Business Analytics ISE
Autor Sanjiv Jaggia, Alison Kelly, Kevin Lertwachara, Leida Chenen Limba Engleză Paperback – 8 mar 2022
Preț: 476.02 lei
Preț vechi: 517.42 lei
-8%
Puncte Express: 714
Preț estimativ în valută:
84.16€ • 99.83$ • 72.87£
84.16€ • 99.83$ • 72.87£
Carte disponibilă
Livrare economică 25 februarie-11 martie
Livrare express 10-14 februarie pentru 64.46 lei
Specificații
ISBN-13: 9781265087685
ISBN-10: 1265087687
Pagini: 1600
Dimensiuni: 216 x 274 x 36 mm
Greutate: 1.29 kg
Ediția:2
Editura: McGraw Hill Education
Colecția McGraw-Hill
Locul publicării:United States
ISBN-10: 1265087687
Pagini: 1600
Dimensiuni: 216 x 274 x 36 mm
Greutate: 1.29 kg
Ediția:2
Editura: McGraw Hill Education
Colecția McGraw-Hill
Locul publicării:United States
Cuprins
CHAPTER 1: Introduction to Business Analytics
CHAPTER 2: Data Management and Wrangling
CHAPTER 3: Summary Measures
CHAPTER 4: Data Visualization
CHAPTER 5: Probability and Probability Distributions
CHAPTER 6: Statistical Inference
CHAPTER 7: Regression Analysis
CHAPTER 8: Introduction to Data Mining
CHAPTER 9: More Topics in Regression Analysis
CHAPTER 10: Logistic Regression Models
CHAPTER 11: Supervised Data Mining: kNN and Naive Bayes
CHAPTER 12: Supervised Data Mining: Decision Trees
CHAPTER 13: Unsupervised Data Mining
CHAPTER 14: Forecasting with Time Series Data
CHAPTER 15: Spreadsheet Modelling
CHAPTER 16: Risk and Simulation
CHAPTER 17: Optimization: Linear Programming
CHAPTER 18: Optimization: Integer and Nonlinear Programming
APPENDIX A Big Data Sets: Variable Description and Data Dictionary
APPENDIX B Getting Started with Excel and Excel Add-Ins
APPENDIX C Getting Started with R
APPENDIX D Statistical Tables
APPENDIX E Answers to Selected Exercises
CHAPTER 2: Data Management and Wrangling
CHAPTER 3: Summary Measures
CHAPTER 4: Data Visualization
CHAPTER 5: Probability and Probability Distributions
CHAPTER 6: Statistical Inference
CHAPTER 7: Regression Analysis
CHAPTER 8: Introduction to Data Mining
CHAPTER 9: More Topics in Regression Analysis
CHAPTER 10: Logistic Regression Models
CHAPTER 11: Supervised Data Mining: kNN and Naive Bayes
CHAPTER 12: Supervised Data Mining: Decision Trees
CHAPTER 13: Unsupervised Data Mining
CHAPTER 14: Forecasting with Time Series Data
CHAPTER 15: Spreadsheet Modelling
CHAPTER 16: Risk and Simulation
CHAPTER 17: Optimization: Linear Programming
CHAPTER 18: Optimization: Integer and Nonlinear Programming
APPENDIX A Big Data Sets: Variable Description and Data Dictionary
APPENDIX B Getting Started with Excel and Excel Add-Ins
APPENDIX C Getting Started with R
APPENDIX D Statistical Tables
APPENDIX E Answers to Selected Exercises