<p>Wind is used as an energy source all over the world. To be able to use this effectively, there is a need for as good forecasts and forecast models as possible. One of these models is Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®) that is used to calculate short time forecasts. This model is used here to calculate wind speeds at two different areas in Västra Götaland, Bengtsfors and Vänersborg. There are also wind measurements with SODAR stations for these areas. The first part of this work is to investigate the difference between two model resolutions, 36 and 12 km, for the model results compared with the measurements. The comparison is done by calculating some different statistical values. The results of these parameters show that the difference between the two resolutions is fairly small and that the lower resolution gives a slightly better result.</p><p>The second and major part of this work is to use two different regression models to adjust the result of the forecast models to the result of the measurements. These regression models will then be possible to use even when there are no measurements to compare with. The idea of these regression models is to find a way to describe the difference between the result of the forecast model and the SODAR measurements. This difference is then subtracted from the result of the forecast model so that you get an adjustment and more accurate result. The first regression model calculates the difference according to time of the day, the other model calculates the difference according to the wind speed.</p><p>Furthermore, the measurements used are taken from 75 meters height above the ground. These are then compared to some different results from the forecast model, for example different model heights and different resolutions, and also the model results adjusted with the regression models. The comparison is done by calculating the same statistic values as before, both with and without an adjustment with the regression models, and also to look at histograms that show the distribution of the difference. It is shown that with the regression adjustment, there is a clear improvement of the statistical values compared to the original results of the forecasts. For example the value of the absolute mean difference is reduced with approximately 0.4-0.7 m/s with an adjustment of the regression model. The histograms clearly show that a more even distribution occurs after the adjustment with the regression models. From having a major part of the differences at 1-2 m/s to now having the major part at around 0 m/s and furthermore there is also generally a lower difference between the measurements and the results from the forecast model.</p>

Wind is used as an energy source all over the world. To be able to use this effectively, there is a need for as good forecasts and forecast models as possible. One of these models is Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®) that is used to calculate short time forecasts. This model is used here to calculate wind speeds at two different areas in Västra Götaland, Bengtsfors and Vänersborg. There are also wind measurements with SODAR stations for these areas. The first part of this work is to investigate the difference between two model resolutions, 36 and 12 km, for the model results compared with the measurements. The comparison is done by calculating some different statistical values. The results of these parameters show that the difference between the two resolutions is fairly small and that the lower resolution gives a slightly better result. The second and major part of this work is to use two different regression models to adjust the result of the forecast models to the result of the measurements. These regression models will then be possible to use even when there are no measurements to compare with. The idea of these regression models is to find a way to describe the difference between the result of the forecast model and the SODAR measurements. This difference is then subtracted from the result of the forecast model so that you get an adjustment and more accurate result. The first regression model calculates the difference according to time of the day, the other model calculates the difference according to the wind speed. Furthermore, the measurements used are taken from 75 meters height above the ground. These are then compared to some different results from the forecast model, for example different model heights and different resolutions, and also the model results adjusted with the regression models. The comparison is done by calculating the same statistic values as before, both with and without an adjustment with the regression models, and also to look at histograms that show the distribution of the difference. It is shown that with the regression adjustment, there is a clear improvement of the statistical values compared to the original results of the forecasts. For example the value of the absolute mean difference is reduced with approximately 0.4-0.7 m/s with an adjustment of the regression model. The histograms clearly show that a more even distribution occurs after the adjustment with the regression models. From having a major part of the differences at 1-2 m/s to now having the major part at around 0 m/s and furthermore there is also generally a lower difference between the measurements and the results from the forecast model.

Penningtvätt i Sverige är sedan tidigare föga utforskat. I denna studie är syftet att undersöka penningtvätt i Sverige vad det gäller brottsstrukturen, gärningspersoner samt statistiska samband för dessa. Studien är ett uppdrag utfärdat av Länskriminalpolisen i Skåne. Materialet har bestått av straffrättsliga domslut hämtade ifrån Blendow Lexnovas rättsfallsdatabas. Utifrån domsluten kodades variabler vilka matades in i SPSS där statistiska analyser genomfördes. Resultaten visar bland annat att mest pengar återinvesteras i företag, gärningspersonerna är typiskt män i 40-årsåldern med brottslig bakgrund samt det finns ett flertal statistiska samband mellan olika aspekter av brottsstrukturen för penningtvätt. I diskussionen framhävs att resultaten möjligen kan användas i uppdragsgivarens operativa verksamhet samt att mer forskning generellt behövs om penningtvätt. En slutsats som dras är att resultaten bör generaliseras med försiktighet då brister återfinns i materialet. / Money laundering in Sweden has previously been little explored. The purpose of this study is to investigate money laundering in Sweden in terms of crime structure, perpetrators and statistical correlations for these. The study is a commission issued by the County Criminal Police in Skåne. The material has consisted of criminal judgments downloaded from Blendow Lexnova’s database of court cases. Variables were encoded which were entered in SPSS where statistical analyses were conducted, based on the criminal judgments. The results demonstrate, among other things, that most of the money is precipitated in companies, the perpetrators are typically men which are 40 years of age with criminal background and there are a number of statistical correlations between the different aspects of crime structure for money laundering. In the discussion, following things are highlighted: the results can possibly be used in the operational activities of CCP and more research is needed on money laundering in general. A conclusion to be drawn is that the results should be generalized with caution when deficiencies are found in the material.

I denna uppsats utvärderar författarna den metod Statistiska Centralbyrån använder sig av vid befolkningsframskrivningar. Metoden fungerar relativt bra vid prognoser över totalbefolkningen, men det visade sig att det blev problem med prognosen av individer i mycket unga och mycket äldre åldrar.

Today in a modern society the pace is high and the need for flexibility and mobilityis big. Despite the increasing access and great digital solutions for online-meetings,the need for short distance transportation remains. With an increasing number ofeasy-to-use mobile applications, the many offered solutions for personal transporta-tion have in the last few years expanded. Besides the effect of an increasing pressureof road space, the pressure on the transportation solutions has escalated. This is the current situation of the company we came in contact with. Their currenttravel service provides on-demand transportation in small electric, emission free andchauffeur driven vehicles they call pods. As a step of claiming their space in thetransportation sector they are developing their application letting customers planand book a transport. For the ability to test their new booking solution this project took form. With asimulation it would be possible to test the various probabilities of a travel outcome.The aim was to develop a simulation software, simulating the events of multipletravels taking place in the system. With the simulation it would be possible to eval-uate the configuration for the booking feature, analyse how it works with the rest ofthe system and to help the company to predict how the intensity of customers in re-lations to the number of available drivers would affect the outcome of a travel request. The project covered the study of how to interpret the factors, that a transportationdirectly depends on, into events in the system and how to use historical events tocreate probabilities of the simulation outcome. The simulator software was not suc-cessful with simulating multiple rides as intended, but parts of the software could beevaluated in relation to historical events. Statistical models were built using aggre-gated events from the system. When comparing the average result of the statisticalmodels with the historical event count of the system, it resulted in an outcomewithin an acceptable range. This shows that it was possible to use aggregated his-torical events to create probabilities and that these probabilities were reliable.

Turism är en av världens största industrier, och dess påverkan på platser och människor är ett mångfacetterat fenomen med både positiva och negativa konsekvenser på ekonomiska, kulturella och sociala domäner. Eftersom tidigare studier visar på att turism även kan ha en påverkan på invånares psykiska hälsa är syftet med den här studien att undersöka effekterna av turism på lokalbefolkningars psykiska hälsa. Detta görs med en sambandsanalys av variabler kopplade till turism och psykisk hälsa, baserade på data över Sveriges kommuner. Samband testas med hjälp av Pearsons korrelation och multivariat analys. Resultatet visar att det finns få robusta samband mellan turism och psykisk (o)hälsa i Sverige, och att de statistiska samband som finns inte är entydiga. Detta innebär att resultaten från tidigare studier inte kan valideras i denna undersökning. Skillnaderna gentemot tidigare studier kan delvis förklaras av att tidigare forskning främst genomförts i Spanien, där turistnäringen är större än i Sverige.

One of many challenges in information architecture is to simplify information and make it understandable. In order to make sense of abstract data such as statistical information and to reach out to many, there are several methods and digital tools to be used to visualize the statistics. This thesis has been studying how Statistics Sweden is working to make their information reach the public. Focusing on usability, based on UX design principles, a quantitative case study was conducted with two data collection methods applied: semi-structured interview and web page analysis. The result of the study shows that Statistics Sweden is consistently working to make information accessible to the public and to present statistical information in relation to the design principles. However, there are areas which can be improved including variation in how the statistics are presented and that they to a greater extent can use digital tools to visualize the statistics in a more interesting way.

Den anadroma öringen i Östersjöns avrinningsområde uppnår inte tillfredsställande status och uppskattningsvis upprätthålls ungefär hälften av populationerna med kompensationsodling. En av dem är Dalälvens anadroma öring som numer har sitt reproduktionsområde vid Älvkarleby, ca 10 km uppströms älvmynningen till Östersjön. Där finns även ett vattenkraftverk som innebär ett definitivt vandringshinder för Dalälvens migrerande arter. Vid Älvkarleby bedriver SLU Aqua forskning på öring och lax, samt ansvarar för kompensationsodlingen av Dalälvens anadroma öring. Tack vare det långvariga kompensationsodlingsprogrammet finns långa tidsserier innehållandes populationsdynamiska och strukturella data om populationen i Dalälven. I denna studie beskrivs långtidstrender i detta data, och med hjälp av statistiska metoder identifieras potentiella påverkansfaktorer. Resultaten visar att studieperioden kännetecknas av kraftiga populationsdynamiska fluktuationer, och temperatur identifierades som en stark påverkansfaktor. / Anadromous trout populations in the Baltic Sea area are in a less than optimal state and about half of the populations are maintained by hatchery-reared trout. One of the populations spawns near Älvkarleby of river Dalälven, about 10 km upstream of the estuary in the Baltic Sea. A hydroelectric dam located in the same area blocks the routes of migratory species. SLU Aqua operates the cultivation of trout native to river Dalälven and conducts research at the research center in Älvkarleby. Owing to the long-term cultivation in river Dalälven, long time-series containing population-specific data is available. Based on the collected data, this study describes long-term trends in the trout population native to river Dalälven and tries to identify potential factors effecting these by using statistical methods. The results show that the study period is characterized by large fluctuations in population dynamics, and that temperature is a major influencing factor.

BackgroundLKAB has struggled for years with measuring the amount of water that fines are containing when it leaves the filters. This is desirable because if the watercontent could be measured it would be easier to keep it stable on a suitable level and the waste in the process could be reduced. MethodThis paper explores the possibility to through predictions based on surrounding signals predict the water content of the fines with desirable precision. These signals are processed with statstical methods and models which will be compared. The models used are Linear-, LASSO, Random Forest- and Additive Models. ResultThe investigations suggests that interaction terms between predictors are not significant and neither are non-linear interactions between predictors and the response. The more complex models which includes more predictors does notperform better than the simpler ones. ConclusionThe resulting best model is a Simple Linear Model which includes the predictor Negative Pressure. This model has a measuring error which is estimated to be around +- 0.5 percentage points which can be compared to a water content percentage of about 7.5-10.5%. There is a LASSO-Model that generates a smaller estimated measuring error but the difference is not considered to be large enough to outweigh the increased complexity of the model. / BakgrundAtt mäta fukthalt i slig i direkt anslutning till de filter som torkar upp slig från slurry på ett till förlitligt sätt har i många år varit en utmaning för LKAB. Att kunna göra detta är önskvärt för att i förlängningen hålla fukten på en stabil nivå och därmed effektivisera pelletiseringsprocessen. MetodDenna uppsats undersöker möjligheten att genom prediktion baserat på kringliggande signaler prediktera fukthalten i sliget med önskvärd precision. Dessa signaler hanteras med hjälp av statistiska metoder och modeller som jämförs med varandra. De modeller som kommer att användas är Linjära-,LASSO-, Random Forest- samt Additiva Modeller. ResultatUndersökningen visar på att samspel mellan prediktorer ej är signifikanta och inte heller icke-linjära samspel mellan prediktorer och fukthalt. Vidare visar undersökningen att de mer komplexa modellerna som tar in fler prediktorer inte presterar bättre än de enklare. SlutsatsDen resulterande bästa modellen är en Enkel Linjär Modell som bygger på prediktorn Undertryck och har ett mätfel som i snitt över filtren skattas till +-0.5 procentenheter, att jämföra med en fuktalt på 7.5-10.5%. En LASSO-modell genererar ett mindre skattat mätfel men det anses ej vara nog mycket mindreför att väga upp för dess mer komplexa uppbyggnad.

Varje år delar aktiebolag i Sverige ut stora summor pengar i formav aktieutdelningar. Storleken på ett företags utdelningar anses blandmånga aktiesparare vara en viktigt faktor då de avgör om de ska köpaaktier i företaget. Det är ett stort beslut för ett företag när de bestämmervilken utdelning de vill ge, och det är ett beslut som tvingar företagetatt ta hänsyn till många faktorer. En stor utdelning kan göraföretagets aktier mer attraktiva, men leder till att företaget har mindreeget kapital att använda för exempelvis produktutveckling och andrainvesteringar. I detta examensarbete inom matematisk statistisk görsen multipel linjär regressionanalys för att modellera direktavkastningen,d.v.s. utdelning dividerat med aktiekurs, för stora svenska företagverksamma inom fastighet och finans (FF); teknologi, hälsa och telekom(THT) och industri. En regressionsmodell gjordes för vardera avdessa tre företagsgrupper, och statistiska test utfördes för att bedömahur bra dessa modeller beskriver relationen mellan direktavkastningoch de företagsvariabler som användes som förklarande variabler. Studiensresultat visar att regressionsmodellen som gjordes för företag inomfastighet och finans är bättre än de som gjordes för industri ochteknologi, hälsa och telekom.