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Statistics: Principles and Methods 8th edition [Pehme köide]

(University of Wisconsin, Madison), (University of Wisconsin, Madison)
  • Formaat: Paperback / softback, 576 pages, kõrgus x laius x paksus: 272x218x25 mm, kaal: 1134 g
  • Ilmumisaeg: 19-Sep-2024
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 1119497116
  • ISBN-13: 9781119497110
Teised raamatud teemal:
  • Formaat: Paperback / softback, 576 pages, kõrgus x laius x paksus: 272x218x25 mm, kaal: 1134 g
  • Ilmumisaeg: 19-Sep-2024
  • Kirjastus: John Wiley & Sons Inc
  • ISBN-10: 1119497116
  • ISBN-13: 9781119497110
Teised raamatud teemal:

Statistics: Principles and Methods, 8th Edition provides students and business professionals with a comprehensive introduction to statistics concepts, terminology, and methods with a wide array of practical applications. Real-world data provides an easily relatable frame of reference, while numerous examples reinforce key ideas and demonstrate critical concepts to help ease student comprehension. Designed for those seeking a highly practical introduction to statistical measurement, reasoning, and analysis, this book requires no specific mathematical background and leaves derivations behind in favor of logic, reasoning, and modern statistics software.

Concepts are introduced first in a real-life setting to illustrate immediate relevancy, and are subsequently expanded to relate underlying mechanisms, limitations, and further applications. An emphasis on the relationship between validity and assumptions underscores the importance of critical thinking and the use of appropriate models while instilling thoughtful habits that lead to accuracy in interpretation. Going beyond the typical introductory text to keep the focus on application, this book gives students a deeper understanding of statistics as it is used every day across disciplines and industries.

1 Introduction to Statistics
1(16)
1 The Subject and Scope of Statistics
2(2)
2 Statistics in Aid of Scientific Inquiry
4(2)
3 Two Basic Concepts---Population and Sample
6(5)
4 The Purposeful Collection of Data
11(1)
Case Study: Statistics in Context
12(2)
5 Objectives of Statistics
14(3)
2 Organization and Description of Data
17(47)
1 Main Types of Data
18(1)
2 Describing Data by Tables and Graphs
19(12)
3 Measures of Center
31(6)
4 Measures of Variation
37(10)
5 Checking the Stability of the Observations Over Time
47(3)
6 More on Graphics
50(2)
Case Study: Statistics in Context
52(12)
3 Descriptive Study of Bivariate Data
64(27)
1 Summarization of Bivariate Categorical Data
65(4)
2 A Designed Experiment for Making a Comparison
69(1)
3 Scatter Diagram of Bivariate Measurement Data
70(3)
4 The Correlation Coefficient---A Measure of Linear Relation
73(9)
5 Prediction of One Variable from Another (Linear Regression)
82(9)
4 Probability
91(43)
1 Probability of an Event
92(5)
2 Methods of Assigning Probability
97(5)
3 Event Operations and Two Laws of Probability
102(7)
4 Conditional Probability and Independence
109(8)
5 Bayes' Theorem
117(4)
6 Random Sampling from a Finite Population
121(5)
Case Study: Statistics in Context
126(8)
5 Probability Distributions
134(44)
1 Random Variables
135(3)
2 Probability Distribution of a Discrete Random Variable
138(6)
3 Mean (Expected Value) and Standard Deviation of a Probability Distribution
144(6)
4 Successes and Failures---Bernoulli Trials
150(4)
5 The Binomial Distribution
154(11)
6 The Poisson Distribution and Rare Events
165(13)
6 The Normal Distribution
178(32)
1 Probability Model for a Continuous Random Variable
179(5)
2 The Normal Distribution---Its General Features
184(2)
3 The Standard Normal Distribution
186(5)
4 Probability Calculations with Normal Distributions
191(3)
5 The Normal Approximation to the Binomial
194(5)
6 Checking the Plausibility of a Normal Model
199(3)
7 Transforming Observations to Attain Near Normality
202(8)
7 Variation in Repeated Samples---Sampling Distributions
210(25)
1 The Sampling Distribution of a Statistic
212(6)
2 Distribution of the Sample Mean and the Central Limit Theorem
218(10)
Case Study: Statistics in Context
228(7)
8 Drawing Inferences from Large Samples
235(43)
1 Two Types of Statistical Inference: Estimation and Testing
236(2)
2 Point Estimation of a Population Mean
238(4)
3 Confidence Interval Estimation of a Population Mean
242(8)
4 Testing Hypotheses About a Population Mean
250(11)
5 Inferences About a Population Proportion
261(17)
9 Small Sample Inferences for Normal Populations
278(25)
1 Student's t Distribution
279(3)
2 Inferences About μ---Small Sample Size
282(7)
3 Relationship Between Tests and Confidence Intervals
289(2)
4 Inferences About the Standard Deviation σ (The Chi-Square Distribution)
291(5)
5 Robustness of Inference Procedures
296(7)
10 Comparing Two Treatments
303(46)
1 Two Designs: Independent Samples and Matched Pairs Sample
305(2)
2 Inferences About the Difference of Means---Independent Large Samples
307(7)
3 Inferences About the Difference of Means---Independent Small Samples from Normal Populations
314(9)
4 Randomization and Its Role in Inference
323(2)
5 Matched Pairs Comparisons
325(7)
6 Choosing Between Independent Samples and a Matched Pairs Sample
332(1)
7 Comparing Two Population Proportions
333(16)
11 Regression Analysis I Simple Linear Regression
349(35)
1 Regression with a Single Predictor
350(3)
2 A Straight Line Regression Model
353(2)
3 The Method of Least Squares
355(7)
4 The Sampling Variability of the Least Squares Estimators---Tools for Inference
362(1)
5 Important Inference Problems
363(10)
6 The Strength of a Linear Relation
373(4)
7 Remarks About the Straight Line Model Assumptions
377(7)
12 Regression Analysis II Multiple Linear Regression and Other Topics
384(24)
1 Nonlinear Relations and Linearizing Transformations
385(5)
2 Multiple Linear Regression
390(8)
3 Residual Plots to Check the Adequacy of a Statistical Model
398(10)
13 Analysis of Categorical Data
408(24)
1 Formulating Testing Problems Concerning Categorical Data
409(2)
2 Pearson's Χ2 Test for Goodness of Fit
411(4)
3 Contingency Table with One Margin Fixed (Test of Homogeneity)
415(7)
4 Contingency Table with Neither Margin Fixed (Test of Independence)
422(10)
14 Analysis of Variance (Anova)
432(28)
1 Comparison of Several Treatments---One-Way Analysis of Variance
433(6)
2 Population Model and Inferences for a One-Way Analysis of Variance
439(4)
3 Simultaneous Confidence Intervals
443(3)
4 Graphical Diagnostics and Displays to Supplement ANOVA
446(2)
5 Randomized Block Experiments for Comparing k Treatments
448(12)
15 Nonparametric Inference
460(23)
1 The Wilcoxon Rank-Sum Test for Comparing Two Treatments
461(8)
2 Matched Pairs Comparisons
469(6)
3 Measure of Correlation Based on Ranks
475(3)
4 Concluding Remarks
478(5)
Appendix A1 Summation Notation 483(5)
Appendix A2 Rules for Counting 488(2)
Appendix A3 Expectation and Standard Deviation---Properties 490(6)
Appendix A4 The Expected Value and Standard Deviation of X 496(2)
Appendix B Tables 498(1)
Table 1 Random Digits 498(3)
Table 2 Cumulative Binomial Probabilities 501(6)
Table 3 Cumulative Poisson Probabilities 507(2)
Table 4 Standard Normal Probabilities p[ x ≤ c] = Σcx=0 e-m mx/x! 509(2)
Table 5 Percentage Points ta of t Distributions 511(1)
Table 6 Percentage Points Χ2α of Χ2 Distributions 512(1)
Table 7 Percentage Points of F(v1, v2) Distributions 513(2)
Table 8 Selected Tail Probabilities for the Null Distribution of Wilcoxon's Rank-Sum Statistic 515(5)
Table 9 Selected Tail Probabilities for the Null Distribution of Wilcoxon's Signed-Rank Statistic 520(2)
Table F1 General Formulas for Inferences about a Mean (μ), Difference of Two Means (μ1 - μ2) 522(1)
Table F2 Inference About Proportions 523(1)
Summary of Formulas Useful for Exams 524(6)
Data Bank 530(14)
Answers to Selected Odd-Numbered Exercises 544(13)
Index 557