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Statistics : the art and science of learning from data

Author: Alan Agresti; Christine A Franklin
Publisher: Upper Saddle River, N.J. : Pearson Prentice Hall, ©2009.
Edition/Format:   Print book : CD for computer : Program   Computer File : English : 2nd edView all editions and formats
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CD-ROM contains: 19 applets including, sample from a population, sampling distributions, random numbers, long run probability demonstrations, mean versus median applet, standard deviation applet, hypothesis tests for a proportion and for a mean.
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Genre/Form: Einführung
Textbooks
Material Type: Program, Internet resource
Document Type: Book, Computer File, Internet Resource
All Authors / Contributors: Alan Agresti; Christine A Franklin
ISBN: 0135131995 9780135131992 0135132401 9780135132401 9780136037354 0136037356 0131357468 9780131357464 0135132029 9780135132029
OCLC Number: 123485547
Notes: Includes indexes.
Description: xxviii, 769, [47] pages : illustrations (some color) ; 29 cm + 1 CD-ROM (4 3/4 in.) + 1 workbook (166 pages : illustrations ; 28 cm)
Contents: PART 1: GATHERING and EXPLORING DATA 1. Statistics: The Art and Science of Learning from Data1.1 How Can You Investigate Using Data?1.2 We Learn about Population Using Samples1.3 What Role do Computers Play in Statistics? Chapter Summary Chapter Exercises 2. Exploring Data with Graphs and Numerical Summaries2.1 What Are the Types of Data?2.2 How Can We Describe Data using Graphical Summaries?2.3 How Can We Describe the Center of Quantitative Data?2.4 How Can We Describe the Spread of Quantitative Data?2.5 How Can Measures of Position Describe Spread?2.6 How Can Graphical Summaries Be Misused? Answers to Chapter Figure Questions Chapter Summary Chapter Exercises 3. Association: Contingency, Correlation, and Regression3.1 How Can We Explore the Association between Two Categorical Variables?3.2 How Can We Explore the Association between Two Quantitative Variables?3.3 How Can We Predict the Outcome of a Variable?3.4 What are Some Cautions in Analyzing Associations? Answers to Chapter Figure Questions Chapter Summary Chapter Exercises 4. Gathering Data4.1 Should We Experiment or Should We Merely Observe?4.2 What Are Good Ways and Poor Ways to Sample?4.3 What Are Good Ways and Poor Ways to Experiment?4.4 What Are Other Ways to Perform Experimental and Nonexperimental Studies? Answers to Chapter Figure Questions Chapter Summary Chapter Exercises PART 1 REVIEW Part 1 Summary Part 1 Exercises PART 2: PROBABILITY AND PROBABILITY DISTRIBUTIONS 5. Probability in our Daily Lives5.1 How Can Probability Quantify Randomness?5.2 How Can We Find Probabilities?5.3 Conditional Probability: What's the Probability of A, Given B?5.4 Applying the Probability Rules Answers to Chapter Figure Questions Chapter Summary Chapter Exercises 6. Probability Distributions6.1 How Can We Summarize Possible Outcomes and Their Probabilities?6.2 How Can We Find Probabilities for Bell-Shaped Distributions?6.3 How Can We Find Probabilities when Each Observation has Two Possible Outcomes? Answers to Chapter Figure Questions Chapter Summary Chapter Exercises 7. Sampling Distributions7.1 How Likely Are the Possible Values of a Statistics? The Sampling Distribution7.2 How Close Are Sample Means to Population Means?7.3 How Can We Make Inferences about a Population? Answers to Chapter Figure Questions Chapter Summary Chapter Exercises PART 2 REVIEW Part 2 Summary Part 2 Exercises PART 3: INFERENCE STATISTICS 8. Statistical Inference: Confidence Intervals8.1 What Are Point and Interval Estimates of Population Parameters?8.2 How Can We Construct a Confidence Interval to Estimate a Population Proportion?8.3 How Can We Construct a Confidence Interval to Estimate a Population Mean?8.4 How Do We Choose the Sample Size for a Study?8.5 How Do Computers Make New Estimation Methods Possible? Answers to Chapter Figure Questions Chapter Summary Chapter Exercises 9. Statistical Inference: Significance Tests about Hypotheses9.1 What Are the Steps for Performing a Significance Test?9.2 Significance Tests about Proportions9.3 Significance Tests about Means9.4 Decisions and Types of Errors in Significance Tests9.5 Limitations of Significance Tests9.6 How Likely is a Type II Error (Not Rejecting H0, Even though it's False)? Answers to Chapter Figure Questions Chapter Summary Chapter Exercises 10. Comparing Two Groups10.1 Categorical Response: How Can We Compare Two Proportions?10.2 Quantitative Response: How Can We Compare Two Means?10.3 Other Ways of Comparing Means and Comparing Proportions10.4 How Can We Analyze Dependent Samples?10.5 How Can We Adjust for Effects of Other Variables? Answers to Chapter Figure Questions Chapter Summary Chapter Exercises PART 3 REVIEW Part 3 Summary Part 3 Exercises PART 4: ANALYZING ASSOCIATIONS AND EXTENDED STATISTICAL METHODS 11. Analyzing the Association Between Categorical Variables11.1 What is Independence and What is Association?11.2 How Can We Test Whether Categorical Variables are Independent?11.3 How Strong is the Association?11.4 How Can Residuals Reveal the Pattern of Association?11.5 What if the Sample Size is Small? Fisher's Exact Test Answers to Chapter Figure Questions Chapter Summary Chapter Exercises 12. Analyzing the Association Between Quantitative Variables: Regression Analysis12.1 How Can We "Model" How Two Variables Are Related?12.2 How Can We Describe Strength of Association?12.3 How Can We Make Inferences about the Association?12.4 What Do We Learn from How the Data Vary around the Regression Line?12.5 Exponential Regression: A Model for Nonlinearity Answers to Chapter Figure Questions Chapter Summary Chapter Exercises 13. Multiple Regression13.1 How Can We Use Several Variables to Predict a Response?13.2 Extending the Correlation and R-squared for Multiple Regression13.3 How Can We Use Multiple Regression to Make Inferences?13.4 Checking a Regression Model Using Residual Plots13.5 How Can Regression Include Categorical Predictors?13.6 How Can We Model a Categorical Response? Answers to Chapter Figure Questions Chapter Summary Chapter Exercises 14. Comparing Groups: Analysis of Variance Methods14.1 How Can We Compare Several Means?: One-Way ANOVA14.2 How Should We Follow Up an ANOVA F Test14.3 What if there are Two Factors?: Two-way ANOVA Answers to Chapter Figure Questions Chapter Summary Chapter Exercises 15. Nonparametric Statistics15.1 How Can We Compare Two Groups by Ranking?15.2 Nonparametric Methods for Several Groups and for Matched Pairs Answers to Chapter Figure Questions Chapter Summary Chapter Exercises PART 4 REVIEW Part 4 Summary Part 4 Exercises TablesSelected AnswersIndexIndex of Applications Photo Credits
Responsibility: Alan Agresti, Christine Franklin.
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Abstract:

Written as a study tool, the Lab Workbook is keyed directly to the text to provide section by section review and practice for the first ten chapters of Agresti/Franklin 2/e. Print outs of the  Read more...

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REVIEWER and CLASS TEST COMMENTS: "This was one of the most enjoyable texts that I have come across. I learned a lot from this book and it has made statistics a lot more fun to teach." - Nazanin Read more...

 
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