The use of marketing research panels are a more and more frequently used source of information for studies within many different branches. The purpose of this report is to investigate the demographic composition of panels and compare it with the population of Sweden, a possible change in behaviour of respondents, and if the source of recruitment is the cause of possible differences in study results. The study was commissioned by Norstats Linkoping office. Sources for the data material include Norstat’s recruitment process and their two main panels with different recruitment sources. To enable a deeper investigation of behaviour we also constructed a survey that was sent to 2,714 members of Norstat’s internet panels. The statistical analysis includes contingency table analysis, multiple logistic regression, and Poisson regression. The results show that the demographic composition does not fully cover all the aspects of the Swedish population and some groups are less represented than others. The behaviour tends to differ between panel members that have responded to three or less surveys compared to members that have responded to twenty or more surveys. Source of recruitment does not seem to affect the results of studies, but it has some effect on the demographic composition of marketing research panels. / Användandet av paneler som källa vid undersökningar har den senaste tiden blivit en allt vanligare företeelse. Denna rapport har för avsikt att undersöka panelers demografiska sammansättning och överensstämmande med Sveriges befolkning, eventuell ändring av svarsbeteende samt huruvida rekryteringskällan ger upphov till kvalitetsskillnader hos medlemmar i en panel. Företaget Norstat har med sitt kontor i Linköping figurerat som uppdragsgivare till arbetet. Datamaterialet till studien har uppkommit från Norstats rekryteringsprocess samt från företagets två huvudpaneler med olika rekryteringskällor. För att djupare undersöka svarsbeteende konstruerade vi även en enkätundersökning som skickades ut till 2 714 medlemmar i Norstats internetpaneler. Den statiska analysen innefattar χ2-test, multipel logistisk regression samt Poissonregression. Resultaten påvisade att den demografiska sammansättningen i panelen inte fullt ut speglade Sveriges befolkning samt att vissa grupper undertäcks i högre utsträckning än andra. Svarsbeteendet hos medlemmar i paneler har en tendens att ändras från det att medlemmen har svarat på en till tre undersökningar, till det att den har svarat på tjugo undersökningar eller fler. Rekryteringskällan till en panel verkar inte ge upphov till några större skillnader i svarsresultat, men däremot finns vissa skillnader i demografisk sammansättning.

Context: According to Swedish National Council for Crime Prevention, there is an increase in residential burglary crimes by 2% in 2014 compared to 2013and by 19% in the past decade. Law enforcement agencies could only solve three to five percent of crimes reported in 2012. Multiple studies done in the field of crime analysis report that most of the residential burglaries are committed by relatively small number of offenders. Thus, the law enforcement agencies need toinvestigate the possibility of linking crimes into crime series. Objectives: This study presents the computation of a median crime which is the centre most crime in a crime series calculated using the statistical concept of median. This approach is used to calculate the uniqueness of a crime series consisting of linked residential burglaries. The burglaries are characterised using temporal, spatial features and modus operandi. Methods: Quasi experiment with repeated measures is chosen as research method.The burglaries are linked based on their characteristics(features) by building a statistical model using logistic regression algorithm to formulate estimated crime series. The study uses median crime as an approach for computing the uniqueness of linked burglaries. The measure of uniqueness is compared between estimated series and legally verified known series. In addition, the study compares the uniqueness of estimated and known series to randomly selected crimes. The measure of uniqueness is used to know the feasibility of using the formulated estimated series for investigation by the law bodies. Results: Statistical model built for linking crimes achieved an AUC = 0.964,R 2 = 0.770 and Dxy = 0.900 during internal evaluation and achieved AU C =0.916 for predictions on test data set and AUC = 0.85 for predictions on known series data set. The uniqueness measure of estimated series ranges from 0.526to 0.715, and from 0.359 to 0.442 for known series corresponding to differentseries. The uniqueness of randomly selected crimes ranges from 0.522 to 0.726 for estimated series and from 0.636 to 0.743 for known series. The values obtained are analysed and evaluated using Independent two sample t-test, Cohen’s d and kolmogorov-smirnov test. From this analysis, it is evident that the uniqueness measure for estimated series is high compared to the known series and closely matches with randomly selected crimes. The uniqueness of known series is clearly low compared to both the estimated series and randomly selected crimes. Conclusion: The present study concludes that estimated series formulated using the statistical model has high uniqueness measures and needs to be furtherfiltered to be used by the law bodies.

信用風險或信用違約意旨金融機構提供給客戶服務卻未得償還的機率，故其在銀行信貸決策的領域是常被鑽研的對象，因為其對於金融機構所扮演的角色尤其重要，對商業銀行來說更是常難以解釋或控制，然而拜現今進步的科技所賜，金融機構可以藉由操控較過去低的成本即可進一步發展強健且精煉的系統與模型去做預測還有信用風險的控管，有鑑於對客戶的評分自大數據時代來臨起，即使是學生亦開始有了可以評鑑的痕跡，憑藉前人所實驗或仰賴的基本考量面向如客戶基本資料、財力狀況或是其於該公司今昔的借貸訊息，再輔以藉由開放資料所帶來的資訊，發想可能影響信用違約率的變數如外在規範對該客戶的紀錄，想驗證是否真有尚可開發的方向，若有則其影響可以到多深。 眾所皆知從過去到現在即有很多種方法被開創以及提出以預測信用違約率，當然所使用的方法和金融機構本身的複雜性、規模大小以及信貸類型有關，最常見的有判別分析，但其對於變數有嚴格的假設，而新興的方法神經網路可以克服判別分析的缺陷且預測的效能也不錯，但神經網路只給予預測結果而運算過程是未知的，對於想要了解變數間的關係無濟於事，故還是選擇從可以對二元分類做預測亦可以藉由模型係數看到應變數和自變數間關係的羅吉斯迴歸方法著手，而研究過程即是依著前人對於羅吉斯迴歸在信用風險上的繩索摸索，將資料如何清理、變數如何轉換、模型如何建立以及最後如何篩選做一個完整的陳述，縱然長道漫漫，對於研究假設在結果終得驗證也始見曙光，考慮的新面向確有其影響力，而在模型係數上也看到其影響的大小，為了更彰顯羅吉斯迴歸對於變數間提供的訊息，故在最後將研究結果以較文字易讀的視覺化方式作呈現。 / Credit risk or credit default means the probability of non-repayment that banks or financial institutions get after they provide services to their customers. Credit risk is also studied intensively in the field of bank lending strategy because it’s usually hard to interpret and control. However, thanks to advanced technology nowadays, banks can manipulate reduced cost to develop robust and well-trained system and models so as to predict and mange credit risk. In the light of the score on customers from the beginning of big data era, every single one can be tracked to assess even though he or she is student. Relying on common facets like personal information, financial statement and past relationship of loan in a specific bank, come up with possible variables like regulations which influence credit risk according to information from open data. Try to verify if there is a new aspect of modeling and how far it effects. As everyone knows, there are several created and offered methodologies in order to predict credit default. They differ from complexity of banks and institutions, size and type of loan. One of the most popular method is discriminant analysis, but variables are restricted to its assumption. Neural network can fix the flaws of the assumption and work efficiently. Considering the unknown process of calculation in neural network, choose logistic regression as research method which can see the relationship between variables and predict the binary category. With the posterior research on credit risk, make a complete statement about how to clean data, how to transform variables and how to build or screen models. Although the procedure is complicated, the result of this study still validates original hypothesis that new aspect indeed has an impact on credit risk and the coefficient shows how deep it affects.

Spezialprävention – im Sinne der Verminderung von Rückfällen durch Resozialisierung, Abschreckung und Sicherung – gilt als eine der wichtigsten Aufgaben des Strafrechts. Dem entgegengesetzt schreibt der Etikettierungsansatz der Bestrafung einen negativen Effekt auf die Legalbewährung zu. Was die deutsche Strafrechtspraxis in dieser Hinsicht bewirkt, ist allerdings weithin unbekannt. Kriminologische Untersuchungen auf dem Gebiet der Wirkungs- und Behandlungsforschung zeigen keine eindeutigen empirischen Befunde. Zudem sind sie meist zeitlich und räumlich eng begrenzt. In der hier vorgestellten Arbeit soll der Frage nachgegangen werden, ob sich der spezialpräventive Erfolg des Strafrechts mit Hilfe von Bundeszentralregisterdaten empirisch prüfen lässt. Die Arbeit stützt sich auf Daten und Auswertungen, die im Rahmen der Legalbewährungsuntersuchungen 1994-1998 und 2004-2007 erstellt wurden. Diese dort präsentierten deskriptiven Auswertungen werden kritisch analysiert; die Datenanalyse wird durch den Einsatz quasi-experimenteller und multifaktorieller Methoden dort verfeinert, wo es notwendig und sinnvoll erscheint. Mit Hilfe dieser Methoden soll der Frage der – positiven oder negativen – Wirkung der Strafen nachgegangen werden, indem Effekte von personen- und tatbezogenen Prädiktoren kontrolliert werden, um den Effekt der Strafe auf die Wiederverurteilung zu isolieren. Darüber hinaus wird eine deskriptive Analyse der Legalbewährungsdauer, nach unterschiedlichen Sanktionsformen vorgestellt und mit Hilfe von Ereignisanalysen differenziert. Die Ergebnisse zeigen, dass auch unter Berücksichtigung anderer Prädiktoren eine schwächere, aber eigenständige Sanktionswirkung zu beobachten ist. In der Mehrzahl der Fälle zeigen sich geringere (monatliche) Rückfallraten nach weniger eingriffsintensive ambulante Sanktionen als nach schwereren Sanktionen. Hier von negativen Sanktionswirkungen zu sprechen ist dennoch voreilig. Weitere differenzierte Analysen für homogenere Tätergruppen und regionale Vergleiche erscheinen notwendig. Möglichkeiten und Chancen für weiterführende Auswertungen werden sich auch durch die Fortführung der Rückfalluntersuchungen ergeben.

Scandinavian Airlines has a large database containing their Eurobonus members. In order to analyze which customers they should target with direct marketing, such as emails, uplift models have been used. With a binary response variable that indicates whether the customer has bought or not, and a binary dummy variable that indicates if the customer has received the campaign or not conclusions can be drawn about which customers are persuadable. That means that the customers that buy when they receive a campaign and not if they don't are spotted. Analysis have been done with one campaign for Sweden and Scandinavia. The methods that have been used are logistic regression with Lasso and logistic regression with Penalized Net Information Value. The best method for predicting purchases is Lasso regression when comparing with a confusion matrix. The variable that best describes persuadable customers in logistic regression with PNIV is Flown (customers that have own with SAS within the last six months). In Lassoregression the variable that describes a persuadable customer in Sweden is membership level1 (the rst level of membership) and in Scandinavia customers that receive campaigns with delivery code 13 are persuadable, which is a form of dispatch.

La présente recherche vise, dans un premier temps, à mieux documenter la relation entre les hallucinations auditives impérieuses à contenus violents et le risque d’obéissance à celles-ci. Plus spécifiquement, l’étude, subséquente au bilan de recherches antérieures sur le sujet, tente d’identifier les facteurs de risque associés à l’obéissance aux hallucinations auditives impérieuses dont les contenus violents sont dirigés vers soi chez une population d’individus aux prises avec un trouble mental grave. Pour ce faire, des analyses secondaires ont été effectuées à l’aide de la base de données de l’étude de MacArthur sur l’évaluation du risque de violence. Des analyses de régression logistique binaire ont révélé que la détresse émotionnelle, l’historique d’obéissance, le fait d’avoir un trouble actuel d’abus de drogue, un trouble actuel de dépression majeure, le fait d’avoir été victime d’abus physique durant l’adolescence ainsi que la sévérité du phénomène hallucinatoire prédisaient tous l’obéissance aux hallucinations auditives impérieuses dont les contenus violents étaient dirigés vers soi. L’étude met en évidence une modélisation prédictive importante afin de guider les cliniciens vers une meilleure évaluation et gestion du risque de gestes automutilatoires et suicidaires en réponse aux hallucinations auditives impérieuses chez les individus aux prises avec un trouble mental grave. / The current research consist, in a first step, to better document the relationship between harmful command hallucinations and compliance. More specifically, the study resulted from a literature review on this subject that aims to identify the risk factors associated with compliance to self-harm command hallucinations in individuals with a major mental disorder. To accomplish this, secondary analyses were performed using the MacArthur Violence Risk Assessment Study database. Binary logistic regressions revealed that emotional distress, history of compliance, actual drug abuse disorder, actual major depressive disorder, victimization of physical abuse during adolescence and severity of the hallucinatory behavior were all significant predictors of compliance to self-harm command hallucinations. The study highlights an important predictive model that may guide clinicians to improve the assessment and management of deliberate self-harm and suicidal behaviors in response to command hallucinations in individuals diagnosed with a major mental disorder.

Magister Economicae - MEcon / The main objective of this study was to identify ways in which transaction costs can be lowered to improve small-scale farmers’ participation in and returns from agricultural output markets, with specific reference to small-scale mango farmers in Limpopo province. This study hypothesizes that transaction costs are lower in informal spot markets and increase when small-scale farmers sell in more structured markets (formal markets). This study builds on transaction cost economics (TCE) to demonstrate how to overcome transaction cost barriers that small-scale mango farmers face in the agro-food markets. The approach to collect primary information was sequenced in two steps: first, key informant and focus group interviews were conducted and, secondly, a structured survey instrument was administered in two districts of Limpopo. A total of 235 smallscale mango farmers were interviewed. A binary logistic regression model was used to estimate the impact of transaction costs on the likelihood of households’ participation in formal (=1) and informal (=0) agro-food markets. STATA Version 10 was used to analyse the data. This study found that a larger proportion of male than female farming households reported participation in the formal markets, suggesting deep-seated gender differentiation in market participation. The average age of small farmers participating in formal markets is 52, compared to 44 for those in informal markets, implying that older farmers might have established stronger networks and acquired experience over a longer period. Farmers staying very far from the densely populated towns (more than 50 km) participate less in the formal markets than those staying closer (0 – 25 km and 26 – 49 km), which implies that the further they are from the towns, the less the likelihood of farmers selling in the formal markets. Farmers who own storage facilities and a bakkie (transportation means) participate more in formal markets compared to those who do not own these assets, which suggests that these farmers are able to store mangoes, retaining their freshness and subsequently delivering them to various agro-food markets on time. Households that participate in formal markets have high mean values of income and social grants. However, this study found that the likelihood of a household’s participation in the markets is less as income and social grants increase. This suggests that households do not invest their financial assets in order to overcome market access barriers. A large proportion of households that own larger pieces of arable land participate in the formal markets, which implies that they are able to produce marketable surplus. Households that have a high mean value (in Rand) of cattle participate more in formal markets than in informal markets. However, this study found that the likelihood of a household’s participation in the markets does not change with an increase in the value of its livestock. These findings suggest that households do not sell their cattle in order to overcome market access barriers. Reduced transaction costs for small-scale mango farmers in Limpopo should improve their participation in and returns from the agro-food markets. Policy interventions to support this need to focus on: access to storage and transportation facilities, enforcement of gender equity requirements in existing policies, and better access to information about markets. / South Africa

The master thesis deals with failed studies at universities in the Czech Republic. The first part is focused on literary research, on explanation of theoretical terms and on statistical methods, which are subsequently applied in the analytical part. These are decision trees and logistic regression that helped to determine the influence of factors on studies without graduation. The aim of this master thesis is to find significant factors, to compile a profile of failed students and to suggest the measures which could reduce their elimination from tertiary education.

Basal Temperature of Snow (BTS) measurements were used as the primary inputs to a high resolution (30 x 30 m grid cells) empirical-statistical regional permafrost probability model for the southern and central Yukon, and northernmost British Columbia (59° - 65°N). Data from seven individual study areas distributed across the region were combined using a blended distance decay technique, with an eighth area used for validation. The model predictions are reasonably consistent with previous permafrost maps for the area with some notable differences and a much higher level of detail. The modelling gives an overall permafrost probability of 52%. North of 62°N, permafrost becomes more extensive in the lowland areas whereas farther south permafrost is typically common only above treeline. Significant differences exist between the mountain environments of the Yukon and the Swiss Alps where the BTS method originated and as a result different modelling approaches had to be developed. This work therefore: (1) develops additional explanatory variables for permafrost probability modelling, the most notable of which is equivalent elevation, (2) confirms the use of ground truthing as a requirement for empirical-statistical modelling in the Yukon and (3) uses a combination of models for the region in order to spatially predict between study areas. The results of this thesis will be of use to linear infrastructure route-planning, geohazard assessment and climate change adaptation strategies. Future work employing the model will allow the effects of scenario-based climate warming to be examined.

L'objectif de la recherche est de questionner le comportement des firmes multinationales issues de pays émergent (FMNE) lors de leur première acquisition majoritaire à l'international. En effet, devenue un phénomène d'ampleur mondial, l'internationalisation de ces firmes du Sud représente une nouveauté, une menace, mais également une opportunité dans le paysage économique mondial. Notre étude teste empiriquement les théories classiques du management international pensées pour les firmes du Nord (FMN) selon des méthodes quantitatives appliquées à un échantillon unique de 504 FMNE issues de la base de données SDC Platinum. Les résultats montrent qu'il existe trois catégories de FMNE influencées par les attributs du pays cibles, leur expérience d'acquisition internationale et leur réseau d'affaires étendu. En revanche, ces mêmes entreprises ne sont influencées ni par les attributs de leur pays domestique ni par leur expérience d'acquisition domestique ni par leur réseau d'affaires proche. Ces résultats éclairent ainsi les connaissances du champ des FMNE en confirmant certaines études dans la littérature tout en en contredisant d'autres. Ce travail de recherche précise donc un ensemble de connaissances scientifiques relatives au phénomène des FMNE et cristallise les réponses aux questionnements du champ à travers l'étude empirique des acquisitions majoritaires à l'international. / The research aims to investigate the emerging multinationals' (EMNE) behaviour through their first international acquisition. Indeed, because of the scope and scale of this international phenomenon, the internationalization of these firms portrayed a novelty, a threat, and an opportunity in the worldwide landscape as well. Our study tests empirically the international management theories basically thought for firms from industrialized economies (MNE) according to quantitative methodologies applied on a unique sample of 504 EMNE from SDC platinum database. The results find three EMNE groups influenced by target-country characteristics, international acquisition experience and extensive network. However, these same firms are not influenced by domestic-country characteristics, their domestic acquisition experience and their close network. These results highlight the field both in corroborate some studies and refute others. This research finally clarifies a set of scientific knowledge related to the EMNE phenomenon through an empirical study of the international acquisitions.