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Norstat recurrently performs a survey that contains questions about how much the respondent is watching different tv-channels, how different media-devices are used, the ownership of different devices and the usage of different tv-channel sites on the internet, social media, internet services, magazine services and streaming services. In this thesis, data from the survey performed during the autumn of 2016 was used. The aim of this thesis is to examine if there is a difference in answers based on different characteristics of the interviewers and respondents.  The 15 most important questions from the survey were chosen in this thesis, and to further reduce the number of response variables principal component analysis was used. The new scores that were produced by the analysis were the reduced response variables, which kept the most important information from the questions in the survey. Thereafter multilevel analyses and regression analyses were performed to examine the effects.   The results showed that there was an effect of different characteristics in different questions in the survey. The characteristics that showed effect were the age of the interviewer, the length of the employment, the age of the respondent, education, sex and native language. Some of the questions also showed effect based on whether the respondent lived in a metropolitan region or not. / Norstat genomför en återkommande undersökning om hur mycket respondenten tittar på olika kanaler, hur olika media-apparater används, ägande av olika apparater, användning av kanalers sidor på internet och sociala medier samt internettjänster, tidningstjänster och streamingtjänster. Datamaterialet som ligger till grund för denna uppsats kommer från undersökningen när den ägde rum under hösten 2016. Syftet med uppsatsen är att hitta skillnader i enkätsvaren som uppstått av olika egenskaper hos intervjuaren och respondenten. De 15 viktigaste enkätfrågorna valdes och i denna uppsats har principalkomponentanalys används för att reducera antalet responsvariabler ännu mer. Det gjordes genom att skapa score som är ett färre antal responsvariabler vilka tillsammans förklarar de olika enkätfrågorna i undersökningen. Därefter har multilevelanalyser och regressionsanalyser använts för att analysera bakgrundsvariablernas påverkan på enkätfrågorna. Resultatet visade att det fanns effekt av olika egenskaper i olika sorters enkätfrågor. De egenskaper som visade effekt var intervjuarens ålder och anställningstid samt respondentens ålder, utbildning, kön och modersmål. Vissa frågor påverkades även av om respondenten bodde i en storstadsregion eller inte.

A simulation study is carried out to compare three distance-based classifiers for their misclassification and asymptotic distributions when the data follow certain elliptically contoured distributions. The data are generated from multivariate normal, multivariate t and multivariate normal mixture distributions with varying covariance structures, sample sizes and dimension sizes. In many of the simulated cases, the dimensions of the data are much larger than the sample size. The simulations show that for small dimension sizes, the centroid classifier generally performs better. The nearest neighbour classifier shows superior performance compared to the other classifiers when the covariance structure is of compound symmetry form. All three classifiers showed to have asymptotic normal distribution, regardless of the underlying distribution of the data.

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