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  1. 221
    Robust Integration of Model-Based Fault Estimation and Fault-Tolerant Control /

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  2. 222
    Sampling Designs Dependent on Sample Parameters of Auxiliary Variables /
    by Wywiał, Janusz L
    Published 2021

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  3. 223
    Robust Multivariate Analysis /
    by J. Olive, David, J. Olive, David
    Published 2017

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  4. 224
    Robust and Multivariate Statistical Methods : Festschrift in Honor of David E. Tyler /
    Published 2023

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  5. 225
    Sampling Theory and Practice /

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  6. 226
    Text Analysis with R : For Students of Literature /

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  7. 227
    Quantitative Portfolio Management : with Applications in Python /

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  8. 228
    Time Series Analysis Using SAS Enterprise Guide /

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  9. 229
    Reliability and Statistics in Transportation and Communication : Selected Papers from the 19th International Conference on Reliability and Statistics in Transportation and Communication, RelStat'19, 16-19 October 2019, Riga, Latvia /
    Published 2020

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  10. 230
    Random Forests with R /

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  11. 231
    Six Sigma Green Belt Certification Project : Identification, Implementation and Evaluation /

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  12. 232
    Excel 2019 for Marketing Statistics : A Guide to Solving Practical Problems /

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  13. 233
    Excel 2019 for Physical Sciences Statistics : A Guide to Solving Practical Problems /

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  14. 234
    Excel 2019 in Applied Statistics for High School Students : A Guide to Solving Practical Problems /
    by Quirk, Thomas J, Quirk, Thomas J
    Published 2021

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  15. 235
    Leadership in Statistics and Data Science : Planning for Inclusive Excellence /
    Published 2021

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  16. 236
    Innovative Learning Environments in STEM Higher Education : Opportunities, Challenges, and Looking Forward /
    Published 2021

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  17. 237
    Measuring and Understanding Complex Phenomena : Indicators and their Analysis in Different Scientific Fields /
    Published 2021

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  18. 238
    2019-20 MATRIX Annals /
    Published 2021

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  19. 239
    Counting Statistics for Dependent Random Events : With a Focus on Finance /

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  20. 240
    A Course on Small Area Estimation and Mixed Models : Methods, Theory and Applications in R /

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