Daftar Referensi Buku Statistik dan Buku Aplikasi Software Statistik ( SPSS LISREL AMOS PLS SAS STATA SPLUS R )

Berikut adalan sebagian Daftar Buku-Buku Aplikasi Software Statistik ( SPSS LISREL AMOS PLS SAS STATA SPLUS R )

  • Advances in Clinical Trial Biostatistics by Nancy L. Geller
  • Analysis of Incomplete Multivariate Data by Joe Schafer
  • Analysis of Messy Data, Volume III: Analysis of Covariance by George A. Milliken Dallas E. Johnson
  • Analysis of Pretest-Posttest Designs by Peter L. Bonate
  • Applied Nonparametric Statistical Methods, Third Edition by Peter Sprent Nigel Charles Smeeton
  • Applied Statistical Designs for the Researcher by Daryl S Paulson
  • Bayes and Empirical Bayes Methods for Data Analysis, Second Edition by Bradley P Carlin Thomas A Louis
  • Clinical Trials in Oncology, Second Edition by Stephanie Green Jacqueline Benedetti John Crowley
  • Contemporary Statistical Models for the Plant and Soil Sciences by Oliver Schabenberger Francis J Pierce
  • Contingency Table Approach to Nonparametric Testing by A J.C.W. Rayner D.J. Best
  • CRC Standard Probability and Statistics Tables and Formulae by Daniel Zwillinger Stephen Kokoska
  • Data Mining Using SAS Applications by George Fernandez
  • Design and Analysis of Cross-Over Trials, Second Edition by Byron Jones M.G. Kenward
  • EM Algorithm and Related Statistical Models, by The Michiko Watanabe Kazunori Yamaguchi
  • Environmental Statistics with S-PLUS by Steven P. Millard Nagaraj K. Neerchal
  • Generalized Latent Variable Modeling: Multilevel, Longitudinal, and Structural Equation Models by Anders Skrondal Sophia Rabe-Hesketh (2 copies)
  • Group Sequential Methods with Applications to Clinical Trials by Christopher Jennison Bruce W. Turnbull
  • Handbook of Parametric and Nonparametric Statistical Procedures, Second Edition by David J Sheskin
  • Handbook of Statistical Analyses Using SAS, Second Edition by Geoff Der Brian S. Everitt
  • Handbook of Statistical Analyses Using SPSS, A Sabine Landau Brian S Everitt
  • Handbook of Statistical Analyses using S-Plus, Second Edition by Brian S. Everitt
  • Handbook of Statistical Analyses Using Stata, Second Edition by Sophia Rabe-Hesketh Brian S. Everitt
  • Hierarchical Modeling and Analysis for Spatial Data by Sudipto Banerjee Bradley P Carlin Alan E Gelfand
  • Introduction to Generalized Linear Models, Second Edition by Annette J. Dobson
  • Measures of Interobserver Agreement by Mohamed M. Shoukri
  • Multidimensional Scaling, Second Edition Trevor F. Cox M.A.A. Cox
  • Sample Size Calculations in Clinical Research by Shein-Chung Chow Jun Shao Hansheng Wang
  • Sampling Methodologies with Applications by Poduri S.R.S. Rao
  • Statistical and Econometric Methods for Transportation Data Analysis by Simon P Washington Matthew G Karlaftis Fred L Mannering
  • Statistics in Drug Research: Methodologies and Recent Developments by SHEIN-CHUNG CHOW JUN SHAO
  • Statistical Methods for Health Sciences, Second Edition by Mohamed M. Shoukri Cheryl A. Pause
  • Statistics in the 21st Century by Adrian E. Raftery Martin A. Tanner Martin T. Wells
  • Theory of the Design of Experiments, The by Sir David R. Cox Nancy Reid
  • Time-Series Forecasting by Chris Chatfield
  • Topics in Modeling of Clustered Data by Marc Aerts Geert Molenberghs Helena Geys Louise Ryan

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Analisa Data : Analisis Data Uji Parametrik & Uji Non Parametrik

Ilmu statistika secara garis besar dibagi menjadi 2 :

1. Statistika parametrik

Ilmu statistika yang mempertimbangkan jenis sebaran/distribusi data, yaitu apakah data menyebar normal atau tidak. Pada umumnya, Jika data tidak menyebar normal, maka data harus dikerjakan dengan metode Statistika non-parametrik, atau setidak2nya dilakukan transformasi agar data mengikuti sebaran normal, sehingga bisa dikerjakan dg statistika parametrik. Contoh metode statistika parametrik: uji-z (1 atau 2 sampel), uji-t (1 atau 2 sampel), korelasi pearson, Perancangan Percobaan (1 or 2-way ANOVA parametrik), dll.

2. Statistika non parametrik

Menurut literatur, statistika non-parametrik adalah statistika bebas sebaran (tidak mensyaratkan bentuk sebaran parameter populasi, baik normal atau tidak). Statistika non-parametrik biasanya digunakan untuk melakukan analisis pada data berjenis Nominal atau Ordinal. Data berjenis Nominal dan Ordinal tidak menyebar normal. Contoh metode Statistika non parametrik: Binomial test, Chi-square test, Median test, Friedman Test, dll.

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