Spreadsheet skills are important for a first job, and DATA ANALYSIS USING MICROSOFT EXCEL prepares students to enter the world of work with stronger spreadsheet skills. Designed as a supplement to a main statistics text or as a reference for professionals, this handbook helps students build their proficiency in Microsoft Excel and shows them how to use the built-in capabilities of Excel to analyze data and make decisions. Although many of the examples are business oriented, the step-by-step approach makes this book appropriate for statistical analysis in other courses and academic disciplines.
Rezensionen / Stimmen
1. Introduction to Excel. 2. Managing Files and Printing. 3. Basic Charts. 4. Univariate Numerical Data. 5. Categorical Data. 6. Bivariate Numerical Data. 7. Probability Distributions. 8. Sampling and Simulation. 9. One-Sample Inference for the Mean. 10. Quality Control Charts. 11. Two-Sample Inference for the Mean. 12. Chi-Square Tests. 13. Analysis of Variance. 14. Simple Linear Regression. 15. Simple Nonlinear Regression. 16. Multiple Regression. 17. Regression using Categorical Data. 18. Autocorrelation and Autoregression. 19. Time Series Smoothing. 20. Time Series Seasonality. Appendix. References. Index.
Auflage
Sprache
Verlagsort
Verlagsgruppe
Zielgruppe
Für höhere Schule und Studium
Für Beruf und Forschung
Editions-Typ
Illustrationen
ISBN-13
978-0-534-40293-8 (9780534402938)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Klassifikation
Michael R. Middleton is a Professor of Decision Sciences at the School of Business and Management, University of San Francisco, where he has taught since 1977. He is a member of the Decision Sciences Institute, the Institute for Operations Research and the Management Sciences, and the American Statistical Association. He has published three books with Duxbury, delivered a variety of seminars and workshops in decision science, and authored two decision science software programs.
1. Introduction to Excel. 2. Managing Files and Printing. 3. Basic Charts. 4. Univariate Numerical Data. 5. Categorical Data. 6. Bivariate Numerical Data. 7. Probability Distributions. 8. Sampling and Simulation. 9. One-Sample Inference for the Mean. 10. Quality Control Charts. 11. Two-Sample Inference for the Mean. 12. Chi-Square Tests. 13. Analysis of Variance. 14. Simple Linear Regression. 15. Simple Nonlinear Regression. 16. Multiple Regression. 17. Regression using Categorical Data. 18. Autocorrelation and Autoregression. 19. Time Series Smoothing. 20. Time Series Seasonality. Appendix. References. Index.
