Methodology of statistical surveys and official statistics in the Swedish university curriculum Kiev 2009 Daniel Thorburn Stockholm University

Swedish University System 6Large universities –Uppsala, Lund, Gothenburg, Stockholm, Umeå, Linköping 6Specialized universities –Tecnical, medical, economical, agricultural 3Small universities –Örebro, Karlstad. Växjö More than 25 University colleges

In Sweden, Statistics is taught by many subjects Statistics Mathematical statistics Applied fields: –Psychology, Sociology, Political Science, Economics, Market Research …

Higher Educational system in Sweden Adapting to the Bologna system (but the system is obstructed from many teachers and universities) –Ordinary school 12 years –Bachelor 3 years (180 ECTS-credits) – 90 credits in main subject –Master 2 years (120 ECTS credits, Swedish students have been uninterested) –Ph D 4 years (240 ECTS credits) - 1 year less if the Master exam was suitable Old system: –3-5 years undergraduate (”Kandidat” – ”Magister”) –4 years graduate

Number of universities with statistical teaching at different levels (My guesstimates) Ph. D. levelBachelor levelSome statistics StatistM StatStatistM StatStatistM Stat Large Special Small University Colleges 0020>10?

Universities with survey sampling within statistics/math statistics (my guesstimates) LevelPh DMasterBachelor/ Undergraduate With special survey programme >30 ECTS credits in Surv Sampl Some activity Statistics423>30 Mat stat200?

Stockholm (now) – as an example First semester: –15 credits Statistical theory –15 credits Data collection and analysis Second semester: –15 credits Statistical theory and regression, –7.5 credits Sampling, –7.5 credits Optional (usually Multivariate or Time series) Third semester: –7.5 credits Statistical theory –7,5 credits Optional ( usually Survey quality or one above) –15 credits Thesis Fourth and fifth semester –More optional courses + 15/30 credits Thesis

First course:A Data collection and Analysis Statistical surveys from information need to report. – Little about everything planning, cost-benefit analysis, searching for existing data, frame construction, existing registers and data bases, secondary analysis, sampling, (SRS, cluster, stratified, systematic), editing, questionnaire construction, editing, coding and classification, privacy and integrity, avoiding and handling non- response, point and interval estimation, statistical report writing, sudoku (survey dokumentation) …

Main Literature First course: Dahmström, Karin, Från datainsamling till rapport, Studentlitteratur 3rd edit 2004?? Sampling course: Mendenhall, Ott, Shaeffer, ??? Survey quality course: Biemer, Lyberg, Wiley ???

Master in Survey methods and public statistics 12 courses, 5 ECTS each Special methodology Survey methods Sampling and estimation Statistical data bases and registers Analysis of survey data Economical statistics Official statistics General statistics Mathematics for statisticians Probability Inference Statistical computations Statistical methods (15 ECTS) Master Thesis (30 ECTS)

Survey Methods – All non-sampling aspects Frame quality Dark numbers Non-response* (avoiding, reporting) Questionnaire construction* Pilot studies Control studies The quality concept, TQM* Relevance, validity Timeliness (Actuality, linkage) Consistancy, co-usability International harmonisation …

Sampling and estimation Sample surveys in general, Regression estimators, GREG, Stratified sampling Optimisation, Ratio estimators. Sampling with varying inclusion probabilities, Combined frames, Normality, Asymptotic results, Imbedded experiments, Sampling in medicine e.g. case-control Subsampling in the non- response, Quality studies, Meta-analysis. Cluster sampling, Variance estimation, Resampling, Longitudinal studies, Estimation with non-response, Other parameters quantiles, domains

Statistical data bases and registers Statistical aspects on statistics from registers and register construction, matching problems, consistency, quality … Wallgren & Wallgren Infological aspects on registers och data bases, conceptual models, units or variables, metadata, hypercubes … Sundgren Other aspects e.g. Data mining, Decision tree techniques, Existing data bases in medicine and finance/economy and examples of statistics from them

Analysis of survey data Modelbased analysis from survey data with varying inclusion probabilities Linear regression (parameter definition in finite populations) Hasard regression (e.g. mortality) Multivariate models (e.g. factor analysis) Much practical work with computer A few large case studies

Economic statistics National accounts, theory and methods Indices (price- and volume- ), theory and methods Other Aspects: –Editing –Imputation –Sampling with skew variables –Cordinated samples, permanent random numbers –Time series linkage and seasonal adjustment –Data collection from economic entities

Official statistics Will be given next spring for the first time. Contents not decided fully yet –Integrity and Privacy, –Ethical and Judicial aspects –Administrative aspects, –Timeliness, –Rationalisation, –Cost-Benefit analysis –...