Excel

Microsoft Excel is a powerful spreadsheet application that can be used to create, analyze, present, and share data. Excel 2003 includes a new set of integrated XML tools, enhanced list functionality, and improved statistical functions. You can create customized solutions with Excel that integrate a broad array of technologies, including XML, Microsoft SharePoint Products and Technologies, smart tags, and PivotTables


References in zbMATH (referenced in 645 articles , 4 standard articles )

Showing results 1 to 20 of 645.
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  1. Strub, O.; Trautmann, N.: A two-stage approach to the UCITS-constrained index-tracking problem (2019)
  2. Bergtold, Jason S.; Pokharel, Krishna P.; Featherstone, Allen M.; Mo, Lijia: On the examination of the reliability of statistical software for estimating regression models with discrete dependent variables (2018)
  3. Cho, Shinil: Fourier transform and its applications using Microsoft EXCEL (2018)
  4. Esensoy, Ali Vahit; Carter, Michael W.: High-fidelity whole-system patient flow modeling to assess health care transformation policies (2018)
  5. Ferrareso Lona, Liliane Maria: A step by step approach to the modeling of chemical engineering processes. Using Excel for simulation (2018)
  6. Khajavirad, Aida; Sahinidis, Nikolaos V.: A hybrid LP/NLP paradigm for global optimization relaxations (2018)
  7. Pagel, Christina; Ramnarayan, Padmanabhan; Ray, Samiran; Peters, Mark J.: Development and implementation of a real time statistical control method to identify the start and end of the winter surge in demand for paediatric intensive care (2018)
  8. Swarup Chauhan; Kathleen Sell; Frieder Enzmann; Wolfram Rühaak; Thorsten Wille; Ingo Sass; Michael Kersten: CobWeb - a toolbox for automatic tomographic image analysis based on machine learning techniques (2018) arXiv
  9. Vigerske, Stefan; Gleixner, Ambros: SCIP: global optimization of mixed-integer nonlinear programs in a branch-and-cut framework (2018)
  10. Zhao, Jingxin; Peng, Heng; Huang, Tao: Variance estimation for semiparametric regression models by local averaging (2018)
  11. Antoine Filipovic-Pierucci, Kevin Zarca, Isabelle Durand-Zaleski: Markov Models for Health Economic Evaluations: The R Package heemod (2017) arXiv
  12. Baio, Gianluca; Berardi, Andrea; Heath, Anna: Bayesian cost-effectiveness analysis with the R package BCEA (2017)
  13. Falke, Andreas; Hruschka, Harald: A Monte Carlo study of design-generating algorithms for the latent class mixed logit model (2017)
  14. İç, Yusuf Tansel; Özel, Melis; Kara, İmdat: An integrated fuzzy TOPSIS-knapsack problem model for order selection in a bakery (2017)
  15. Jauhari, Shaurya; Rizvi, S. A. M.: \itA priori, \itde novo mathematical exploration of gene expression mechanism via regression viewpoint with briefly cataloged modeling antiquity (2017)
  16. Koehler, Henning; Link, Sebastian: Inclusion dependencies and their interaction with functional dependencies in SQL (2017)
  17. Kolb, Samuel; Paramonov, Sergey; Guns, Tias; De Raedt, Luc: Learning constraints in spreadsheets and tabular data (2017)
  18. Lasdon, Leon; Shirzadi, Shawn; Ziegel, Eric: Implementing CRM models for improved oil recovery in large oil fields (2017)
  19. Li, Weiyu; Patilea, Valentin: A new minimum contrast approach for inference in single-index models (2017)
  20. Peltier, Corey: “What If” analysis: benefits of utilizing a “What If” analysis in excel (2017)

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