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Interactive Statistics,9780132310369
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Interactive Statistics

by ;
Edition:
Spiral
ISBN13:

9780132310369

ISBN10:
0132310368
Format:
Paperback
Pub. Date:
12/1/1998
Publisher(s):
Prentice Hall
List Price: $80.00

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This is the Spiral edition with a publication date of 12/1/1998.
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Summary

This volume takes a hands-on approach to the introduction of basic statistical methods, using a highly interactive method. Readers are taught to ask "why" and think like a statistician to find the logical solution. With its strong emphasis on data analysis, the book gives readers the skills to understand and interpret a variety of statistical results. Provides an overview of the basic components of decision-making and using statistical ideas. Helps readers master the language of statistics, the importance of a p-value, and the meaning of statistical significance. Includes coverage of current topics such as power of the test and effect size, bootstrap, and blocking designs in experiments. Usesexamples frombusiness, sports, economics, and more to address a wide range of interests. Includes chapter-ending TI Quick Steps for using calculators to enter, manipulate, and plot data. For anyone interested in learning more about statistics.

Table of Contents

Preface VII
How to Make a Decision with Statistics
1(58)
Introduction---Statistics and the Scientific Method
1(1)
Decisions, Decisions
2(1)
The Language of Statistical Decision Making
3(9)
Testing Theories
4(2)
How Do We Decide Which Theory to Support?
6(3)
What Errors Could We Make?
9(3)
What's in the Bag?
12(24)
Forming a Decision Rule
14(6)
More on the Direction of Extreme
20(3)
How Unusual Are the Data?: The p-value
23(13)
Significant versus Important
36(23)
Chapter Summary
39(1)
Key Terms
40(1)
Exercises
40, 55(46)
Appendix 1.A Selecting Two Vouchers
46(5)
1.A.1 Forming a Decision Rule
51(3)
1.A.2 What's in the Bag? p-value When the Sample Size is 2
54(5)
Producing Data
59(46)
Introduction
59(1)
Why Sample?
60(1)
The Language of Sampling
60(3)
Good Data?
63(5)
Simple Random Sampling
68(7)
Stratified Random Sampling
75(6)
Systematic Sampling
81(4)
Cluster Sampling
85(4)
Multistage Sampling
89(16)
Chapter Summary
94(1)
Key Terms
95(1)
Exercises
95(7)
TI Quick Steps
102(3)
Observational Studies and Experiments
105(42)
Introduction
105(1)
Why Study Studies?
105(1)
The Language of Studies
106(7)
Observation versus Experimentation
106(1)
Relating Two Variables
107(3)
A Problem Called Confounding
110(3)
Understanding Observational Studies
113(5)
Types of Observational Studies
113(3)
Difficulties in Observational Studies
116(2)
Understanding Experiments
118(12)
Basic Terminology
118(4)
Principles for Planning an Experiment
122(8)
Reading with a Critical Eye
130(4)
What about Ethics?
134(13)
Chapter Summary
137(1)
Key Terms
138(1)
Exercises
138(9)
Summarizing Data Graphically
147(46)
Introduction
147(1)
What Are We Summarizing?
148(9)
Types of Variables
149(3)
What?, How?, Who?, When?
152(3)
Distribution of a Variable
155(2)
Displaying Distributions---Qualitative Variables
157(6)
Pie Charts
157(1)
Bar Graphs
158(5)
Displaying Distributions---Quantitative Variables
163(18)
Frequency Plots
163(3)
Shapes of Distributions
166(6)
Histograms
172(6)
Time Plots
178(3)
Guidelines for Plots, Graphs, and Pictures
181(12)
Chapter Summary
184(1)
Key Terms
185(1)
Exercises
185(4)
TI Quick Steps
189(4)
Summarizing Data Numerically
193(42)
Introduction
193(1)
Measuring Center
194(9)
Measuring Variation or Spread
203(17)
Linear Transformations and Standardization
220(15)
Chapter Summary
225(1)
Key Terms
226(1)
Exercises
226(6)
TI Quick Steps
232(3)
Using Models to Make Decisions
235(42)
Introduction
235(1)
Why Do We Need to Know Models?
236(1)
Modeling Continuous Variables
237(20)
Normal Distributions
238(15)
Uniform Distributions
253(4)
Modeling Discrete Variables
257(20)
Chapter Summary
262(1)
Key Terms
263(1)
Exercises
263(5)
TI Quick Steps
268(9)
Is There a Relationship?
277(72)
Introduction
277(1)
Two Quantitative Variables
278(44)
Scatterplots
279(4)
Simple Linear Regression
283(3)
Calculating the Least Squares Regression Line
286(6)
Statistically Significant Relationship?
292(6)
Residual Analysis
298(3)
Influential Points and Outliers
301(4)
Correlation: How Strong Is the Linear Relationship?
305(11)
Regression Effect
316(6)
When Scatterplots Don't Work: Two Qualitative Variables
322(27)
Marginal and Conditional Distributions
322(4)
Is There a Significant Relationship?
326(2)
Simpson's Paradox
328(5)
Chapter Summary
333(1)
Key Terms
333(1)
Exercises
333(12)
TI Quick Steps
345(4)
How to Measure Uncertainty with Probability
349(66)
Introduction
349(1)
What Is Probability?
350(1)
Simulating Probabilities
351(7)
The Language of Probability
358(25)
Sample Spaces and Events
359(6)
Rules of Probabilities
365(10)
Partitioning and Bayes's Rule
375(8)
Random Variables
383(32)
Discrete Random Variables
384(6)
Continuous Random Variables
390(5)
Chapter Summary
395(1)
Key Terms
396(1)
Exercises
397, 411(403)
Appendix 8.A The Binomial Distribution
403(10)
TI Quick Steps
413(2)
Sampling Distributions: Measuring the Accuracy of Sample Results
415(40)
Introduction
415(1)
Sampling Distribution of a Sample Proportion
416(6)
Bias and Variability
422(16)
Sampling Distribution of a Sample Mean
438(17)
Chapter Summary
445(2)
Key Terms
447(1)
Exercises
447(4)
TI Quick Steps
451(4)
Making Decisions with Confidence
455(72)
Introduction
455(1)
Making Decisions about a Population Proportion
456(14)
Making Decisions about a Population Mean
470(18)
Known Population Standard Deviation
471(5)
Unknown Population Variance
476(12)
Confidence Interval Estimation: For a Proportion
488(11)
Confidence Interval Estimation: For a Mean
499(8)
Confidence Intervals and Hypothesis Testing
507(20)
Chapter Summary
509(1)
Key Terms
510(1)
Exercises
511(8)
TI Quick Steps
519(8)
Comparing Two Treatments
527(50)
Introduction
527(2)
Paired Samples versus Independent Samples
529(5)
Paired Samples
534(9)
Independent Samples: Comparing Means
543(16)
Independent Samples: Comparing Proportions
559(18)
Chapter Summary
566(1)
Key Terms
567(1)
Exercises
567(5)
TI Quick Steps
572(5)
Comparing Many Treatments
577(36)
Introduction
577(3)
Analysis of Variance
580(5)
The F-Test Statistic and the F-distribution
585(5)
ANOVA: Letting the Computer Do the Work!
590(3)
How Do We Get the Mean Squares?
593(7)
What Does Reject H0 in Anova Mean? (And What Doesn't It Mean?)
600(13)
Chapter Summary
605(1)
Key Terms
606(1)
Exercises
606(3)
TI Quick Steps
609(4)
Analysis of Count Data
613(40)
Introduction
613(1)
The Chi-Square Statistic
614(3)
Test of Goodness of Fit
617(8)
Test of Homogeneity
625(9)
Test of Independence
634(19)
Chapter Summary
641(1)
Key Terms
642(1)
Exercises
642(7)
TI Quick Steps
649(4)
Appendix 653(10)
Answers to Odd-Numbered Exercises 663(11)
Index 674


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