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Drivande faktorer bakom Tv-tittandepå den svenska marknaden: En regressionsanalys utifrån definierade målgrupper
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
2014 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [sv]

Det här kandidatexamensarbetet utreder huruvida multipel linjär regressionsanalys går att tillämpa på TV-tittarhistorik för att avgöra vilka programdynamiska faktorer som bidrar till höga tittarsiffror. Datan som ligger till underlag för den här analysen kommer från Mediamätning i Skandinavien, MMS. Slutsatser som har dragits i det här kandidatexamensarbetet är att det, inte utan svårigheter, går att tillämpa regressionsanalys på MMS-data. Det kräver bland annat omfattande bearbetning av datan, men också formulering av de programkategorierna som ska undersökas. Utöver det är TV-tittarhistorik som Y-variabel begränsad såväl nedifrån som ovanifrån, vilket kräver viss omtransformering för att kunna användas i regressionsanalysen. I det här arbetet används logaritmen av (Ƴ +1). Slutsatser kring programdynamiska faktorer som kunnat dras är att TV6 når ut bra i dagsläget till sin definierade målgrupp, medan TV3, TV8 och TV10 kan förbättra sitt TV-tablå-utbud för att bättre nå ut till sina respektive målgrupper. Programkategorier som Talkshows, Hjälp-TV-serier och Utslagstävlingar driver höga tittarsiffror, medan väderinslaget i Nyheterna borde uteslutas ur nyhetssändningen då de flesta byter kanal när det tar vid. Fortsatt analys av MMS-data med regressionsanalys rekommenderas eftersom det är ett rikt område där nya regressionsmodeller kan ställas upp för att utreda andra och/eller mer specifika variabler som påverkar TV-tittande.

Abstract [en]

This bachelor’s thesis investigates whether multiple linear regression analysis can be applied to analyse TV audience measurements in order to examine and draw conclusions about which program dynamics factors contribute to high ratings. The data that forms the basis for this analysis comes from Media Measurement in Scandinavia, MMS. The conclusion that has been drawn in this bachelor’s thesis is that it is possible, but not without difficulty, to apply regression analysis on MMS data. It requires, among other things, extensive processing of the data, but also a formulation of the program categories which are to be examined. In addition, the TV audience measurement as the Ƴvariable in the model is limited from above as well as from below, which requires transformation of the Y-variable for it to be used in regression modelling. In this bachelor’s thesis, the logarithm of is (Ƴ+1) used. Conclusions that could be drawn about program dynamics factors is that TV6 reaches its target audience well, while TV3, TV8 and TV10 can improve their TV guide, in order to better reach out to their target audiences. Program categories such as Talk Shows, Help TV series and Knockout Competitions drive high viewer ratings, while the weather forecast in the Newscast should be excluded, since most people change the channel when it begins. Continued use of regressions analysis on TV audience measurement is recommended, as it is a rich area where new regression models can be set up to investigate further and /or more specific variables which affect television viewing ratings.

Place, publisher, year, edition, pages
2014.
Series
TRITA-MAT-K, 2014_07
National Category
Mathematical Analysis
Identifiers
URN: urn:nbn:se:kth:diva-146736OAI: oai:DiVA.org:kth-146736DiVA: diva2:725051
Subject / course
Applied Mathematical Analysis
Educational program
Master of Science in Engineering - Industrial Engineering and Management
Supervisors
Examiners
Available from: 2014-06-14 Created: 2014-06-14 Last updated: 2014-06-14Bibliographically approved

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