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 746 articles , 4 standard articles )

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  1. Ceccon, Francesco; Siirola, John D.; Misener, Ruth: SUSPECT: MINLP special structure detector for Pyomo (2020)
  2. Dickson, David C. M.; Hardy, Mary R.; Waters, Howard R.: Actuarial mathematics for life contingent risks (2020)
  3. Fok, Alex; Chew, Hooi Pin: Mathematical models for dental materials research (2020)
  4. Gupta, Bhisham C.; Guttman, Irwin; Jayalath, Kalanka P.: Statistics and probability with applications for engineers and scientists using MINITAB, R and JMP (2020)
  5. Mokhov, Andrey; Mitchell, Neil; Peyton Jones, Simon: Build systems à la carte: theory and practice (2020)
  6. Prank, Rein: Analysing the “calculator effect” of different kinds of software for school arithmetic and algebra (2020)
  7. Quirk, Thomas J.: Excel 2019 for engineering statistics. A guide to solving practical problems (2020)
  8. Stefan Kloppenborg: cmstatr: An R Package for Statistical Analysis of Composite Material Data (2020) not zbMATH
  9. Ann-Kristin Kreutzmann; Sören Pannier; Natalia Rojas-Perilla; Timo Schmid; Matthias Templ; Nikos Tzavidis: The R Package emdi for Estimating and Mapping Regionally Disaggregated Indicators (2019) not zbMATH
  10. Cleff, Thomas: Applied statistics and multivariate data analysis for business and economics. A modern approach using SPSS, Stata, and Excel (2019)
  11. John, Boby; Kadadevaramath, Rajeshwar S.: Optimization of software development life cycle process to minimize the delivered defect density (2019)
  12. Junghenn, Hugo D.: An introduction to financial mathematics. Option valuation (2019)
  13. Nguyen, Hien; Yee, Yohan; McLachlan, Geoffrey; Lerch, Jason: False discovery rate control for grouped or discretely supported (p)-values with application to a neuroimaging study (2019)
  14. Nikolopoulos, Kostas I.; Thomakos, Dimitrios D.: Forecasting with the theta method. Theory and applications (2019)
  15. Radojčić, Dejan; Kalajdžić, Milan; Simić, Aleksandar: Power prediction modeling of conventional high-speed craft (2019)
  16. Sandoval-Hernandez, Mario A.; Vazquez-Leal, Hector; Filobello-Nino, Uriel; Hernandez-Martinez, Luis: New handy and accurate approximation for the Gaussian integrals with applications to science and engineering (2019)
  17. Strub, O.; Trautmann, N.: A two-stage approach to the UCITS-constrained index-tracking problem (2019)
  18. van den Driessche, P.; Yakubu, Abdul-Aziz: Disease extinction versus persistence in discrete-time epidemic models (2019)
  19. van den Driessche, P.; Yakubu, Abdul-Aziz: Demographic population cycles and (\mathcalR_0) in discrete-time epidemic models (2019)
  20. Vinay Yadav, Subhankar Karmakar, Pradip P. Kalbar, A.K. Dikshit: PyTOPS: A Python based tool for TOPSIS (2019) not zbMATH

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