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This book is intended as a textbook for a first course in applied statistics for students of economics, public administration and business administration. A limited knowledge of mathematics and - in one single chapter - some knowledge of elementary matrix algebra is required for understanding the text. Complicated mathematical proofs are avoided and the explanations are based on intuition and numerical examples. The aim of this book is to enable the student to understand the reasoning underlying a statistical analysis and to apply statistical methods to problems likely to be met within the fields of economics, public administration and business administration. The topics covered by the book are: - methods for exploratory data analysis - probability theory and standard statistical distributions - statistical inference theory - and three main areas of application: regression analysis, survey sampling and contingency tables. The treatment of exploratory data analysis, regression analysis and the analysis of contingency tables are based on the most recent theoretical developments in these areas. Most of the examples have never been presented before in English textbooks

The spatial configuration of the agricultural landscape and the organization of farming practices have strong effects on the flows and balances of nutrients and organic matter and their environmental impacts. This has been acknowledged to varying degree in the different generations of action plans, legislation and strategies implemented in Denmark to reduce the impact on the terrestrial and aquatic environment. The aim of this paper is to analyse three decades of environmental regulation of the farming sector in Denmark, with a focus on the underlying landscape paradigms and agro- and landscape ecological models. The study includes analyses of policy documents, action plans, legislation, guidelines and other implementation papers. We identify spatially targeted measures and underlying assumptions regarding the landscape and assess the landscape component of models used for policy design and evaluations. Additionally, we interview key stakeholders involved in the different stages of implementation to identify the main drivers and motives in policy design. There has been a considerable development of ecological models and availability of data during the three decades of N, P and OM related regulation in Denmark. In the early plans of the 1980s focus was on simple measures such as improving manure storage facilities and handling with no or few links to landscapes. This changed with the introduction of fertilization plans (1987) and norm based fertilizer rules (1991). However, the measures were still largely based on simple field-scale models focusing on leaching from the root-zone ignoring spatial variation and horizontal fluxes. Gradually more advanced models that included the landscape level were introduced along with the implementation of measures with spatial components such as wetland restoration, environmental approval of husbandry farms, buffer-zones and voluntary schemes targeted to designated areas. Today tools include the spatial configuration and organization of the landscape in the modelling and assessment of nutrient fluxes and balances. However, the use of modelling tools is increasingly questioned as to their reliability arguing that on-site specific measurements rather than model results are needed. The models and data required to design and assess spatially differentiated measures to reduce the nutrients load from Danish agriculture has been developed and improved considerably since the implementation of the first mitigation measures in the mid-1980s. Also, the need for spatially differentiated policies was identified at an early stage of the process we have described. However, the implementation of spatially differentiated measures has been slow as a consequence of the Danish approach to (non)targeting. Today there is a broad consensus among stakeholders and farmers on the need for spatially differentiation and the next generation of measures are likely to reflect this. This will target the mitigation efforts towards high load areas affecting vulnerable ecosystems, whereas it is still uncertain if it also will include fewer restrictions on farming in areas which have less environmental impact. This work is partly funded by the Strategic Research Alliance DNMARK (2013–2017) funded by The Danish Innovation Foundation.