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Elementary Statistics : A Step by Step Approach W/MathZone

ISBN: 9780073251639 | 0073251631
Edition: 6th
Format: Hardcover
Publisher: McGraw-Hill Science/Engineering/Math
Pub. Date: 12/7/2005

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SummaryTable of Contents
ELEMENTARY STATISTICS: A STEP BY STEP APPROACHis for general beginning statistics courses with a basic algebra prerequisite. The book is non-theoretical, explaining concepts intuitively and teaching problem solving through worked examples and step-by-step instructions. This edition places more emphasis on conceptual understanding and understanding results. This edition also features increased emphasis on Excel, MINITAB, and the TI-83 Plus and TI 84-Plus graphing calculators, computing technologies commonly used in such courses.
Prefacexi
The Nature of Probability and Statistics
1(32)
Introduction
2(1)
... MORE
Descriptive and Inferential Statistics
3(3)
Variables and Types of Data
6(3)
Data Collection and Sampling Techniques
9(4)
Random Sampling
10(2)
Systematic Sampling
12(1)
Stratified Sampling
12(1)
Cluster Sampling
12(1)
Other Sampling Methods
13(1)
Observational and Experimental Studies
13(3)
Uses and Misuses of Statistics
16(3)
Suspect Samples
17(1)
Ambiguous Averages
17(1)
Changing the Subject
17(1)
Detached Statistics
18(1)
Implied Connections
18(1)
Misleading Graphs
18(1)
Faulty Survey Questions
18(1)
Computers and Calculators
19(5)
Summary
24(9)
Frequency Distributions and Graphs
33(62)
Introduction
34(1)
Organizing Data
35(13)
Categorical Frequency Distributions
36(1)
Grouped Frequency Distributions
37(11)
Histograms, Frequency Polygons, and Ogives
48(15)
The Histogram
48(2)
The Frequency Polygon
50(1)
The Ogive
51(2)
Relative Frequency Graphs
53(2)
Distribution Shapes
55(8)
Other Types of Graphs
63(23)
Pareto Charts
64(1)
The Time Series Graph
65(1)
The Pie Graph
66(4)
Misleading Graphs
70(3)
Stem and Leaf Plots
73(13)
Summary
86(9)
Data Description
95(76)
Introduction
96(1)
Measures of Central Tendency
97(18)
The Mean
98(3)
The Median
101(2)
The Mode
103(2)
The Midrange
105(1)
The Weighted Mean
106(2)
Distribution Shapes
108(7)
Measures of Variation
115(18)
Range
116(1)
Population Variance and Standard Deviation
117(2)
Sample Variance and Standard Deviation
119(2)
Variance and Standard Deviation for Grouped Data
121(3)
Coefficient of Variation
124(1)
Range Rule of Thumb
125(1)
Chebyshev's Theorem
125(2)
The Empirical (Normal) Rule
127(6)
Measures of Position
133(19)
Standard Scores
133(2)
Percentiles
135(6)
Quartiles and Deciles
141(1)
Outliers
142(10)
Exploratory Data Analysis
152(9)
The Five-Number Summary and Boxplots
153(8)
Summary
161(10)
Probability and Counting Rules
171(66)
Introduction
172(1)
Sample Spaces and Probability
173(16)
Basic Concepts
173(3)
Classical Probability
176(3)
Complementary Events
179(2)
Empirical Probability
181(2)
Law of Large Numbers
183(1)
Subjective Probability
183(1)
Probability and Risk Taking
184(5)
The Addition Rules for Probability
189(10)
The Multiplication Rules and Conditional Probability
199(13)
The Multiplication Rules
199(5)
Conditional Probability
204(3)
Probabilities for ``At Least''
207(5)
Counting Rules
212(11)
The Fundamental Counting Rule
212(3)
Factorial Notation
215(1)
Permutations
215(2)
Combinations
217(6)
Probability and Counting Rules
223(4)
Summary
227(10)
Discrete Probability Distributions
237(48)
Introduction
238(1)
Probability Distributions
239(6)
Mean, Variance, Standard Deviation, and Expectation
245(11)
Mean
245(3)
Variance and Standard Deviation
248(2)
Expectation
250(6)
The Binomial Distribution
256(13)
Other Types of Distributions (Optional)
269(9)
The Multinomial Distribution
269(1)
The Poisson Distribution
270(2)
The Hypergeometric Distribution
272(6)
Summary
278(7)
The Normal Distribution
285(62)
Introduction
286(2)
Properties of a Normal Distribution
288(2)
The Standard Normal Distribution
290(17)
Finding Areas Under the Standard Normal Distribution Curve
291(8)
A Normal Distribution Curve as a Probability Distribution Curve
299(8)
Applications of the Normal Distribution
307(15)
Finding Data Values Given Specific Probabilities
311(2)
Determining Normality
313(9)
The Central Limit Theorem
322(9)
Distribution of Sample Means
322(6)
Finite Population Correction Factor (Optional)
328(3)
The Normal Approximation to the Binomial Distribution
331(7)
Summary
338(9)
Confidence Intervals and Sample Size
347(44)
Introduction
348(1)
Confidence Intervals for the Mean (σ Known or n ≥ 30) and Sample Size
349(13)
Confidence Intervals
350(5)
Sample Size
355(7)
Confidence Intervals for the Mean (σ Unknown and n < 30)
362(7)
Confidence Intervals and Sample Size for Proportions
369(8)
Confidence Intervals
370(1)
Sample Size for Proportions
371(6)
Confidence Intervals for Variances and Standard Deviations
377(7)
Summary
384(7)
Hypothesis Testing
391(72)
Introduction
392(1)
Steps in Hypothesis Testing--Traditional Method
393(12)
z Test for a Mean
405(14)
P-Value Method for Hypothesis Testing
410(9)
t Test for a Mean
419(10)
z Test for a Proportion
429(8)
Χ2 Test for a Variance or Standard Deviation
437(12)
Additional Topics Regarding Hypothesis Testing
449(4)
Confidence Intervals and Hypothesis Testing
449(2)
Type II Error and the Power of a Test
451(2)
Summary
453(10)
Testing the Difference Between Two Means, Two Variances, and Two Proportions
463(64)
Introduction
464(1)
Testing the Difference Between Two Means: Large Samples
465(12)
Testing the Difference Between Two Variances
477(10)
Testing the Difference Between Two Means: Small Independent Samples
487(10)
Testing the Difference Between Two Means: Small Dependent Samples
497(12)
Testing the Difference Between Proportions
509(8)
Summary
517(10)
Hypothesis-Testing Summary 1
525(2)
Correlation and Regression
527(56)
Introduction
528(1)
Scatter Plots
529(4)
Correlation
533(11)
Correlation Coefficient
533(3)
The Significance of the Correlation Coefficient
536(4)
Correlation and Causation
540(4)
Regression
544(14)
Line of Best Fit
545(1)
Determination of the Regression Line Equation
545(13)
Coefficient of Determination and Standard Error of the Estimate
558(8)
Types of Variation for the Regression Model
558(3)
Coefficient of Determination
561(1)
Standard Error of the Estimate
561(2)
Prediction Interval
563(3)
Multiple Regression (Optional)
566(9)
The Multiple Regression Equation
568(2)
Testing the Significance of R
570(1)
Adjusted R2
571(4)
Summary
575(8)
Other Chi-Square Tests
583(36)
Introduction
584(1)
Test for Goodness of Fit
585(12)
Test of Normality (Optional)
590(7)
Tests Using Contingency Tables
597(15)
Test for Independence
597(6)
Test for Homogeneity of Proportions
603(9)
Summary
612(7)
Analysis of Variance
619(40)
Introduction
620(1)
One-Way Analysis of Variance
621(8)
The Scheffe Test and the Tukey Test
629(7)
Scheffe Test
630(1)
Tukey Test
631(5)
Two-Way Analysis of Variance
636(14)
Summary
650(9)
Hypothesis-Testing Summary 2
657(2)
Nonparametric Statistics
659(48)
Introduction
660(1)
Advantages and Disadvantages of Nonparametric Methods
661(2)
Advantages
661(1)
Disadvantages
661(1)
Ranking
662(1)
The Sign Test
663(8)
Single-Sample Sign Test
663(3)
Paired-Sample Sign Test
666(5)
The Wilcoxon Rank Sum Test
671(5)
The Wilcoxon Signed-Rank Test
676(5)
The Kruskal-Wallis Test
681(6)
The Spearman Rank Correlation Coefficient and the Runs Test
687(11)
Rank Correlation Coefficient
687(3)
The Runs Test
690(8)
Summary
698(9)
Hypothesis-Testing Summary 3
704(3)
Sampling and Simulation
707(32)
Introduction
708(1)
Common Sampling Techniques
709(14)
Random Sampling
709(4)
Systematic Sampling
713(1)
Stratified Sampling
714(2)
Cluster Sampling
716(1)
Other Types of Sampling Techniques
717(6)
Surveys and Questionnaire Design
723(3)
Simulation Techniques
726(1)
The Monte Carlo Method
726(6)
Summary
732(7)
Appendix A Algebra Review739(6)
Appendix B-1 Writing the Research Report745(2)
Appendix B-2 Bayes' Theorem747(4)
Appendix B-3 Alternate Approach to the Standard Normal Distribution751(4)
Appendix C Tables755(30)
Appendix D Data Bank785(8)
Appendix E Glossary793(8)
Appendix F Bibliography801(2)
Appendix G Photo Credits803
Appendix H Selected Answers1(1)
Index1

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