitative modelling in property valuation.

This paper discusses the future use of statistical models in valuation and the need to recognise the relationships between market participants and the increasingly complex environment, and their impact on value. This would suggest adopting modelling techniques from behavioural economics.

This paper highlights the difference between quantitative and qualitative models and discusses the role that each can play in property valuation.

This paper provides insights on the development of statistical modelling and discusses the application of the same in property valuation.

Citizens today are inundated with quantitative information in an information-rich world. However, students rarely get the opportunity to use mathematics to explore social issues— a concept known as Social Mathematics. Social Mathematics should be an important part of students’ K-12 experiences and is fundamental in preparing our students for active citizenship in a democratic society. This feature makes the case that social mathematics is an important but often neglected area of social studies and mathematics education, and improving students’ knowledge in this area requires the collaborative efforts of both social studies and mathematics teachers. A variety of strategies and resources for interdisciplinary collaboration between social studies and mathematics teachers is provided.

This study aims to describe the pedagogical content knowledge (PCK) of a kindergarten educator who implements a lesson plan about informal inferential reasoning designed in a lesson study group.

To this end, we analyzed teaching interventions in two kindergarten lessons focused on the playful task of tossing two coins, associated with inferential statistical reasoning. The study highlights the importance of arguing and promoting this reasoning to develop statistical thinking. It is crucial to recognize how early students can be subject to learning experiences that promote a language of uncertainty, assess the evidence provided by the data, and make generalizations.

The results reveal that while the educator demonstrated knowledge and skills relevant to the curriculum and conceptual teaching strategies, the understanding of the content by the students and the integration of the PCK components still present a challenge.

The lesson study collaborative teaching practices that promote PCK have proven effective for informing the design and implementation of instructional practices supporting the development of early statistical thinking in young children.

The study enriches the knowledge regarding the potential of the lesson study (LS) in the professional learning of kindergarten educators. It also contributes to a comprehensive approach based on authentic playful experiences in grade K that supports the development of early statistical thinking in young children.

The purpose of the article is to gain more insight into factors that can explain students' success in business subjects. The focus is on the connection between performance in introductory courses in business mathematics (BM) and business statistics (BS) and success in various business subjects.

Use of a regression model with administrative data from a business school in Norway over a period of 10 years.

The findings show a strong correlation, especially in quantitative subjects. The results suggest that statistical skills are more strongly related to academic success than mathematical skills.

The data are collected from only one school. No information on undergraduates' personalities and behaviours is available.

There are limited published studies that have explored the relationship between success in statistics and later achievements in business courses. This is useful knowledge for planning the content of the bachelor's programme.

To prepare pre-service mathematics teachers (PSMTs) in Egypt, learning statistics as a subject takes place at the faculty of science, apart from what is going on at the faculty of education. The Organization for Economic Co-operation and Development has highlighted this dilemma as follows; “Pre-service education in Egypt is characterized by a separation of theory from practice, in the belief that student teachers will put it into practice later in schools” (OECD, 2015, p. 120). The purpose of this paper is to propose a microteaching lesson study (MLS) model that bridges the gap between learning free content pedagogies and teaching statistics, consequently, enhances PSMTs’ pedagogical content knowledge.

The ethnographic approach has been employed, and hence, the national faculty policy guidelines have been revised through Grossman’s (1990) model. Moreover, a focus group of PSMTs’ opinions has been investigated to interpret the aforementioned situation and provide meaningful insights.

As a result, the MLS model rooted in constructivism theory has been introduced. Furthermore, supported discourse to enhance PSMTs’ pedagogical content knowledge (PCK) of teaching statistics is described.

The MLS model may help to change PSMTs’ perception concerning the gap between theory and practice. Meanwhile, it could be an endeavor to reform PSMTs’ initial views regarding what learning and teaching of statistics look like, through enhancing their PCK of teaching statistics. Furthermore, engaging them in such environments to be a part of the learning community and learn more from the experts is crucial.

This paper aims to propose a novel statistic energy analysis method with fuzzy parameters to study the dynamic and acoustic responses of coupled system with fuzzy parameters, which can expand the applied range of statistic energy analysis method in engineering to some extent.

On the basis of the property of membership level, the uncertain fuzzy parameters are expressed as the interval forms. Interval mathematics and interval expansion principle are adopted to solve the problem with interval parameters. At last, two numerical examples, which include a two-plate coupled system and a single-partition sound-insulation system, are carried out to demonstrate the feasibility and validity of the presented method.

Interval mathematics and interval expansion principle are adopted to solve the problem with interval parameters.

By integrating the interval analysis, optimization technique and Taylor expansion method, two non-probabilistic, set-theoretical statistical energy analyses are proposed for predicting the dynamical and acoustical response of the complex coupled system with uncertain parameters in high-frequency domain.

The traditional Shewhart control chart, the X-bar and R/S chart, cannot give support to decide when it is not economically feasible to stop the process in order to remove special causes. Therefore, the purpose of this paper is to propose a new control chart design – a modified acceptance control chart, which provides a supportive method for decision making in economic terms, especially when the process has high capability indices.

The authors made a modeling expectation average run length (ARL), which incorporates the probability density function of the sampling distribution of C_pk, to compare and analyze the efficiency of the proposed design.

This study suggested a new procedure to calculate the control limits (CL) of the X-bar chart, which allows economic decisions about the process to be made. By introducing a permissible average variation and defining three regions for statistical CL in the traditional X-bar control chart, a new design is proposed.

A framework is presented to help practitioners in the use of the proposed control chart. Two new parameters (C_p and C_pk) in addition to m and n were introduced in the expected ARL equation. The C_pk is a random variable and its probability function is known. Therefore, by using a preliminary sample of a process under control, the authors can test whether the process is capable or not.