- Häftad (Paperback)
- Antal sidor
- Velleman, Paul / Bock, David E.
- 275 x 215 x 25 mm
- Antal komponenter
- 2050 g
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Richard De Veaux, Paul Velleman, and David Bock wrote Stats: Data and Models with the goal that students and instructors have as much fun reading it as they did writing it. Maintaining a conversational, humorous, and informal writing style, this new edition engages students from the first page. The authors focus on statistical thinking throughout the text and rely on technology for calculations. As a result, students can focus on developing their conceptual understanding. Innovative Think/Show/Tell examples give students a problem-solving framework and, more importantly, a way to think through any statistics problem and present their results. The Fourth Edition is updated with instructor podcasts, video lectures, and new examples to keep material fresh, current, and relevant to todays students.
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MyStatLab not included. Students, if MyStatLab is a recommended/mandatory component of the course, please ask your instructor for the correct ISBN and course ID. MyStatLab should only be purchased when required by an instructor. Instructors, contact your Pearson representative for more information.
MyStatLab is an online homework, tutorial, and assessment product designed to personalize learning and improve results. With a wide range of interactive, engaging, and assignable activities, students are encouraged to actively learn and retain tough course concepts.
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Fler böcker av Richard D De Veaux
Part I: Exploring and Understanding Data
1. Stats Starts Here
1.1 What Is Statistics?
2. Displaying and Describing Categorical Data
2.1 Summarizing and Displaying a Single Categorical variable
2.2 Exploring the Relationship Between Two Categorical variables
3. Displaying and Summarizing Quantitative Data
3.1 Displaying quantitative variables
3.5 Boxplots and 5-Number Summaries
3.6 The Center of Symmetric Distributions: The Mean
3.7 The Spread of Symmetric Distributions: The Standard Deviation
3.8 SummaryWhat to Tell About a quantitative variable
4. Understanding and Comparing Distributions
4.1 Comparing Groups with Histograms
4.2 Comparing Groups with Boxplots
4.4 Timeplots: Order, Please!
4.5 Re-Expressing Data: A First Look
5. The Standard Deviation as a Ruler and the Normal Model
5.1 Standardizing with z-Scores
5.2 Shifting and Scaling
5.3 Normal Models
5.4 Finding Normal Percentiles
5.5 Normal Probability Plots
Part II: Exploring Relationships Between Variables
6. Scatterplots, Association, and Correlation
6.3 Warning: Correlation Causation
6.4 Straightening Scatterplots
7. Linear Regression
7.1 Least Squares: The Line of Best Fit
7.2 The Linear Model
7.3 Finding the Least Squares Line
7.4 Regression to the Mean
7.5 Examining the Residuals
7.6 R2The variation Accounted For by the Model
7.7 Regression Assumptions and Conditions
8. Regression Wisdom
8.1 Examining Residuals
8.2 Extrapolation: Reaching Beyond the Data
8.3 Outliers, Leverage, and Influence
8.4 Lurking variables and Causation
8.5 Working with Summary values
9. Re-expressing Data: Get It Straight!
9.1 Straightening Scatterplots The Four Goals
9.2 Finding a Good Re-Expression
Part III: Gathering Data
10. Understanding Randomness
10.1 What Is Randomness?
10.2 Simulating by Hand
11. Sample Surveys
11.1 The Three Big Ideas of Sampling
11.2 Populations and Parameters
11.3 Simple Random Samples
11.4 Other Sampling Designs
11.5 From the Population to the Sample: You Cant Always Get What You Want
11.6 The valid Survey
11.7 Common Sampling Mistakes, or How to Sample Badly
12. Experiments and Observational Studies
12.1 Observational Studies
12.2 Randomized, Comparative Experiments
12.3 The Four Principles of Experimental Design
12.4 Control Treatments
Part IV: Randomness and Probability...