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008 190725s2019 gw o 000 0 eng d
020 _a9783030175542
040 _aLQU
_beng
_cLQU
_dUPM
_dOCLCO
_dYDX
_dGW5XE
_dOCLCF
_dAEU
050 4 _aTS155-TS194
082 0 4 _a658.5
100 1 _aCanela, Miguel Ángel.
245 1 0 _aQuantitative methods for management
_b: a practical approach /
_cby Miguel Ángel Canela, Inés Alegre, Alberto Ibarra.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing,
_c2019 ; :
_bImprint Springer.
300 _aXIII, 144 p. 42 illus.
505 _aSummary Statistics — Probability Distributions — Regression Analysis — The Regression Line — Multiple Regression — Testing Regression Coefficients — Dummy Variables — Interaction — Classification — Classification Models — Out-of-Sample Validation — Time Series Data — Trend and Seasonality — Nonlinear Trends — Moving Average Trends — Holt-Winters Forecasting.
520 _aThis book focuses on the use of quantitative methods for both business and management, helping readers understand the most relevant quantitative methods for managerial decision-making. Pursuing a highly practical approach, the book reduces the theoretical information to a minimum, so as to give full prominence to the analysis of real business problems. Each chapter includes a brief theoretical explanation, followed by a real-life managerial case that needs to be solved, which is accompanied by a corresponding Microsoft Excel® dataset. The practical cases and exercises are solved using Excel, and for each problem, the authors provide an Excel file with the complete solution and corresponding calculations, which can be downloaded easily from the books website. Further, in an appendix, readers can find solutions to the same problems, but using the R statistical language. The book represents a valuable reference guide for postgraduate, MBA and executive education students, as it offers a hands-on, practical approach to learning quantitative methods in a managerial context. It will also be of interest to managers looking for a practical and straightforward way to learn about quantitative methods and improve their decision-making processes.
650 0 _aProduction management.
650 0 _aEngineering economy.
650 0 _aStatistics.
650 7 _aCommercial statistics.
_2fast
_0(OCoLC)fst00869640
650 7 _aDecision making
_xStatistical methods.
_2fast
_0(OCoLC)fst00889068
650 7 _aManagement
_xStatistical methods.
_2fast
_0(OCoLC)fst01007232
700 1 _aAlegre, Inés.
700 1 _aIbarra, Alberto.
942 _2lcc
999 _c3596
_d3596
041 _aEnglish