Statistics

ISBN-10: 0321891953
ISBN-13: 9780321891952
Edition: 3rd 2013
List price: $210.00 Buy it from $10.00
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Description: 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  More...

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Book details

List price: $210.00
Edition: 3rd
Copyright year: 2013
Publisher: Addison Wesley
Publication date: 8/9/2012
Binding: Mixed Media
Size: 9.00" wide x 11.25" long x 1.50" tall
Weight: 4.356
Language: English

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. TheThird Editionhas 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.   

Alan Agrestiis Distinguished Professor in the Department of Statistics at the University of Florida. He has been teaching statistics there for 30 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 article and four texts including "Statistics: The Art and Science of Learning From Data" (withnbsp;Christine Franklin,nbsp;Prentice Hall, 2nd 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 he 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 20 countries worldwide. He has also received teaching awards from UF and an excellence in writing award from John Wiley & Sons.

Gathering and Exploring Data
Statistics: the Art and Science of Learning from Data
Using Data to Answer Statistical Questions
Sample Versus Population
Using Calculators and Computers
Chapter Summary
Chapter Problems
Exploring Data with Graphs and Numerical Summaries
Different Types of Data
Graphical Summaries of Data
Measuring the Center of Quantitative Data
Measuring the Variability of Quantitative Data
Using Measures of Position to Describe Variability
Recognizing and Avoiding Misuses of Graphical Summaries
Chapter Summary
Chapter Problems
Association: Contingency, Correlation, and Regression
the Association Between Two Categorical Variables
the Association Between Two Quantitative Variables
Predicting the Outcome of a Variable
Cautions in Analyzing Associations
Chapter Summary
Chapter Problems
Gathering Data
Experimental and Observational Studies
Good and Poor Ways to Sample
Good and Poor Ways to Experiment
Other Ways to Conduct Experimental and Nonexperimental Studies
Chapter Summary
Chapter Problems
Review
Questions
Exercises
Probability, Probability Distributions, and Sampling Distributions
Probability in our Daily Lives
How Probability Quantifies Randomness
Finding Probabilities
Conditional Probability: the Probability of a Given B
Applying the Probability Rules
Chapter Summary
Chapter Problems
Probability Distributions
Summarizing Possible Outcomes and Their Probabilities
Probabilities for Bell-Shaped Distributions
Probabilities When Each Observation Has Two Possible Outcomes
Chapter Summary
Chapter Problems
Sampling Distributions
How Sample Proportions Vary Around the Population Proportion
How Sample Means Vary Around the Population Mean
the Binomial Distribution is a Sampling Distribution (Optional)
Chapter Summary
Chapter Problems
Review
Questions
Exercises
Inferential Statistics
Statistical Inference: Confidence Intervals
Point and Interval Estimates of Population Parameters
Constructing a Confidence Interval to Estimate a Population Proportion
Constructing a Confidence Interval to Estimate a Population Mean
Choosing the Sample Size for a Study
Using Computers to Make New Estimation Methods Possible
Chapter Summary
Chapter Problems
Statistical Inference: Significance Tests about Hypotheses
Steps for Performing a Significance Test
Significance Tests about Proportions
Significance Tests about Means
Decisions and Types of Errors in Significance Tests
Limitations of Significance Tests
the Likelihood of a Type II Error (Not Rejecting H<sub>0</sub>, Even Though It's False)
Chapter Summary
Chapter Problems
Comparing Two Groups
Categorical Response: Comparing Two Proportions
Quantitative Response: Comparing Two Means
Other Ways of Comparing Means and Comparing Proportions
Analyzing Dependent Samples
Adjusting for the Effects of Other Variables
Chapter Summary
Chapter Problems
Review
Questions
Exercises
Analyzing Association and Extended Statistical Methods
Analyzing the Association Between Categorical Variables
Independence and Association
Testing Categorical Variables for Independence
Determining the Strength of the Association
Using Residuals to Reveal the Pattern of Association
Small Sample Sizes: Fisher's Exact Test
Chapter Summary
Chapter Problems
Analyzing the Association Between Quantitative Variables: Regression Analysis
Model How Two Variables are Related
Describe Strength of Association
Make Inference About the Association
How the Data Vary Around the Regression Line
Exponential Regression: a Model for Nonlinearity
Chapter Summary
Chapter Problems
Multiple Regression
Using Several Variables to Predict a Response
Extending the Correlation and R-squared for Multiple Regression
Using Multiple Regression to Make Inferences
Checking a Regression Model Using Residual Plots
Regression and Categorical Predictors
Modeling a Categorical Response
Chapter Summary
Chapter Problems
Comparing Groups: Analysis of Variance Methods
One-Way ANOVA: Comparing Several Means
Estimating Differences in Groups for a Single Factor
Two-Way ANOVA
Chapter Summary
Chapter Problems
Nonparametric Statistics
Compare Two Groups by Ranking
Nonparametric Methods for Several Groups and for Matched Pairs
Chapter Summary
Chapter Problems
Review
Questions
Exercises
Tables
Answers
Index
Index of Applications
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