Interactive Statistics

by Aliaga, Martha; Gunderson, Brenda

• ISBN13: 9780132310369
• ISBN10: 0132310368
• Edition: Spiral
• Format: Paperback
• Copyright: 1998-12-01
• Publisher: Prentice Hall

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