This chapter introduces readers to the lived experience of an anxious student, providing a human lens through which to explore mathematics anxiety – a global, multi-dimensional phenomenon that has evolved over more than seventy years. It offers foundational definitions and situates mathematics anxiety within the context of non-specialist university students, particularly those encountering barriers to engaging with statistics and quantitative research methods. While the discussion is especially relevant to students in the social sciences, the issues addressed also resonate with learners in STEM disciplines. The chapter sets the stage for a pedagogical intervention designed to moderate anxiety and enhance learning, previewing its implementation and key highlights. It concludes with an overview of the book’s structure, guiding readers through themes of inclusive education and emotionally intelligent teaching practices.

Chapter 3 offers an initial empirical assessment of the book’s main argument. It begins by identifying the partisan Left and Right in postcommunist Europe and analyzing patterns of their programmatic positions and ballot box results. The findings support the theoretical expectation that the long-term economic stances and electoral performance of the Left, but not of the Right, are two mutually related legacies of postcommunist junctures. Next, having developed a set of variables to compare long- and short-term electoral effects on the Left, I show that the former are the stronger predictor of illiberal electoral outcomes. The chapter closes with a discussion of why rival arguments prioritizing economic, political, and cultural demand, institutional and leadership supply, and international factors fail to adequately explain the variation identified in book’s opening chapter. This point is empirically reinforced in Appendix D, where I test the plausibility of the postcommunist juncture theory vis-à-vis rival hypotheses by using an original dataset and standard statistical methods for cross-sectional and time series data. The results show that the long-term regularities rooted in postcommunist junctures explain illiberal electoral outcomes in the most significant and consistent way.

This chapter examines how the rhetoric of achievement books is crafted through images and numbers as well as words. I argue that these media have two purposes. On one hand, they act as symbolic fragments of the nation, constituted by a recognisable Nasser-era iconography. Peasants and workers, students and soldiers, factories and machines, land and buildings – all these elements are marshalled to depict a cohesive national mosaic. On the other hand, each photograph and statistic acts as an index of the state’s achievements; the picture and the number become, on their own, an inarguable demonstration of the state’s ability to achieve. After describing the typical content of Nasserist iconography, the chapter moves to analyse it in relation to the master narratives of industrial modernisation and revolutionary responsibility. The chapter concludes with an analysis of what images exclude, what lies beyond their frame, and how these exclusions are telling about what constitutes ‘the state’ under Nasser. Governmental images and numbers are not a peripheral epiphenomenon to Nasser-era politics, but they are symbolically and indexically central to the state’s construction.

The chapter analyses how the climate change action plan developed by the European Central Bank (ECB) as part of its monetary policy strategy review in 2020-2021 is aligned with the ECB’s mandate set out in the Treaty on the Functioning of the European Union and the Treaty on European Union. The Treaties require the ECB to integrate climate change considerations into its monetary policy and to contribute to the EU’s objectives regarding climate change, as established by Regulation (EU) 2021/1119, the European Climate Law. However, there are also legal limits on the action the ECB can take in this field. The chapter examines the key measures proposed as part of the plan from a legal perspective, including measures related to macroeconomic forecasts and models, the collection of statistical information for climate change risk analysis, the enhancement of risk assessment capabilities, asset purchase programmes, and possible changes to the collateral framework. It also considers the questions regarding the ECB’s democratic legitimacy and accountability that arise in this context.

Science is invariably based on some sort of data collection and further treatment of the data gathered. Data can come from pure observations, from structured observations (‘natural experiments’) or from experiments. The central importance of models in science is mentioned. It is discussed how the choice of statistics reflects the philosophy of science adopted by the scientist. Different research programmes use different statistics, in particular, depending on when and how they deal with variation. The relationship between falsificationism and the rejection of null hypotheses as a workaround for the Duhem-Quine thesis is discussed, as well as the role of significance thresholds and their associated problems. It is argued that predicted results are more reliable than chance findings. The pros and cons of having alternative hypotheses are discussed, and a short introduction to Bayesian statistics as an alternative to frequentist approaches is given. Systematic reviews and metaanalyses of data from several studies are introduced, and an example is given on how different types of evidence from many studies are combined to form the current consensus of rational opinion regarding a particular hypothesis.

This chapter introduces the field and the scope of research and the fundamental terminology. The basic objective of this monograph is primary onomatopoeia defined as imagic icons of the signified objects; prototypically, they are underived and uninflected monemes. The Introduction maps the state of the art in onomatopoeia research, mainly based on a questionnaire-based survey among language experts covering 124 languages of the world. It accounts for the method of language sampling. Since data collection can be significantly affected by the status of the sample languages, this section also provides their classification according to the Expanded Graded Intergenerational Disruption Scale. This chapter also provides an overview of resources available for research in this field with a focus on the availability of dictionaries and corpora that identify the class of onomatopoeia. Significant attention is given to the categorization of sounds, an aspect often overlooked in onomatopoeia studies. This categorization is crucial for mapping the sound sources and sound events that onomatopoeias represent across the sampled languages.

Statistics were the lens through which the Bank viewed the global economy. Although the quantification of economic phenomena had many prewar precedents, the unresolved problems stemming from the First World War led to its reinvention. The Bank originally employed economists, including Oliver M.W. Sprague and Walter W. Stewart, to develop its in-house statistical capabilities. Subsequent developments included the creation of a research division, employment of trained staff members, and publication of a monthly report. With the onset of the British slump and the contentious debates on the (Macmillan) Committee on Finance and Industry, experts gained new opportunities to influence economic policy. Through its research, the Bank of England was able to establish its reputation as an intellectual authority.

This chapter draws on the original cross-national dataset of counterrevolutions to examine global patterns and historical trends in counterrevolutionary emergence and success. It begins with a series of statistical analyses that support core elements of the theory. Counterrevolutions are much less likely to topple radical-violent revolutions than moderate-unarmed ones – a finding that holds across two different measures of these types. Subsequent analyses shed light on the mechanisms behind this relationship: loyal armies and powerful foreign sponsors are key to defeating counterrevolution, whereas robust parties matter less. Next, the chapter shows that counterrevolutions are most likely to emerge following revolutions with medium levels of violence, which leave the old regime with both the capacity and interest to launch a challenge. Further, there is little support for four alternative explanations, particularly when it comes to counterrevolutionary success. Next, the chapter evaluates how key events during the post-revolutionary transition (like land reforms and elections) affect the likelihood of counterrevolution. It concludes with an exploration of the decline in counterrevolution since 1900 (followed by an uptick in the last decade), which it traces to a combination of the changing nature of revolution and shifts in the distribution of global power.

This chapter analyzes the popular dimensions of Egypt’s 2013 counterrevolution, using an original dataset of protests during the post-revolutionary transition. It shows that Egypt’s revolutionaries were unable to consolidate the social support of the revolution, and that this failure allowed counterrevolutionaries to channel broad disaffections with revolutionary rule into a popular movement for restoration. The dataset covers the final eighteen months of the transition and includes approximately 7,500 contentious events sourced from the major Arabic-language newspaper Al-Masry Al-Youm. These data reveal, first, the extent to which social mobilization persisted after the end of the eighteen-day uprising. The transition period was awash with discontent and unrest, much of it over nonpolitical issues like the deterioration of the economy, infrastructure problems, and unmet labor demands. Second, statistical analyses show that this discontent came to be directed against Mohamed Morsi’s government. The earliest and most persistent anti-Morsi protests emerged in places where the population had long been highly mobilized over socio-economic grievances. Later, they also began to emerge in places with large numbers of old regime supporters. Ultimately, these two groups – discontented Egyptians and committed counterrevolutionaries – came together to provide the social base for the movement that swept the military back to power.

We introduce basic principles of the statistical analysis of hemodynamic imaging data, including concepts like the General Linear Model, data cleaning, efficiency, parametric hypothesis testing, correction for multiple comparisons, first- and second-level analyses, region of interest analysis, double dipping, and the issue of statistical inference with reference to forward and reverse inferences.

This chapter provides an end-to-end introduction to statistics; this highlights how statistics can be used to develop models from data, to quantify the uncertainty of such models, and to make decisions under uncertainty. The chapter also discusses how random variables are the key modeling paradigm that is used in statistics to characterize and quantify uncertainty and risk.