After the tragic events of 9/11 in 2001, the lack of proficient bilinguals in the United States became evident. US security agencies “were so desperate for translators of Arabic and other languages of south Asia that they were forced to place want-ads in newspapers” (Crawford, 2004, p. 71). To meet the new challenges, many government programs were created to produce highly proficient bilinguals, especially in critical languages, to fulfill economic, military, and diplomatic needs. Strengthening languages of language-minority communities, known as heritage languages, is a potential resource to bridge the existing gap.

The term “lingua franca” has been used to define a contact language that emerges from the need to communicate when speakers do not share a common language. Due to different linguistic backgrounds, interactions taking place in such contexts may develop as pidgins or creoles, that is, a mixture of two or more languages. In other cases, natural languages can serve similar purposes (Mauranen, 2018). Latin, for instance, used to be a lingua franca during the Roman Empire. Actually, the term itself derives from Latin “language of the Franks” (lingua franca) to refer to the language used mainly for commerce in the area around the East Mediterranean Sea. In colonial times, for example, the language of the colonizers (e.g., English in India) was generally imposed as a lingua franca.

Suppose you are the parent of a young child and you feel that your child’s language is not developing as rapidly or as well as that of your friend’s child of a similar age. What could be the reason? Is this a normal stage of development that your child is likely to outgrow, or is it a problem that will persist? Now suppose you are a parent in a similar situation, except your child is exposed to two languages on a regular basis. Is this a problem? Would it be better to limit the child to one language? These are the types of questions that speech-language pathologists (SLPs) working with children face almost every day. Distinguishing typical development from language impairment in young children is complicated enough – adding bilingualism to the mix brings a whole set of complicating factors.

The simple linear regression is one of the most frequently employed statistical model. Linear regression is used to describe the relationship between two numerical variables, but it also serves as a building block for more complex statistical methods, such as the multivariate ordination. We start by comparing the concepts of regression and correlation, before introducing the equation of the simple linear regression. We also explain the decomposition of the observed values of the response variable into fitted values and regression residuals. Following this is a discussion regarding the hypotheses that can be tested for a regression model, distinguishing the F-ratio based test from the t tests of individual regression coefficients. The calculation of confidence and prediction intervals allow us to enhance diagrams displaying the fitted model. A separate section is devoted to the graphs of regression diagnostics and their interpretation, as well as to the effects of log-transforming the variables to linearise their relationship. Additional specialised sections deal with regression through the origin and its possible dangers, regression using a predictor with random variation, and with linear calibration. The methods described in this chapter are accompanied by a carefully-explained guide to the R code needed for their use, including the effects and lmodel2 packages.

The contingency tables are used to quantify and test relationships between two or more categorical (qualitative) variables. Taking a simple example of a two-way contingency table (relating two categorical variables), we illustrate the process of calculating the frequencies of category combinations expected under the assumption of variable independence, and show how observed and expected frequencies are compared within the chi-square test statistic. We also briefly describe the task of measuring the strength of association between two categorical variables, which is important for evaluating the co-occurrence of biological taxa. We illustrate the differences between statistical and causal relationships between variables, highlighting the essential role of manipulative experiments for revealing causality. Finally, we demonstrate the possible ways of visualising contingency tables and their test results. The methods described in this chapter are accompanied by a carefully-explained guide to the R code needed for their use, including the vcd package.

We explain linear regression models with multiple predictors, including an overview of partial regression coefficients. The related concept of partial correlation is discussed in a separate section. We also contrast the overall model test using the F-ratio statistic and the t tests of partial effects of individual predictors. The adjusted coefficient of determination is presented as a more accurate way of conveying the explanatory power of a regression model. Finally, we characterise the family of general linear models, focusing specifically on analysis of covariance (ANCOVA). We provide examples of ANCOVA models and demonstrate their usefulness when applied to the analysis of biological experiments. The methods described in this chapter are accompanied by a carefully-explained guide to the R code needed for their use, including the effects and ppcor packages.

The evolution of World Englishes has widely affected and transformed the lives of many people in many countries; it is thus a process of great cultural and political significance. This chapter surveys some social debates and issues which have arisen in this context and attitudes towards new varieties of English, outlining sociocultural contexts and considerations affecting the emergence and acquisition of World Englishes. Topics include the association of English with "elitism", accessible mainly through higher education and thus a class divider, as opposed to its "grassroots growth"; the claim that it is a "killer language" reducing global linguistic diversity; norm orientations (towards a supposed "international English", "English as a Lingua Franca", or endonormative models); the role of new dialects of expressing local identities; the problematic status of the notion of a "native speaker"; the spread of mixed language forms; and pedagogical consequences resulting from all these issues.

Chapters 2 and 3 discussed the analytical and numerical solution of one-dimensional (1-D), steady-state problems. These are problems in which the temperature within the material is independent of time and varies in only one spatial dimension (e.g., x). Examples of such problems are the plane wall studied in Section 2.2, which is truly a 1-D problem, and the extended surface problems in Chapter 3 that are only approximately 1-D. The governing differential equation for these problems is an ordinary differential equation (ODE) and the mathematics required to solve the problem are straightforward.

In this chapter, we discuss the general finite element analysis procedure for linear vector field problems. A vector field problem is a problem whose primary unknown physical quantity is a vector quantity at any spatial location in the computational domain. As solid mechanics and fluid dynamics are representatives of vector field problems, this chapter demonstrates the solutions of a set of solid mechanics and fluid dynamics problems. The chapter contains four sections. The first section briefly reviews the theory of linear elasticity. The second section introduces the FEA procedure for structural analysis of a 2-D elasticity problem. The third section discusses a 3-D elasticity problem and illustrates the FEA steps. The fourth section discusses the FEA procedure for 2-D steady state incompressible viscous flow problems. At the end of each section, MATLAB codes for solving these problems are presented.

The chapter introduces "World Englishes" as a topic of scholarly research and argues that the global spread of English is a fascinating but also a complex process, with a number of possible, and sometimes conflicting, perspectives on and approaches to it. It is shown that nearly every speaker of English today has been exposed to different varieties of global English through media, travel, international contacts, and so on. It is argued that, based on their own linguistic backgrounds and more or less incidental cases of exposure to global varieties of English, proficient speakers of the language typically have intuitions on the sociosymbolic signaling functions of variant forms of English. Furthermore, it is shown that a wide range of sociostylistic information can be culled from any individual text. As a sample text, a Malaysian speech on a scientific subject is presented and discussed, pointing out some of its distinctive features on the levels of vocabulary, grammar, and pronunciation. Knowing more about such facts enriches our ability to assess, understand and contextualize Englishes from all around the world.