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 595 articles , 4 standard articles )

Showing results 1 to 20 of 595.
Sorted by year (citations)

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  1. Antoine Filipovic-Pierucci, Kevin Zarca, Isabelle Durand-Zaleski: Markov Models for Health Economic Evaluations: The R Package heemod (2017) arXiv
  2. 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)
  3. Peltier, Corey: “What If” analysis: benefits of utilizing a “What If” analysis in excel (2017)
  4. Rothwell, Alan: Optimization methods in structural design (2017)
  5. Barton, Jeffrey T.: Models for life. An introduction to discrete mathematical modeling with Microsoft Office Excel (2016)
  6. Barton, Jeffrey T.: Solutions manual to accompany `Models for life. An introduction to discrete mathematical modeling with Microsoft Office Excel’ (2016)
  7. Benacka, Jan: Calculating ellipse area by the Monte Carlo method and analysing dice poker with excel at high school (2016)
  8. Casper, Michael: Digital support. Incorporating digital tools into learning stations (2016) MathEduc
  9. Friedman, Daniel; Sinervo, Barry: Evolutionary games in natural, social, and virtual worlds (2016)
  10. Haslwanter, Thomas: An introduction to statistics with Python. With applications in the life sciences (2016)
  11. Hayward, Charles N.; Kogan, Marina; Laursen, Sandra L.: Facilitating instructor adoption of inquiry-based learning in college mathematics (2016) MathEduc
  12. Hong, Jungsik; Koo, Hoonyoung; Kim, Taegu: Easy, reliable method for mid-term demand forecasting based on the Bass model: a hybrid approach of NLS and OLS (2016)
  13. Huang, Dongmei; Sun, Le; Shi, Shaohua; Su, Cheng; Zhao, Danfeng: Tabular-oriented data model and its query issues (2016) ioport
  14. Kaliszewski, Ignacy; Miroforidis, Janusz; Podkopaev, Dmitry: Multiple criteria decision making by multiobjective optimization. A toolbox (2016)
  15. Kimbrough, Steven Orla; Lau, Hoong Chuin: Business analytics for decision making (2016)
  16. Le, Chap T.; Eberly, Lynn E.: Introductory biostatistics (2016)
  17. Mendenhall, William M.; Sincich, Terry L.: Statistics for engineering and the sciences (2016)
  18. Pfeifer, Phillip E.: The promise of pick-the-winners contests for producing crowd probability forecasts (2016)
  19. Singh, Rishabh; Gulwani, Sumit: Transforming spreadsheet data types using examples (2016)
  20. Syntetos, Aris A.; Babai, Zied; Boylan, John E.; Kolassa, Stephan; Nikolopoulos, Konstantinos: Supply chain forecasting: theory, practice, their gap and the future (2016)

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