Interactive Statistics

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  • Edition: 3rd
  • Format: Paperback
  • Copyright: 2005-06-10
  • Publisher: Pearson

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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

Prefacep. VII
How to Make a Decision with Statisticsp. 1
Introduction--Statistics and the Scientific Methodp. 1
Decisions, Decisionsp. 2
The Language of Statistical Decision Makingp. 3
What's in the Bag?p. 12
Significant versus Importantp. 36
Producing Datap. 59
Introductionp. 59
Why Sample?p. 60
The Language of Samplingp. 60
Good Data?p. 63
Simple Random Samplingp. 68
Stratified Random Samplingp. 75
Systematic Samplingp. 81
Cluster Samplingp. 85
Multistage Samplingp. 89
Observational Studies and Experimentsp. 105
Introductionp. 105
Why Study Studies?p. 105
The Language of Studiesp. 106
Understanding Observational Studiesp. 113
Understanding Experimentsp. 118
Reading with a Critical Eyep. 130
What about Ethics?p. 134
Summarizing Data Graphicallyp. 147
Introductionp. 147
What Are We Summarizing?p. 148
Displaying Distributions--Qualitative Variablesp. 157
Displaying Distributions--Quantitative Variablesp. 163
Guidelines for Plots, Graphs, and Picturesp. 181
Summarizing Data Numericallyp. 193
Introductionp. 193
Measuring Centerp. 194
Measuring Variation or Spreadp. 203
Linear Transformations and Standardizationp. 220
Using Models to Make Decisionsp. 235
Introductionp. 235
Why Do We Need to Know Models?p. 236
Modeling Continuous Variablesp. 237
Modeling Discrete Variablesp. 257
Is There a Relationship?p. 277
Introductionp. 277
Two Quantitative Variablesp. 278
When Scatterplots Don't Work: Two Qualitative Variablesp. 322
How to Measure Uncertainty with Probabilityp. 349
Introductionp. 349
What Is Probability?p. 350
Simulating Probabilitiesp. 351
The Language of Probabilityp. 358
Random Variablesp. 383
Sampling Distributions: Measuring the Accuracy of Sample Resultsp. 415
Introductionp. 415
Sampling Distribution of a Sample Proportionp. 416
Bias and Variabilityp. 422
Sampling Distribution of a Sample Meanp. 438
Making Decisions with Confidencep. 455
Introductionp. 455
Making Decisions about a Population Proportionp. 456
Making Decisions about a Population Meanp. 470
Confidence Interval Estimation: For a Proportionp. 488
Confidence Interval Estimation: For a Meanp. 499
Confidence Intervals and Hypothesis Testingp. 507
Comparing Two Treatmentsp. 527
Introductionp. 527
Paired Samples versus Independent Samplesp. 529
Paired Samplesp. 534
Independent Samples: Comparing Meansp. 543
Independent Samples: Comparing Proportionsp. 559
Comparing Many Treatmentsp. 577
Introductionp. 577
Analysis of Variancep. 580
The F-Test Statistic and the F-distributionp. 585
ANOVA: Letting the Computer Do the Work!p. 590
How Do We Get the Mean Squares?p. 593
What Does Reject H[subscript 0] in ANOVA Mean? (And What Doesn't It Mean?)p. 600
Analysis of Count Datap. 613
Introductionp. 613
The Chi-Square Statisticp. 614
Test of Goodness of Fitp. 617
Test of Homogeneityp. 625
Test of Independencep. 634
Appendixp. 653
Answers to Odd-Numbered Exercisesp. 663
Indexp. 674
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