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Logit, oddskvot och sannolikhet: En analys av multinomial logistisk regression
Karlstad University, Faculty of Economic Sciences, Communication and IT, Department of Economics and Statistics.
2019 (Swedish)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesisAlternative title
Logit, oddsratio and probability : An Analysis of Multinomial Logistic Regression (English)
Abstract [sv]

Den här uppsatsen inleds med att studera de moment som används för multinomial logistisk regression och hur resultaten mäts. Teorin tar sin avsats i den binomiala logistiska regression, för att stegvis ta sig vidare till den multinomiala logistiska regressionen. Begreppen logit, oddskvoten och sannolikheterna förtydligas, effekterna av de oberoende variablerna diskuteras och kopplingen till vanlig linjär regression åskådliggörs. Det blir även en fördjupning av matematiken bakom den logistiska funktionen.

Därefter tillämpas den multinomial logistisk regressionsanalysen med ett praktiskt exempel. Analysmodellen är användbar inom flertalet områden och den här uppsatsen ligger inom ramen för sportanalys. Matchstatistik från ishockey och närmare bestämt Örebro Hockeys matcher från säsongerna 2012/13 till 2017/18 nyttjas och den slutgiltiga modellen använder sig av tre förklarande variabler. Resultatet visar att utfallet efter ordinarie tid kan förklaras till 60,9% med hjälp av matchstatistiken, vilket tyder på att den multinomiala regressionsmodellen presterar likvärdigt med andra metoder som tillämpar kategorisk dataanalys inom sportanalys.

Abstract [en]

This thesis starts by studying the multinomial logistic regression and its moments and how the results are measured. The theory begins with the binomial logistics regression and gradually moves on towards the multinomial logistics regression. Concepts as logit, odds ratio and probabilities are explained, the effects of the independent variables discussed and the link to ordinary linear regression is illustrated. There will also be a deeper, mathematical look at the function of logistic growth.

Thereafter the multinomial logistic regression model will be applied. The model is useful within several domains and this thesis lies within sportsanalytics. For this thesis matchstatistics from ice hockey, that is Örebro Hockey’s matches from season 2012/13 to 2017/18, has been used and the final model has three exploratory variables. The outcome of the result performs equivalent to other methods, which applies categorical data analysis within sportsanalytics.

Place, publisher, year, edition, pages
2019. , p. 23
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:kau:diva-74575OAI: oai:DiVA.org:kau-74575DiVA, id: diva2:1346978
Subject / course
Statistics
Presentation
2019-06-24, Karlstad, 13:00 (Swedish)
Supervisors
Examiners
Available from: 2019-09-03 Created: 2019-08-29 Last updated: 2019-09-03Bibliographically approved

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