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Interactive Statistics

ISBN: 9780130655974 | 013065597X
Edition: 3rd
Format: Paperback
Publisher: PRENTICE HALL
Pub. Date: 1/1/2006

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SummaryTable of Contents
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 statis... MORE
Prefacexi
How to Make a Decision with Statistics
1(74)
Introduction---Statistics and the Scientific Method
1(1)
... MORE
Decisions, Decisions
2(2)
The Language of Statistical Decision Making
4(10)
Testing Theories
4(2)
How Do We Decide Which Theory to Support?
6(4)
What Errors Could We Make?
10(4)
What's in the Bag?
14(26)
Forming a Decision Rule
16(5)
More on the Direction of Extreme
21(4)
How Unusual Are the Data? The p-value
25(15)
Selecting Two Vouchers
40(9)
Forming a Decision Rule
45(3)
What's in the Bag? p-value When the Sample Size Is 2
48(1)
Significant versus Important
49(26)
Chapter Summary
52(2)
Key Terms
54(1)
Exercises
54(21)
Producing Data
75(54)
Introduction
75(1)
Why Sample?
76(1)
The Language of Sampling
76(3)
Good Data?
79(5)
Simple Random Sampling
84(7)
Stratified Random Sampling
91(7)
Systematic Sampling
98(4)
Cluster Sampling
102(4)
Multistage Sampling
106(23)
Chapter Summary
111(1)
Key Terms
112(1)
Exercises
112(16)
TI Quick Steps
128(1)
Observational Studies and Experiments
129(54)
Introduction
129(1)
Why Study Studies?
130(1)
The Language of Studies
130(8)
Observation versus Experimentation
130(1)
Relating Two Variables
131(4)
A Problem Called Confounding
135(3)
Understanding Observational Studies
138(7)
Types of Observational Studies
139(2)
Difficulties in Observational Studies
141(4)
Understanding Experiments
145(14)
Basic Terminology
145(4)
Principles for Planning an Experiment
149(10)
Reading with a Critical Eye
159(3)
What about Ethics?
162(21)
Chapter Summary
165(1)
Key Terms
166(1)
Exercises
167(16)
Summarizing Data Graphically
183(84)
Introduction
183(1)
What Are We Summarizing?
184(8)
Types of Variables
185(3)
What? How? Who? When?
188(2)
Distribution of a Variable
190(2)
Displaying Distributions---Qualitative Variables
192(17)
Pie Charts
192(2)
Bar Graphs
194(5)
Displaying Relationships between Two Qualitative Variables
199(10)
Displaying Distributions---Quantitative Variables
209(36)
Frequency Plots
209(3)
Shapes of Distributions
212(1)
Stem-and-Leaf Plots
213(8)
Histograms
221(10)
Time Plots
231(6)
Scatterplots
237(8)
Guidelines for Plots, Graphs, and Pictures
245(22)
Chapter Summary
248(1)
Key Terms
249(1)
Exercises
249(14)
TI Quick Steps
263(4)
Summarizing Data Numerically
267(58)
Introduction
267(1)
Measuring Center
268(12)
Mean
268(3)
Median
271(2)
Another Measure---The Mode
273(1)
Which Measure of Center to Use?
274(6)
Measuring Variation or Spread
280(23)
Range
280(1)
Interquartile Range
281(1)
Five-number Summary
282(9)
Standard Deviation
291(12)
Linear Transformations and Standardization
303(22)
Chapter Summary
310(1)
Key Terms
310(1)
Exercises
311(12)
TI Quick Steps
323(2)
Using Models to Make Decisions
325(50)
Introduction
325(1)
Why Do We Need to Know Models?
326(1)
Modeling Continuous Variables
327(27)
Normal Distributions
329(20)
Uniform Distributions
349(5)
Modeling Discrete Variables
354(21)
Chapter Summary
360(1)
Key Terms
361(1)
Exercises
361(9)
TI Quick Steps
370(5)
How to Measure Uncertainty with Probability
375(88)
Introduction
375(1)
What Is Probability?
376(1)
Simulating Probabilities
377(10)
The Language of Probability
387(35)
Sample Spaces and Events
387(7)
Rules of Probabilities
394(18)
Partitioning and Bayes's Rule
412(10)
Random Variables
422(41)
Discrete Random Variables
424(6)
Binomial Random Variables
430(9)
Continuous Random Variables
439(10)
Chapter Summary
449(2)
Key Terms
451(1)
Exercises
451(10)
TI Quick Steps
461(2)
Sampling Distributions: Measuring the Accuracy of Sample Results
463(54)
Introduction
463(2)
Sampling Distribution of a Sample Proportion
465(7)
Bias and Variability
472(22)
Sampling Distribution of a Sample Mean
494(23)
Chapter Summary
509(1)
Key Terms
510(1)
Exercises
511(5)
TI Quick Steps
516(1)
Making Decisions about a Population Proportion with Confidence
517(50)
Introduction
517(1)
Learning about a Population Proportion
518(1)
Testing Hypotheses about a Population Proportion
519(19)
Confidence Interval Estimation for a Population Proportion
538(13)
Determining a Sample Size
551(4)
Using Confidence Intervals to Make Decisions
555(12)
Chapter Summary
557(2)
Key Terms
559(1)
Exercises
559(5)
TI Quick Steps
564(3)
Making Decisions about a Population Mean with Confidence
567(52)
Introduction
567(1)
Testing Hypotheses about a Population Mean
568(21)
Confidence Interval Estimation for a Population Mean
589(12)
Confidence Intervals and Hypothesis Testing
601(18)
Chapter Summary
605(1)
Key Terms
606(1)
Exercises
606(6)
TI Quick Steps
612(7)
Comparing Two Treatments
619(68)
Introduction
619(4)
Paired Samples versus Independent Samples
623(4)
Paired Samples
627(15)
Independent Samples: Comparing Means
642(23)
Independent Samples: Comparing Proportions
665(22)
Chapter Summary
674(1)
Key Terms
675(1)
Exercises
675(7)
TI Quick Steps
682(5)
Comparing Many Treatments
687(56)
Introduction
687(1)
One-Way Analysis of Variance
688(7)
Assumptions in One-Way ANOVA
695(2)
The F-distribution
697(10)
Computational Details of One-Way ANOVA
707(9)
How Do We Compute the F-Statistic?
708(1)
Measuring Variation Between the Groups (MSB)
708(1)
Measuring Variation Within the Groups (MSW)
709(1)
Measuring Total Variation
709(2)
Performing an ANOVA F-test Using the TI
711(5)
Multiple Comparisons
716(7)
Why Do We Need ANOVA?
716(1)
Multiple Comparisons
717(6)
Two-Way ANOVA and Interaction
723(20)
Chapter Summary
729(1)
Key Terms
730(1)
Exercises
730(3)
TI Quick Steps
733(10)
Is There a Relationship Between Two or More Quantitative Variables?
743(108)
Introduction
743(1)
Displaying the Relationship
744(3)
Modeling a Linear Relationship
747(11)
Simple Linear Regression
747(4)
Calculating the Least Squares Regression Line
751(7)
Residual Analysis
758(7)
Influential Points and Outliers
765(4)
Statistically Significant Relationship?
769(6)
Correlation: How Strong Is the Linear Relationship?
775(21)
How to Calculate r
778(8)
Relationship Between r and the Slope
786(10)
Regression Effect
796(3)
The Squared Correlation r2---What Does It Tell Us?
799(1)
Inference in Simple Linear Regression
800(21)
The Simple Linear Regression Model
801(3)
Testing Hypotheses about the Linear Relationship
804(6)
Predicting for an Individual versus Estimating the Mean
810(3)
Checking Assumptions for Simple Linear Regression
813(8)
Multiple Regression
821(30)
Chapter Summary
828(1)
Key Terms
829(1)
Exercises
829(12)
TI Quick Steps
841(10)
Analysis of Count Data
851(52)
Introduction
851(1)
The Chi-Square Statistic
852(5)
Test of Goodness of Fit
857(9)
Test of Homogeneity
866(11)
Test of Independence
877(26)
Chapter Summary
891(1)
Key Terms
892(1)
Exercises
892(7)
TI Quick Steps
899(4)
What if the Assumptions Don't Hold?
903(36)
Introduction
903(1)
One Sample---Sign Test
904(5)
Two Independent Samples---Rank Sum Test
909(8)
Frame of Reference
911(6)
Paired Samples---Signed Rank Test
917(6)
Frame of Reference
918(5)
Kruskal-Wallis Test
923(16)
Chapter Summary
925(1)
Key Terms
925(1)
Exercises
925(14)
Appendix939(20)
Answers to Odd-Numbered Exercises959(24)
Index983

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