Statistics The Art and Science of Learning from Data

Kombinasjonsprodukt / 2011 / Engelsk

Produktdetaljer

ISBN13
9780321755940
Publisert
2011
Utgave
3. utgave
Utgiver
Vendor
Pearson
Aldersnivå
05, U
Språk
Product language
Engelsk
Format
Product format
Kombinasjonsprodukt
Sider
832
Vekt
1850 gr
Høyde
283 mm
Bredde
220 mm
Tykkelse
32 mm
Se alle

Statistics The Art and Science of Learning from Data

Kombinasjonsprodukt / 2011 / Engelsk
Alan Agresti and Chris Franklin have merged their research and classroom experience to develop this successful introductory statistics text. Statistics: The Art and Science of Learning from Data, Third Edition, helps students become statistically literate by encouraging them to ask and answer interesting statistical questions. It takes the ideas that have turned statistics into a central science in modern life and makes them accessible and engaging to students without compromising necessary rigor. The Third Edition has been edited for conciseness and clarity to keep students focused on the main concepts. The data-rich examples that feature intriguing human-interest topics now include topic labels to indicate which statistical topic is being applied. New learning objectives for each chapter appear in the Instructor's Edition, making it easier to plan lectures and Chapter 7 (Sampling Distributions) now incorporates simulations in addition to the mathematical formulas.
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Part 1: Gathering and Exploring Data 1. Statistics: The Art and Science of Learning from Data1.1 Using Data to Answer Statistical Questions1.2 Sample Versus Population1.3 Using Calculators and ComputersChapter SummaryChapter Problems 2. Exploring Data with Graphs and Numerical Summaries2.1 Different Types of Data2.2 Graphical Summaries of Data2.3 Measuring the Center of Quantitative Data2.4 Measuring the Variability of Quantitative Data2.5 Using Measures of Position to Describe Variability2.6 Recognizing and Avoiding Misuses of Graphical SummariesChapter SummaryChapter Problems 3. Association: Contingency, Correlation, and Regression3.1 The Association Between Two Categorical Variables3.2 The Association Between Two Quantitative Variables3.3 Predicting the Outcome of a Variable3.4 Cautions in Analyzing AssociationsChapter SummaryChapter Problems 4. Gathering Data4.1 Experimental and Observational Studies4.2 Good and Poor Ways to Sample4.3 Good and Poor Ways to Experiment4.4 Other Ways to Conduct Experimental and Nonexperimental StudiesChapter SummaryChapter Problems Part 1 ReviewPart 1 QuestionsPart 1 Exercises Part 2: Probability, Probability Distributions, and Sampling Distributions 5. Probability in Our Daily Lives5.1 How Probability Quantifies Randomness5.2 Finding Probabilities5.3 Conditional Probability: The Probability of A Given B5.4 Applying the Probability RulesChapter SummaryChapter Problems 6. Probability Distributions6.1 Summarizing Possible Outcomes and Their Probabilities6.2 Probabilities for Bell-Shaped Distributions6.3 Probabilities When Each Observation Has Two Possible OutcomesChapter SummaryChapter Problems 7. Sampling Distributions7.1 How Sample Proportions Vary Around the Population Proportion7.2 How Sample Means Vary Around the Population Mean7.3 The Binomial Distribution Is a Sampling Distribution (Optional)Chapter SummaryChapter Problems Part 2 ReviewPart 2 QuestionsPart 2 Exercises Part 3: Inferential Statistics 8. Statistical Inference: Confidence Intervals8.1 Point and Interval Estimates of Population Parameters8.2 Constructing a Confidence Interval to Estimate a Population Proportion8.3 Constructing a Confidence Interval to Estimate a Population Mean8.4 Choosing the Sample Size for a Study8.5 Using Computers to Make New Estimation Methods PossibleChapter SummaryChapter Problems 9. Statistical Inference: Significance Tests about Hypotheses9.1 Steps for Performing a Significance Test9.2 Significance Tests about Proportions9.3 Significance Tests about Means9.4 Decisions and Types of Errors in Significance Tests9.5 Limitations of Significance Tests9.6 The Likelihood of a Type II Error (Not Rejecting H0, Even Though It's False)Chapter SummaryChapter Problems 10. Comparing Two Groups10.1 Categorical Response: Comparing Two Proportions10.2 Quantitative Response: Comparing Two Means10.3 Other Ways of Comparing Means and Comparing Proportions10.4 Analyzing Dependent Samples10.5 Adjusting for the Effects of Other VariablesChapter SummaryChapter Problems Part 3 ReviewPart 3 Questions Part 3 Exercises Part 4: Analyzing Association and Extended Statistical Methods 11. Analyzing the Association Between Categorical Variables11.1 Independence and Association11.2 Testing Categorical Variables for Independence11.3 Determining the Strength of the Association11.4 Using Residuals to Reveal the Pattern of Association11.5 Small Sample Sizes: Fisher's Exact TestChapter SummaryChapter Problems 12. Analyzing the Association Between Quantitative Variables: Regression Analysis12.1 Model How Two Variables Are Related12.2 Describe Strength of Association12.3 Make Inference About the Association12.4How the Data Vary Around the Regression Line12.5 Exponential Regression: A Model for NonlinearityChapter SummaryChapter Problems 13. Multiple Regression13.1 Using Several Variables to Predict a Response13.2 Extending the Correlation and R-squared for Multiple Regression13.3 Using Multiple Regression to Make Inferences13.4 Checking a Regression Model Using Residual Plots13.5 Regression and Categorical Predictors13.6 Modeling a Categorical ResponseChapter SummaryChapter Problems 14. Comparing Groups: Analysis of Variance Methods14.1 One-Way ANOVA: Comparing Several Means14.2 Estimating Differences in Groups for a Single Factor 14.3 Two-Way ANOVAChapter SummaryChapter Problems 15. Nonparametric Statistics15.1 Compare Two Groups by Ranking15.2 Nonparametric Methods For Several Groups and for Matched PairsChapter SummaryChapter Problems PART 4 ReviewPart 4 Questions Part 4 Exercises TablesAnswersIndexIndex of ApplicationsPhoto Credits
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Alan Agresti is Distinguished Professor Emeritus in the Department of Statistics at the University of Florida. He taught statistics there for 38 years, including the development of three courses in statistical methods for social science students and three courses in categorical data analysis. He is author of over 100 refereed articles and five texts including "Statistical Methods for the Social Sciences" (with Barbara Finlay, Prentice Hall, 4th edition 2009) and "Categorical Data Analysis" (Wiley, 2nd edition 2002). He is a Fellow of the American Statistical Association and recipient of an Honorary Doctor of Science from De Montfort University in the UK. In 2003 Alan was named "Statistician of the Year" by the Chicago chapter of the American Statistical Association and in 2004 he was the first honoree of the Herman Callaert Leadership Award in Biostatistical Education and Dissemination awarded by the University of Limburgs, Belgium. He has held visiting positions at Harvard University, Boston University, London School of Economics, and Imperial College and has taught courses or short courses for universities and companies in about 30 countries worldwide. Alan has also received teaching awards from UF and an excellence in writing award from John Wiley & Sons. Christine Franklin is a Senior Lecturer and Lothar Tresp Honoratus Honors Professor in the Department of Statistics at the University of Georgia. She has been teaching statistics for more than 30 years at the college level. Chris has been actively involved at the national and state level with promoting statistical education at Pre-K-16 since the 1980s. She is a past Chief Reader for AP Statistic. She has developed three graduate level courses at the University of Georgia in statistics for elementary, middle, and secondary teachers. Chris served as the lead writer for the ASA-endorsed Guidelines for Assessment and Instruction in Statistics Education (GAISE) Report: A Pre- K-12 Curriculum Framework. Chris has been honored by her selection as a Fellow of the American Statistical Association, the 2006 Mu Sigma Rho National Statistical Education Award recipient for her teaching and lifetime devotion to statistics education, and numerous teaching and advising awards at the University of Georgia including election to the UGA Teaching Academy. Chris has written more than 50 journal articles and resource materials for textbooks.
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1.442,-
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Produktdetaljer

ISBN13
9780321755940
Publisert
2011
Utgave
3. utgave
Utgiver
Vendor
Pearson
Aldersnivå
05, U
Språk
Product language
Engelsk
Format
Product format
Kombinasjonsprodukt
Sider
832
Vekt
1850 gr
Høyde
283 mm
Bredde
220 mm
Tykkelse
32 mm
Se alle