Applied statistics in business and economics /
Edition statement:7th ed. Published by : McGraw Hill LLC, (New York, NY : ) Physical details: xxiv, 818 pages : col. illus. ; 28 cm. ISBN:9781260597646.| Item type | Current location | Collection | Call number | Status | Date due | Barcode | Course reserves |
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ASCOT Library - Zabali Campus Reference | Reference | Ref 519.5 D65a 2022 04608 (Browse shelf) | Available | Ref5195004608 |
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| Ref 428 R31r 2023 Research developments in world Englishes / | Ref 512 G97c 2023 04600 College algebra / | Ref 515 M26c 2023 Calculus: an introduction / | Ref 519.5 D65a 2022 04608 Applied statistics in business and economics / | Ref 519.5 N22s 2020 Statistics for engineers and scientists / | Ref 530 Si64e 2023 C1 Earth science and technology / | Ref 530 Si64e 2023 C2 Earth science and technology / |
Includes appendices and index.
Chapter 1: Overview of Statistics --
Chapter 2: Data Collection --
Chapter 3: Describing Data Visually --
Chapter 4: Descriptive Statistics --
Chapter 5: Probability --
Chapter 6: Discrete Probability Distributions --
Chapter 7: Continuous Probability Distributions --
Chapter 8: Sampling Distributions and Estimation --
Chapter 9: One-Sample Hypothesis Tests --
Chapter 10: Two-Sample Hypothesis Tests --
Chapter 11: Analysis of Variance --
Chapter 12: Simple Regression --
Chapter 13: Multiple Regression --
Chapter 14: Time-Series Analysis --
Chapter 15: Chi-Square Tests --
Chapter 16: Nonparametric Tests --
Chapter 17: Quality Management --
Chapter 18: Simulation 1.
"Applied Statistics in Business and Economics, 7th edition, provides real meaning to the use of statistics in the real world by using real business situations and real data while appealing to students who want to know the why rather than just the how. The text emphasizes thinking about data, choosing appropriate analytic tools, using computers effectively, and recognizing the limitations of statistics. It motivates student learning through applied current exercises and cases that provide real-world relevance and includes analytics in action, careers, and applications of big data, Artificial Intelligence, and machine learning (including ethical issues). The Doane and Seward authors work as a team, integrating the digital and eBook assets seamlessly. In recognition of a growing interest in analytics training beyond Excel, the textbook now provides an optional introduction to R with illustrations of topics in each chapter. Support for R is further enhanced with Learning Stats modules, tables of R functions, and R-compatible Excel data sets." -- Provided by publisher
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