Introductory statistics + CD
Material type: TextPublication details: UK Addison Wesley 2001Edition: 6th edDescription: 9p., 260 x 222mm, Index, hardbackISBN:- 0201710595
Item type | Current library | Call number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|
Standard Loan | Thurles Library Main Collection | 519.5 WEI (Browse shelf(Opens below)) | Available | R08653KRCT | ||
Standard Loan | Thurles Library Main Collection | 519.5 WEI (Browse shelf(Opens below)) | Available | R08657KRCT | ||
Standard Loan | Thurles Library Main Collection | 519.5 WEI (Browse shelf(Opens below)) | Available | R08658KRCT |
Enhanced descriptions from Syndetics:
Weiss Introductory Statistics is intended for a one- or two-semester introductory statistics course. Students learn the core statistical concepts in an applied setting, and can access more advanced topics (multiple regression, ANOVA, and Experimental Design) through chapters available on the WeissStat CD. With advances in technology and new insights into the practice of teaching statistics, the sixth edition can now easily fit the organization and pace of various course syllabi and technologies in use. The book offers a flexible organization of content and has a more diversified emphasis on using technology such as Minitab, the TI-83 Plus graphing calculator, Excel, and the Internet to investigate statistical problems. *NEW All New Design. We have redesigned the text and now feature a four-color format for improved readability and understanding. *NEW What Does It Mean? This feature, which appears throughout the book, presents the meaning and significance of the statistical results in plain, everyday language and emphasizes the importance of interpretation. *NEW Technology Coverage. Students are introduced to technology at the section level with Minitab, Excel, and the TI-83 Plus
Table of contents provided by Syndetics
- Preface
- Supplements List
- Data Sources
- Part I Introduction
- Chapter 1 The Nature of Statistics
- 1.1 Statistics Basics
- 1.2 Simple Random Sampling
- 1.3 Other Sampling Designs*
- 1.4 Experimental Designs*
- Part II Descriptive Statistics
- Chapter 2 Organizing Data
- 2.1 Variables and Data
- 2.2 Grouping Data
- 2.3 Graphs and Charts
- 2.4 Distribution Shapes
- 2.5 Misleading Graphs
- Chapter 3 Descriptive Measures
- 3.1 Measures of Center
- 3.2 Measures of Variation
- 3.3 The Five-Number Summary
- Boxplots
- 3.4 Descriptive Measures for Populations
- Use of Samples
- Part III Probability, Random Variables, and Sampling Distributions
- Chapter 4 Probability Concepts
- 4.1 Probability Basics
- 4.2 Events
- 4.3 Some Rules of Probability
- 4.4 Contingency Tables
- Joint and Marginal Probabilities*
- 4.5 Conditional Probability*
- 4.6 The Multiplication Rule
- Independence*
- 4.7 Bayes's Rule*
- 4.8 Counting Rules*
- Chapter 5 Discrete Random Variables*
- 5.1 Discrete Random Variables and Probability Distributions*
- 5.2 The Mean and Standard Deviation of a Discrete Random Variable*
- 5.3 The Binomial Distribution*
- 5.4 The Poisson Distribution*
- Chapter 6 The Normal Distribution
- 6.1 Introducing Normally Distributed Variables
- 6.2 Areas Under the Standard Normal Curve
- 6.3 Working with Normally Distributed Variables
- 6.4 Assessing Normality
- Normal Probability Plots
- 6.5 Normal Approximation to the Binomial Distribution*
- Chapter 7 The Sampling Distribution of the Sample Mean
- 7.1 Sampling Error the Need for Sampling Distributions
- 7.2 The Mean and Standard Deviation of the Sample Mean
- 7.3 The Sampling Distribution of the Sample Mean
- Part IV Inferential Statistics
- Chapter 8 Confidence Intervals for One Population Mean
- 8.1 Estimating a Population Mean
- 8.2 Confidence Intervals for One Population Mean When ó is Known
- 8.3 Margin of Error
- 8.4 Confidence Intervals for One Population Mean When ó is Unknown
- Chapter 9 Hypothesis Tests for One Population Mean
- 9.1 The Nature of Hypothesis Testing
- 9.2 Terms, Errors, and Hypotheses
- 9.3 Hypothesis Tests for One Population Mean When ó is Known
- 9.4 Type II Error Probabilities Power*
- 9.5 P-Values
- 9.6 Hypothesis Tests for One Population Mean When ó is Unknown
- 9.7 The Wilcoxon Signed-Rank Test*
- 9.8 Which Procedure Should Be Used?*
- Chapter 10 Inferences for Two Population Means
- 10.1 The Sampling Distribution of the Difference Between Two Sample Means for Independent Samples
- 10.2 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Assumed Equal
- 10.3 Inferences for Two Population Means, Using Independent Samples: Standard Deviations Not Assumed Equal
- 10.4 The MannùWhitney Test*
- 10.5 Inferences for Two Population Means, Using Paired Samples
- 10.6 The Paired Wilcoxon Signed-Rank Test*
- 10.7 Which Procedure Should Be Used?*
- Chapter 11 Inferences for Population Standard Deviations*
- 11.1 Inferences for One Population Standard Deviation*
- 11.2 Inferences for Two Population Standard Deviations, Using Independent Samples*
- Chapter 12 Inferences for Population Proportions
- 12.1 Confidence Intervals for One Population Proportion
- 12.2 Hypothesis Tests for One Population Proportion
- 12.3 Inferences for Two Population Proportions
- Chapter 13 Chi-Square Procedures
- 13.1 The Chi-Square Distribution
- 13.2 Chi-Square Goodness-of-Fit Test
- 13.3 Contingency Tables
- Association
- 13.4 Chi-Square Independence Test
- Part V Regression, Correlation, and ANOVA
- Chapter 14 Descriptive Methods in Regression and Correlation
- 14.1 Linear Equations With One Independent Variable
- 14.2 The Regression Equation
- 14.3 The Coefficient of Determination
- 14.4 Linear Correlation
- Chapter 15 Inferential Methods in Regression and Correlation
- 15.1 The Regression Model
- Analysis of Residuals
- 15.2 Inferences for the Slope of the Population Regression Line
- 15.3 Estimation and Prediction
- 15.4 Inferences in Correlation
- 15.5 Testing for Normality*
- Chapter 16 Analysis of Variance (ANOVA)
- 16.1 The F-Distribution
- 16.2 One-Way ANOVA: The Logic
- 16.3 One-Way ANOVA: The Procedure
- 16.4 Multiple Comparisons*
- 16.5 The KruskalùWallis Test*
- Part VI Multiple Regression and Model Building
- Experimental Design and ANOVA (On The WeissStats CD-ROM)
- Module A Multiple Regression Analysis
- A.1 The Multiple Linear Regression Model
- A.2 Estimation of the Regression Parameters
- A.3 Inferences Concerning the Utility of the Regression Model
- A.4 Inferences Concerning the Utility of Particular Predictor Variables
- A.5 Confidence Intervals for Mean Response Prediction Intervals for Response
- A.6 Checking Model Assumptions and Residual Analysis
- Module B Model Building in Regression
- B.1 Transformations to Remedy Model Violations
- B.2 Polynomial Regression Model
- B.3 Qualitative Predictor Variables
- B.4 Multicollinearity
- B.5 Model Selection: Stepwise Regression
- B.6 Model Selection: All Subsets Regression
- B.7 Pitfalls and Warnings
- Module C Design of Experiments and Analysis of Variance
- C.1 Factorial Designs
- C.2 Two-Way ANOVA: The Logic
- C.3 Two-Way ANOVA: The Procedure
- C.4 Two-Way ANOVA: Multiple Comparisons
- C.5 Randomized Block Designs
- C.6 Randomized Block ANOVA: The Logic
- C.7 Randomized Block ANOVA: The Procedure
- C.8 Randomized Block ANOVA: Multiple Comparisons
- C.9 Friedman's Nonparametric Test for the Randomized Block Design*
- Appendixes
- Appendix A Statistical Tables
- I Random numbers
- II Areas under the standard normal curve
- III Normal scores
- IV Values of tá
- V Values of Wá
- VI Values of Má
- VII Values of և2
- VIII Values of Fá
- IX Critical values for a correlation test for normality
- X Values of q0.01
- XI Values of q0.05
- XII Binomial probabilities
- Appendix B Answers to Selected Exercises
- Index
- Photo Credits
- Indexes for Biographical Sketches
- Case Studies
- indicates an optional section