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Viser: Statistics: the Art and Science of Learning from Data, Global Edition
Statistics: the Art and Science of Learning from Data, Global Edition
Alan Agresti, Christine Franklin og Bernhard Klingenberg
(2017)
Sprog: Engelsk
Detaljer om varen
- 4. Udgave
- Paperback: 816 sider
- Udgiver: Pearson Education, Limited (April 2017)
- Forfattere: Alan Agresti, Christine Franklin og Bernhard Klingenberg
- ISBN: 9781292164779
For courses in introductory statistics.
Statistics: The Art and Science of Learning from Data takes a conceptual approach, helping students understand what statistics is about and learning the right questions to ask when analysing data, rather than just memorising procedures. This book takes the ideas that have turned statistics into a central science in modern life and makes them accessible, without compromising the necessary rigor. Students will enjoy reading this book, and will stay engaged with its wide variety of real-world data in the examples and exercises.
The authors believe that it's important for students to learn and analyse both quantitative and categorical data. As a result, the text pays greater attention to the analysis of proportions than many other introductory statistics texts. Concepts are introduced first with categorical data, and then with quantitative data.
PART ONE: GATHERING AND EXPLORING DATA
1. Statistics: The Art and Science of Learning from Data
2. Exploring Data with Graphs and Numerical Summaries
3. Association: Contingency, Correlation, and Regression
4. Gathering Data
PART TWO: PROBABILITY, PROBABILITY DISTRIBUTIONS, AND SAMPLING DISTRIBUTIONS
5. Probability in Our Daily Lives
6. Probability Distributions
7. Sampling Distributions
PART THREE: INFERENTIAL STATISTICS
8. Statistical Inference: Confidence Intervals
9. Statistical Inference: Significance Tests About Hypotheses
10. Comparing Two Groups
PART FOUR: ANALYZING ASSOCIATION AND EXTENDED STATISTICAL METHODS
11. Analyzing the Association Between Categorical Variables
12. Analyzing the Association Between Quantitative Variables: Regression Analysis
13. Multiple Regression
14. Comparing Groups: Analysis of Variance Methods
15. Nonparametric Statistics Tables Answers Index Index of Applications Photo Credits
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