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9780471329367

Chance Encounters A First Course in Data Analysis and Inference

by ;
  • ISBN13:

    9780471329367

  • ISBN10:

    0471329363

  • Edition: 1st
  • Format: Hardcover
  • Copyright: 1999-11-30
  • Publisher: Wiley

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Supplemental Materials

What is included with this book?

Summary

This unique book combines lucid and engaging exposition, graphic and poignantly applied examples, and realistic exercises to take readers beyond the mechanics of statistical techniques. The result is a journey into the realm of practical data analysis and inference-based problem solving.

Author Biography

Christopher J. Wild, University of Auckland
George A. F. Seber, University of Auckland

Table of Contents

What Is Statistics?
1(37)
Polls and Surveys
2(16)
Random Sampling
6(3)
Errors in Surveys
9(6)
Unrepresentative Information Can Be Useful
15(1)
Preparing for a Survey
15(1)
Who Uses Survey Methods?
16(2)
Experimentation
18(6)
Observational Studies
24(4)
Statistics: What Is It, and Who Uses It?
28(3)
Summary
31(6)
Review Exercises 1
33(4)
Tools for Exploring Univariate Data
37(64)
Introduction
38(5)
Types of Variables
40(3)
Presentation of Data
43(4)
The Roles of Numbers
43(1)
Guidelines for Tabular Presentation
44(3)
Simple Plots for Continuous Variables
47(14)
Dot Plots
47(2)
Stem-and-Leaf Plots
49(6)
Histograms
55(3)
Interpreting Stem-and-Leaf Plots and Histograms
58(3)
Numerical Summaries for Continuous Variables
61(14)
Locating the Center of the Data
61(5)
The Five-Number Summary
66(4)
Measuring the ``Spread'' of the Data
70(3)
Plotting Data Summaries: The Box Plot
73(2)
Repeated and Grouped Data
75(6)
Repeated Data (Discrete Variables)
75(5)
Grouped Data (Continuous Variables)
80(1)
Qualitative Variables
81(8)
Other Forms of Graphs
84(1)
Choosing between Types of Graphs
85(1)
Pareto Chart
86(3)
Summary
89(12)
Numbers and Tables of Data
90(1)
Plotting
91(1)
Review Exercises 2
91(10)
Exploratory Tools for Relationships
101(38)
Two Quantitative Variables
102(15)
Plotting the Data
102(5)
Modeling the Relationship
107(7)
The Prediction Problem
114(2)
Other Patterns
116(1)
Quantitative versus Qualitative Variables
117(7)
Using Dot Plots
120(1)
Using Stem-and-Leaf Plots
120(2)
Using Box Plots
122(1)
An Organized Approach to Comparing Groups
123(1)
Two Qualitative Variables
124(4)
Are the Patterns You See Real or Random?
128(2)
Summary
130(9)
Review Exercises 3
131(8)
Probabilities and Proportions
139(58)
Introduction
139(2)
Coin Tossing and Probability Models
141(2)
Where Do Probabilities Come From?
143(6)
Probabilities from Models
144(1)
Probabilities from Data
145(1)
Subjective Probabilities
146(1)
Manipulation of Probabilities
147(2)
Simple Probability Models
149(9)
Sample Spaces
149(1)
Events
150(2)
Combining Events
152(1)
Probability Distributions
153(4)
Probabilities and Proportions
157(1)
Probability Rules
158(5)
Addition Rule for More Than Two Mutually Exclusive Events
160(3)
Conditional Probability
163(14)
Definition
163(4)
Multiplication Rule
167(2)
More-Complicated Calculations Using Conditional Probabilities
169(8)
Statistical Independence
177(7)
Two Events
177(3)
Positive and Negative Association
180(1)
Mutual Independence of More Than Two Events
181(3)
Summary
184(13)
Summary of Concepts
184(1)
Summary of Useful Formulas
185(1)
Review Exercises 4
186(11)
Discrete Random Variables
197(34)
Random Variables
197(1)
Probability Functions
198(6)
The Binomial Distribution
204(10)
Sampling from a Finite Population
204(1)
The Binomial Assumptions
205(5)
Sampling from a Finite Population Revisited
210(4)
Expected Values
214(8)
Formula and Terminology
214(5)
Population Standard Deviation
219(1)
The Effect of Rescaling Random Variables
220(2)
Summary
222(9)
Review Exercises 5
223(8)
Continuous Random Variables
231(46)
Introduction
231(6)
Proportions as Areas: The Standardized Histogram
231(2)
Probabilities and Density Curves
233(1)
Some Comparisons with the Discrete Case
234(3)
The Normal Distribution
237(10)
Introducing the Normal Distribution
237(2)
Obtaining Probabilities
239(5)
The Inverse Problem: Percentiles and Quantiles
244(2)
Central Ranges
246(1)
Working in Standard Units
247(5)
The z-Score
247(2)
Central Ranges and Extremes Using z-Scores
249(2)
Obtaining Normal-Distribution Probabilities from Tables
251(1)
Sums and Differences of Random Quantities
252(14)
Variation and Its Propagation
252(3)
Investigating the Behavior of a Sum and a Difference
255(3)
Working with Sums and Differences
258(5)
Application to Random Samples
263(3)
Summary
266(11)
Continuous Variables and Density Curves
266(1)
The Normal Distribution
267(1)
Combining Random Quantities
267(1)
Review Exercises 6
268(9)
Sampling Distributions of Estimates
277(50)
Parameters and Estimates
278(2)
Capital Letters and Small Letters: Estimates and Estimators
279(1)
Sampling Distribution of the Sample Mean
280(12)
Means of Random Samples
280(4)
The Central Limit Effect
284(6)
Introducing the Standard Error
290(2)
Sampling Distribution of the Sample Proportion
292(5)
Sample Proportions and Their Standard Errors
292(4)
Some Asides about Polling
296(1)
Estimates That Are Approximately Normal
297(4)
Bias, Precision, and Accuracy
298(1)
Interval Estimates
299(1)
How Many Significant Figures?
300(1)
Standard Errors of Differences
301(7)
Standard Error for a Difference (Independent Samples)
302(2)
Interpreting an Interval for a Difference
304(1)
Individual Two-Standard-Error Intervals and Differences
305(3)
Student's t-Distribution
308(5)
Introduction
308(1)
The Usefulness of Student's t-Distribution
309(1)
Upper-Tail Probabilities and Percentage Points
310(3)
Summary
313(14)
Sampling Distributions
313(1)
Estimation
314(1)
Student's t-Distribution
315(1)
Review Exercises 7
315(12)
Confidence Intervals
327(40)
Introduction
327(8)
Adjusting the Confidence Level
331(2)
How Can We Make a Precise Statement with Confidence?
333(1)
Conservative Confidence Levels
334(1)
Means
335(2)
Proportions
337(1)
Comparing Two Means
338(3)
Comparing Two Proportions
341(10)
Independence Case
341(2)
Other Common Comparisons
343(6)
``Margins of Error'' in Media Reports
349(2)
How Big Should My Study Be?
351(3)
Proportions
351(1)
Means
352(2)
Summary
354(13)
Review Exercises 8
355(12)
Significance Testing: Using Data to Test Hypotheses
367(42)
Getting Started
368(6)
Examples
368(3)
Measuring Distance in Numbers of Standard Errors
371(1)
The Difference between Tests and Intervals
372(2)
What Do We Test? Types of Hypotheses
374(4)
We Cannot Prove That a Hypothesized Value Is True
374(1)
The Research Hypothesis and the Null Hypothesis
375(1)
The Alternative Hypothesis (H1)
376(2)
Measuring the Evidence against a Null Hypothesis
378(11)
t-Tests and P-Values
378(5)
Further Examples
383(6)
Hypothesis Testing as Decision Making
389(2)
Why Tests Should Be Supplemented by Intervals
391(5)
A Relationship between Tests and Intervals
391(1)
Interpreting the Word Significant
392(3)
How Do You Show That a Hypothesis Is True?
395(1)
Detecting Differences When They Matter
396(1)
The Test Statistic and the P-Value as General Ideas
397(1)
Summary
398(11)
Hypotheses
398(1)
P-Values
399(1)
Significance
399(1)
Review Exercises 9
400(9)
Data on a Continuous Variable
409(58)
One-Sample Issues
410(18)
Tests and Confidence Intervals for a Mean
410(7)
Paired Comparisons
417(6)
A Nonparametric Test
423(3)
Inferences about Spread
426(2)
Two Independent Samples
428(6)
Questions of Study Design and Analysis
428(3)
Comparing Two Means
431(3)
More Than Two Samples
434(11)
One-Way Analysis of Variance and the F-Test
434(4)
The F-Test and the Analysis-of-Variance Table
438(7)
Blocking, Stratification, and Related Samples
445(5)
Pairing
445(3)
More General Blocking and Stratification
448(2)
Summary
450(17)
Some General Ideas about Analyzing Data
450(1)
Normal Theory Techniques
451(1)
Study Design and Interpretation
452(1)
Review Exercises 10
452(15)
Tables of Counts
467(36)
One-Dimensional Tables
468(7)
The Chi-Square Test for Goodness of Fit
469(4)
Tables for the Chi-Square Distribution
473(2)
Two-Way Tables of Counts
475(16)
Introduction
475(6)
The Chi-Square Test of Homogeneity
481(6)
The Chi-Square Test of Independence
487(2)
2 X 2 Tables
489(2)
The Validity of the Chi-Square Test
491(1)
The Perils of Collapsing Tables
491(2)
Summary
493(10)
General Ideas about Chi-Square Tests
493(1)
One-Dimensional Tables
493(1)
Two-Way Tables
494(1)
Review Exercises 11
495(8)
Relationships between Quantitative Variables: Regression and Correlation
503(54)
Why Do Regression?
504(5)
Correlation versus Regression
504(1)
Causal Relationships
504(4)
Inferences about Theories
508(1)
Introduction to Relationship Modeling
509(6)
The Straight Line
511(1)
Extensions
512(1)
The Exponential Curve
512(2)
Other Types of Trend Curves
514(1)
Choosing the Best Line
515(5)
What Line Fits the Data Best?
516(2)
The Least-Squares Line
518(2)
Formal Inference for the Simple Linear Model
520(19)
The Simple Linear Model
520(5)
Inferences about the Slope and Intercept
525(7)
The Regression Model and Prediction
532(3)
Model Checking
535(4)
Correlation and Association
539(6)
Two Regression Lines
539(1)
The Correlation Coefficient
540(5)
Summary
545(12)
Concepts
545(1)
Linear Relationships
546(1)
Review Exercises 12
546(11)
Control Charts See web site
Time Series See web site
APPENDIXES Statistical Tables 557(12)
A1 Random Numbers
558(1)
A2 Binomial Distribution (Individual Terms)
559(3)
A3 Minimum Sample Sizes
562(1)
A4 Standard Normal Distribution
563(2)
A5 Additional Standard Normal Tables
565(1)
A6 Student's t-Distribution
566(1)
A7 Chi-Square Distribution
567(2)
References 569(6)
Answers to Selected Problems 575(30)
Index 605

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The New copy of this book will include any supplemental materials advertised. Please check the title of the book to determine if it should include any access cards, study guides, lab manuals, CDs, etc.

The Used, Rental and eBook copies of this book are not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.

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