Basic Statistics in Business and Economics ISE
Autor Douglas Lind, William Marchal, Samuel Wathenen Limba Engleză Paperback – 17 mar 2021
Students are given every step needed to be successful in a basic statistics course. This step-by-step approach enhances performance, accelerates preparedness, and significantly improves motivation. Understanding the concepts, seeing and doing plenty of examples and exercises, and comprehending the application of statistical methods in business and economics are the focus of this book.
Today, the practice of data analytics is widely applied to big data. The practice of data analytics requires skills and knowledge in several areas. Computer skills are needed to process large volumes of information. Analytical skills are needed to evaluate, summarize, organize, and analyze the information. Critical thinking skills are needed to interpret and communicate the results of processing the information. This text supports the development of basic data analytical skills with the end of each chapter sections called Data Analytics providing the instructor and student with opportunities to apply statistical knowledge and statistical software to explore several business environments. Interpretation of the analytical results is an integral part of these exercises.
A variety of statistical software is available to complement the 10th edition. Microsoft Excel includes an add-in with many statistical analyses. MegaStat is an add-in available for Microsoft Excel. Minitab and JMP are stand-alone statistical software packages available to download for either PC or Mac. In the text, Microsoft Excel, Minitab, and MegaStat are used to illustrate statistical software analyses. The text also includes references or links to Excel tutorials in Connect. These provide users with clear demonstrations using statistical software to create graphical and descriptive statistics and statistical analyses to test hypotheses.
Digital resources within McGraw Hill Connect® help students apply what they've learned and achieve higher outcomes in the course. Connect is the only integrated learning system that empowers students by continuously adapting to deliver precisely what they need when they need it and how they need it so that class time is more engaging and effective.
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Specificații
ISBN-13: 9781260597578
ISBN-10: 1260597571
Pagini: 640
Dimensiuni: 267 x 203 x 28 mm
Greutate: 1.03 kg
Ediția:10
Editura: McGraw Hill Education
Colecția McGraw-Hill
Locul publicării:United States
ISBN-10: 1260597571
Pagini: 640
Dimensiuni: 267 x 203 x 28 mm
Greutate: 1.03 kg
Ediția:10
Editura: McGraw Hill Education
Colecția McGraw-Hill
Locul publicării:United States
Cuprins
Chapter 1: What is Statistics?
Chapter 2: Describing Data: Frequency Tables, FrequencyDistributions, and Graphic Presentation
Chapter 3: Describing Data: Numerical Measures
Chapter 4: Describing Data: Displaying and Exploring Data
Chapter 5: A Survey of Probability Concepts
Chapter 6: Discrete Probability Distributions
Chapter 7: Continuous Probability Distributions
Chapter 8: Sampling, Sampling Methods, and the Central LimitTheorem
Chapter 9: Estimation and Confidence Intervals
Chapter 10: One-Sample Tests of Hypothesis
Chapter 11: Two-Sample Tests of Hypothesis
Chapter 12: Analysis of Variance
Chapter 13: Correlation and Linear Regression
Chapter 14: Multiple Regression Analysis
Chapter 15: Nonparametric Methods: Nominal-Level HypothesisTests
Appendixes: Data Sets, Tables, Answers
Chapter 2: Describing Data: Frequency Tables, FrequencyDistributions, and Graphic Presentation
Chapter 3: Describing Data: Numerical Measures
Chapter 4: Describing Data: Displaying and Exploring Data
Chapter 5: A Survey of Probability Concepts
Chapter 6: Discrete Probability Distributions
Chapter 7: Continuous Probability Distributions
Chapter 8: Sampling, Sampling Methods, and the Central LimitTheorem
Chapter 9: Estimation and Confidence Intervals
Chapter 10: One-Sample Tests of Hypothesis
Chapter 11: Two-Sample Tests of Hypothesis
Chapter 12: Analysis of Variance
Chapter 13: Correlation and Linear Regression
Chapter 14: Multiple Regression Analysis
Chapter 15: Nonparametric Methods: Nominal-Level HypothesisTests
Appendixes: Data Sets, Tables, Answers