TY  - BOOK
AU  - Bowerman,Bruce L.
AU  - Drougas,Anne M.
AU  - Duckworth,William M.
AU  - Froelich,Amy G.
AU  - Hummel,Ruth M.
AU  - Moninger,Kyle B.
AU  - Schur,Patrick J.
TI  - Business statistics and analytics in practice
T2  - Operations and Decision Sciences
SN  - 9781260187496
U1  - 519.5 23
PY  - 2019///
CY  - Nueva York : 
PB  - McGraw Hill Education
KW  - Estadística matemática
KW  - Distribución (teoría de la probabilidad)
KW  - Probabilidades
KW  - Modelos matemáticos
KW  - Análisis de varianza
KW  - Análisis de regresión
KW  - Prueba de hipótesis estadística
KW  - Estadística no paramétrica
N1  - Incluye respuestas a los problemas propuestos en cada capítulo; Incluye referencias (896-898); Incluye índice de términos (899-906); Chapter 1. An introduction to business statistics and analytics ; Chapter 2. Descriptive statistics and analytics: tabular and graphical methods ; Chapter 3. Descriptive statistics and analytics: numerical methods ; Chapter 4. Probability and probability models ; Chapter 5. Predictive analytics I: trees, k-Nearest Neighbors, Naive Bayes', and ensemble estimates ; Chapter 6. Discrete random variables ; Chapter 7. Continouns random variables ; Chapter 8. Sampling distributions ; Chapter 9. Confidence intervals ; Chapter 10. Hypothesis testing ; Chapter 11. Statistical inferences based on two samples ; Chapter 12. Experimental design and analysis of variance ; Chapter 13. Chi-square test ; Chapter 14. Simple linear regression analysis ; Chapter 15. Multiple regression and model building ; Chapter 16. Predictive analytics II: logistic regresssion, dicriminate analysis, and neural networks ; Chapter 17. Time series forecasting and index numbers ; Chapter 18. Nonparametric methods ; Chapter 19. Decision theory ; Chapter 20. (Online) Process improvement using control charts for website
N2  - Business Statistics and Analytics in Practice, provides a unique and flexible framework for teaching the introductory course in business statistics. This framework consists of a complete presentation of traditional business statistics, with improved discussions of introductory concepts, probability modeling, classical statistical inference, and regression and time series modeling. A complete presentation of business analytics, with topic coverage in six optional sections and two optional chapters. Continuing case studies that facilitate student learning by presenting new concepts in the context of familiar situations and many new exercises and use of excel
ER  -