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ABSTRACTWith the increase of data availability, knowledge about quantitative methods is more important than ever. Indeed, students need quantitative methods to understand quantitative academic research, to conduct this research themselves, and to increase their employability in the labor market. Yet, students often experience quantitative methods as difficult to learn and, in turn, instructors find the topic difficult to teach. To make both learning and teaching easier, this article provides seven concrete suggestions regarding the teaching of quantitative methods.

This article introduces the symposium issue on `Narrative, Numbers and Socio-Cultural Change'.The articles were all papers presented initially at the conference `Narrative, Numbers and Social Change' at the University of Manchester, UK in November 2007.The conference was organized through the Economic and Social Research Council (ESRC) funded Centre for Research on Socio-Cultural Change (CRESC). Methodological issues have been central to CRESC since its inception, and the Centre has an ongoing commitment to nurturing methodological expertise and innovation in the study of socio-cultural change. This particular event marked an interest in rethinking the boundaries of qualitative and quantitative research and in developing methods adequate to the challenges posed by socio-cultural complexity, in ways which involve reworking some of the conventional understandings of the relationships between the empirical, the theoretical and methodology. The introduction reviews the articles and reflects on their significance in the context of understandings of methods in cultural sociology and the sociology of culture, in the UK and beyond.

This book provides a brief yet rigorous introduction to various quantitative methods used in economic decision-making. It has no prerequisites other than high school algebra. The book begins with matrix algebra and calculus, which are then used in the book's core modes. Once the reader grasps matrix theory and calculus, the quantitative models can be understood easily, and for each model there are many solved examples related to business and economic applications.

"Systematic research and comprehensive analyses allow to monitor the implementation of the sustainable development goals. Obviously, when you are interested in the selected issue of sustainable development, it is worth using data from the secondary sources in the first place. This e-book presents a few selected methods that will allow you to answer the questions: how to gather data and how to analyse them? Among the data collection methods presented in this book, we have chosen both: qualitative, in particular focus group interview, and quantitative--based on a questionnaire. In terms of data analysis methods, we present three methods: factor analysis, structural equation modelling and data envelopment analysis. The examples presented in this book relate to sustainable development, for example: sustainable consumption, ecological culture, better nutrition, agricultural development and many more. The book consists of five chapters. Chapter 1 "Qualitative methods" presents the issues concerning the methodology of qualitative research, designing a focus group interview, conducting a focus group interview and analysis of qualitative data using the CAQDAS programs. The main goal of Chapter 2 titled "Quantitative methods" is to exhibit the basics of survey research that can be used in analyses of sustainable development. In particular, this part presents the measurement levels, questionnaire design, population and sample, and the ways of presenting the results of quantitative research. Chapter 3 "Factor analysis in sustainable development research" describes the basic theoretical aspects of factor analysis. The second part of this chapter presents an example of the use of this method in research on sustainable consumption. The last part of this chapter presents case study of the use of factor analysis in research on managers' ethics in retail industry. Chapter 4 titled "Structural equation modelling in sustainable development research" is dedicated to the structural equation modeling methods applied to solve sustainable development research problems. A structural equation model is an abstraction of reality, and the researcher's job is to build a model that approximates that reality as closely as possible. And the aim of Chapter 5 "Data envelopment analysis methods in sustainable agricultural development research" is to determine the relative technical efficiency of representative agricultural farms from the individual European Union countries."--

In the past years qualitative methods have been discussed and practised in German social science as an alternative to conventional qualitative methods. In this paper some reasons for the use of qualitative methods in ethnomedical research are given. Starting from the assumption that the researcher has relatively little knowledge about his object research methods are suggested allowing to approach the object in an open manner with as few pre-conceptions as possible. Using as examples three methods (narrative interview, participant observation, objective hermeneutic) some typical expectations of and some problems associated with the use of qualitative methods are then discussed. It is shown that the regulative principle underlying the use of these methods is a "free-floating attention". Then it is discussed whether the investigation should be orientated towards observing natural situations or whether an artificial research situation should be created, as in the case of interviews. Furthermore, the central problem of qualitative research is taken into consideration: to ensure that the results obtained by these methods should reach an acceptably high scientific standard. It is argued that it is unwise to apply criteria used to test the validity of statements produced by quantitative methods to the testing of qualitative methods, and that it would be more advisable to develop criteria which better do justice to the methods of qualitative research. The paper concludes with some prospects for the future.

"This book consists of the following four parts: Motivations and Foundations; Elementary Probability and Statistics; Decision Making Models; and Advanced Statistical Modeling. Part I is introductory, and an initial chapter provides motivation for all of the subsequent chapters by means of simple, but (hopefully) well-thought, toy examples. The following two chapters lay down necessary foundations in calculus and algebra. Part II consists of a classical course in probability and statistics, and the author stresses the use of many examples and counter-examples. Part III addresses decision making since probability and statistics are used to make decisions. Deterministic models, i.e. typical LP models, are introduced, and the emphasis is on modeling rather than computation by the simplex method. Emphasis is also placed on risk aversion and risk measures, and the author illustrates portfolio management as a main motivator. Part IV builds on Part II and discusses a few multivariate analysis models. To help less mathematically inclined readers, each chapter in Part IV contains an initial section that illustrates and motivates each approach without delving into too many details. These readers may wish to skip the remainder of each chapter. The book's companion Web site includes Microsoft Office Excel workbooks to illustrate concepts. In addition, MATLAB files, additional excercises with solutions are provided online"--

Stellenausschreibung der HMU Health and Medical University Erfurt. Deadline: 21. März 2024