1. Regression analysis by example [2012]
- Book
- xv, 393 pages : illustrations ; 27 cm.
- Simple linear regression
- Multiple linear regression
- Regression diagnostics : detection of model violations
- Qualitative variables as predictors
- Transformation of variables
- Weighted least squares
- The problem of correlated errors
- Analysis of collinear data
- Working with collinear data
- Variable selection procedures
- Logistic regression
- Further topics.
(source: Nielsen Book Data)9780470905845 20160619
- Simple linear regression
- Multiple linear regression
- Regression diagnostics : detection of model violations
- Qualitative variables as predictors
- Transformation of variables
- Weighted least squares
- The problem of correlated errors
- Analysis of collinear data
- Working with collinear data
- Variable selection procedures
- Logistic regression
- Further topics.
(source: Nielsen Book Data)9780470905845 20160619
Law Library (Crown)
Law Library (Crown) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA278.2 .C5 2012 | Unknown 2-hour loan |
LAW-362-01
- Course
- LAW-362-01 -- Foundations Of Statistical Inference
- Instructor(s)
- Strnad, James Frank
2. Bayesian statistical modelling [2006]
- Book
- xi, 573 p. : ill. ; 25 cm.
- Preface.Chapter 1 Introduction: The Bayesian Method, its Benefits and Implementation.Chapter 2 Bayesian Model Choice, Comparison and Checking.Chapter 3 The Major Densities and their Application.Chapter 4 Normal Linear Regression, General Linear Models and Log-Linear Models.Chapter 5 Hierarchical Priors for Pooling Strength and Overdispersed Regression Modelling.Chapter 6 Discrete Mixture Priors.Chapter 7 Multinomial and Ordinal Regression Models.Chapter 8 Time Series Models.Chapter 9 Modelling Spatial Dependencies.Chapter 10 Nonlinear and Nonparametric Regression.Chapter 11 Multilevel and Panel Data Models.Chapter 12 Latent Variable and Structural Equation Models for Multivariate Data.Chapter 13 Survival and Event History Analysis.Chapter 14 Missing Data Models.Chapter 15 Measurement Error, Seemingly Unrelated Regressions, and Simultaneous Equations.Appendix 1 A Brief Guide to Using WINBUGS.Index.
- (source: Nielsen Book Data)9780470018750 20160528
(source: Nielsen Book Data)9780470018750 20160528
- Preface.Chapter 1 Introduction: The Bayesian Method, its Benefits and Implementation.Chapter 2 Bayesian Model Choice, Comparison and Checking.Chapter 3 The Major Densities and their Application.Chapter 4 Normal Linear Regression, General Linear Models and Log-Linear Models.Chapter 5 Hierarchical Priors for Pooling Strength and Overdispersed Regression Modelling.Chapter 6 Discrete Mixture Priors.Chapter 7 Multinomial and Ordinal Regression Models.Chapter 8 Time Series Models.Chapter 9 Modelling Spatial Dependencies.Chapter 10 Nonlinear and Nonparametric Regression.Chapter 11 Multilevel and Panel Data Models.Chapter 12 Latent Variable and Structural Equation Models for Multivariate Data.Chapter 13 Survival and Event History Analysis.Chapter 14 Missing Data Models.Chapter 15 Measurement Error, Seemingly Unrelated Regressions, and Simultaneous Equations.Appendix 1 A Brief Guide to Using WINBUGS.Index.
- (source: Nielsen Book Data)9780470018750 20160528
(source: Nielsen Book Data)9780470018750 20160528
Law Library (Crown)
Law Library (Crown) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA279.5 .C65 2006 | Unknown 2-hour loan |
LAW-362-01
- Course
- LAW-362-01 -- Foundations Of Statistical Inference
- Instructor(s)
- Strnad, James Frank
3. Mastering MATLAB 7 [2005]
- Book
- xi, 852 p. : ill. ; 24 cm.
- 1. Getting Started. 2. Basic Features. 3. The MATLAB Desktop. 4. Script M-Files. 5. Arrays and Array Operations. 6. Multidimensional Arrays. 7. Cell Arrays and Structures. 8. Character Strings. 9. Relational and Logical Operations. 10. Control Flow. 11. Function M-Files. 12. M-File Debugging and Profiling. 13. File and Directory Management. 14. Set, Bit, and Base Functions. 15. Time Computations. 16. Matrix Algebra. 17. Data Analysis. 18. Data Interpolation. 19. Polynomials. 20. Cubic Splines. 21. Fourier Analysis. 22. Optimization. 23. Integration and Differentiation. 24. Differential Equations. 25. Two-Dimensional Graphics. 26. Three-Dimensional Graphics. 27. Using Color and Light. 28. Images, Movies, and Sound. 29. Printing and Exporting Graphics. 30. Handle Graphics. 31. Graphical User Interfaces. 32. Dialog Boxes. 33. MATLAB Classes and Object-Oriented Programming. 34. MATLAB Programming Interfaces. 35. Extending MATLAB with Java. 36. Windows Application Integration. 37. Getting Help. 38. Examples, Examples, Examples. Appendix A: Common Handle Graphics Properties. Appendix B: Axes Object Properties. Appendix C: Figure Object Properties. Appendix D: Image Object Properties. Appendix E: Light Object Properties. Appendix F: Line Object Properties. Appendix G: Patch Object Properties. Appendix H: Rectangle Object Properties. Appendix I: Root Object Properties. Appendix J: Surface Object Properties. Appendix K: Text Object Properties. Appendix L: Uicontextmenu and Uimenu Object Properties. Appendix M: Uicontrol Object Properties. Index.
- (source: Nielsen Book Data)9780131857148 20160527
(source: Nielsen Book Data)9780131857148 20160527
For undergraduate and graduate courses in MATLAB or as a reference in courses where MATLAB is used. This text covers all essential aspects of MATLAB presented within an easy- to-follow "learn while doing" tutorial format.
(source: Nielsen Book Data)9780131430181 20160527
- 1. Getting Started. 2. Basic Features. 3. The MATLAB Desktop. 4. Script M-Files. 5. Arrays and Array Operations. 6. Multidimensional Arrays. 7. Cell Arrays and Structures. 8. Character Strings. 9. Relational and Logical Operations. 10. Control Flow. 11. Function M-Files. 12. M-File Debugging and Profiling. 13. File and Directory Management. 14. Set, Bit, and Base Functions. 15. Time Computations. 16. Matrix Algebra. 17. Data Analysis. 18. Data Interpolation. 19. Polynomials. 20. Cubic Splines. 21. Fourier Analysis. 22. Optimization. 23. Integration and Differentiation. 24. Differential Equations. 25. Two-Dimensional Graphics. 26. Three-Dimensional Graphics. 27. Using Color and Light. 28. Images, Movies, and Sound. 29. Printing and Exporting Graphics. 30. Handle Graphics. 31. Graphical User Interfaces. 32. Dialog Boxes. 33. MATLAB Classes and Object-Oriented Programming. 34. MATLAB Programming Interfaces. 35. Extending MATLAB with Java. 36. Windows Application Integration. 37. Getting Help. 38. Examples, Examples, Examples. Appendix A: Common Handle Graphics Properties. Appendix B: Axes Object Properties. Appendix C: Figure Object Properties. Appendix D: Image Object Properties. Appendix E: Light Object Properties. Appendix F: Line Object Properties. Appendix G: Patch Object Properties. Appendix H: Rectangle Object Properties. Appendix I: Root Object Properties. Appendix J: Surface Object Properties. Appendix K: Text Object Properties. Appendix L: Uicontextmenu and Uimenu Object Properties. Appendix M: Uicontrol Object Properties. Index.
- (source: Nielsen Book Data)9780131857148 20160527
(source: Nielsen Book Data)9780131857148 20160527
For undergraduate and graduate courses in MATLAB or as a reference in courses where MATLAB is used. This text covers all essential aspects of MATLAB presented within an easy- to-follow "learn while doing" tutorial format.
(source: Nielsen Book Data)9780131430181 20160527
Law Library (Crown)
Law Library (Crown) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA297 .H2963 2005 | Unknown 2-hour loan |
LAW-362-01
- Course
- LAW-362-01 -- Foundations Of Statistical Inference
- Instructor(s)
- Strnad, James Frank
4. MATLAB primer [2005]
- Book
- xii, 215 p. ; 17 cm.
- ACCESSING MATLAB THE MATLAB DESKTOP Help Window Start Button Command Window Workspace Window Command History Window Array Editor Window Current Directory Window MATRICES AND MATRIX OPERATIONS Referencing Individual Entries Matrix Operators Matrix Division (Slash and Backslash) Entry-Wise Operators Relational Operators Complex Numbers Strings Other Data Types SUBMATRICES AND COLON NOTATION Generating Vectors Accessing Submatrices MATLAB FUNCTIONS Constructing Matrices Scalar Functions Vector Functions and Data Analysis Matrix Functions The linsolve Function The find Function CONTROL FLOW STATEMENTS The for Loop The while Loop The switch Statement The try/catch Statement Matrix Expressions (if and while) Infinite Loops M-FILES M-File Editor/Debugger Window Script Files Function Files Multiple Inputs and Outputs Variable Arguments Comments and Documentation MATLAB's Path ADVANCED M-FILE FEATURES Function Handles and Anonymous Functions Name Resolution Error and Warning Messages User Input Performance Measures Efficient Code CALLING C FROM MATLAB A Simple Example C Versus MATLAB Arrays A Matrix Computation in C MATLAB mx and mex Routines Online Help for MEX Routines Larger Examples on the Web CALLING FORTRAN FROM MATLAB Solving a Transposed System A Fortran mexFunction with %val If You Cannot Use %val CALLING JAVA FROM MATLAB A Simple Example Encryption/Decryption MATLAB's Java Class Path Calling Your Own Java Methods Loading a URL as a Matrix TWO-DIMENSIONAL GRAPHICS Planar Plots Multiple Figures Graph of a Function Parametrically Defined Curves Titles, Labels, and Text in a Graph Control of Axes and Scaling Multiple Plots Line Types, Marker Types, Colors Subplots and Specialized Plots Graphics Hard Copy THREE-DIMENSIONAL GRAPHS Curve Plots Mesh and Surface Plots Parametrically Defined Surfaces Volume and Vector Visualization Color Shading and Color Profile Perspective of View ADVANCED GRAPHICS Handle Graphics Graphical User Interface Images SPARSE MATRIX COMPUTATIONS Storage Modes Generating Sparse Matrices Computation with Sparse Matrices Ordering Methods Visualizing Matrices THE SYMBOLIC MATH TOOLBOX Symbolic Variables Calculus Variable Precision Arithmetic Numeric and Symbolic Substitution Algebraic Simplification Two-Dimensional Graphs Three Dimensional Surface Graphs Three-Dimensional Curves Symbolic Matrix Operations Symbolic Linear Algebraic Functions Solving Algebraic Equations Solving Differential Equations Further Maple Access POLYNOMIALS, INTERPOLATION, AND INTEGRATION Representing Polynomials Evaluating Polynomials Polynomial Interpolation Numeric Integration (Quadrature) SOLVING EQUATIONS Symbolic Equations Linear Systems of Equations Polynomial Roots Nonlinear Equations Ordinary Differential Equations Other Differential Equations DISPLAYING RESULTS CELL PUBLISHING CODE DEVELOPMENT TOOLS M-Lint Code Check Report TODO/FIXME Report Help Report Report Dependency Report File Comparison Report Profile and Coverage Report HELP TOPICS General Purpose Commands Operators and Special Characters Programming Language Constructs Elementary Matrices and Matrix Manipulation Elementary Math Functions Specialized Math Functions Matrix Functions-Numerical Linear Algebra Data Analysis, Fourier Transforms Interpolation and Polynomials Function Functions and ODEs Sparse Matrices Annotation and Plot Editing Two-Dimensional Graphs Three-Dimensional Graphs Specialized Graphs Handle Graphics Graphical User Interface Tools Character Strings Image and Scientific Data File Input/Output Audio and Video Support Time and Dates Data Types and Structures Version Control Creating and Debugging Code Help Commands Microsoft Windows Functions Examples and Demonstrations Preferences Symbolic Math Toolbox ADDITIONAL RESOURCES INDEX.
- (source: Nielsen Book Data)9781584885238 20160528
(source: Nielsen Book Data)9781584885238 20160528
- ACCESSING MATLAB THE MATLAB DESKTOP Help Window Start Button Command Window Workspace Window Command History Window Array Editor Window Current Directory Window MATRICES AND MATRIX OPERATIONS Referencing Individual Entries Matrix Operators Matrix Division (Slash and Backslash) Entry-Wise Operators Relational Operators Complex Numbers Strings Other Data Types SUBMATRICES AND COLON NOTATION Generating Vectors Accessing Submatrices MATLAB FUNCTIONS Constructing Matrices Scalar Functions Vector Functions and Data Analysis Matrix Functions The linsolve Function The find Function CONTROL FLOW STATEMENTS The for Loop The while Loop The switch Statement The try/catch Statement Matrix Expressions (if and while) Infinite Loops M-FILES M-File Editor/Debugger Window Script Files Function Files Multiple Inputs and Outputs Variable Arguments Comments and Documentation MATLAB's Path ADVANCED M-FILE FEATURES Function Handles and Anonymous Functions Name Resolution Error and Warning Messages User Input Performance Measures Efficient Code CALLING C FROM MATLAB A Simple Example C Versus MATLAB Arrays A Matrix Computation in C MATLAB mx and mex Routines Online Help for MEX Routines Larger Examples on the Web CALLING FORTRAN FROM MATLAB Solving a Transposed System A Fortran mexFunction with %val If You Cannot Use %val CALLING JAVA FROM MATLAB A Simple Example Encryption/Decryption MATLAB's Java Class Path Calling Your Own Java Methods Loading a URL as a Matrix TWO-DIMENSIONAL GRAPHICS Planar Plots Multiple Figures Graph of a Function Parametrically Defined Curves Titles, Labels, and Text in a Graph Control of Axes and Scaling Multiple Plots Line Types, Marker Types, Colors Subplots and Specialized Plots Graphics Hard Copy THREE-DIMENSIONAL GRAPHS Curve Plots Mesh and Surface Plots Parametrically Defined Surfaces Volume and Vector Visualization Color Shading and Color Profile Perspective of View ADVANCED GRAPHICS Handle Graphics Graphical User Interface Images SPARSE MATRIX COMPUTATIONS Storage Modes Generating Sparse Matrices Computation with Sparse Matrices Ordering Methods Visualizing Matrices THE SYMBOLIC MATH TOOLBOX Symbolic Variables Calculus Variable Precision Arithmetic Numeric and Symbolic Substitution Algebraic Simplification Two-Dimensional Graphs Three Dimensional Surface Graphs Three-Dimensional Curves Symbolic Matrix Operations Symbolic Linear Algebraic Functions Solving Algebraic Equations Solving Differential Equations Further Maple Access POLYNOMIALS, INTERPOLATION, AND INTEGRATION Representing Polynomials Evaluating Polynomials Polynomial Interpolation Numeric Integration (Quadrature) SOLVING EQUATIONS Symbolic Equations Linear Systems of Equations Polynomial Roots Nonlinear Equations Ordinary Differential Equations Other Differential Equations DISPLAYING RESULTS CELL PUBLISHING CODE DEVELOPMENT TOOLS M-Lint Code Check Report TODO/FIXME Report Help Report Report Dependency Report File Comparison Report Profile and Coverage Report HELP TOPICS General Purpose Commands Operators and Special Characters Programming Language Constructs Elementary Matrices and Matrix Manipulation Elementary Math Functions Specialized Math Functions Matrix Functions-Numerical Linear Algebra Data Analysis, Fourier Transforms Interpolation and Polynomials Function Functions and ODEs Sparse Matrices Annotation and Plot Editing Two-Dimensional Graphs Three-Dimensional Graphs Specialized Graphs Handle Graphics Graphical User Interface Tools Character Strings Image and Scientific Data File Input/Output Audio and Video Support Time and Dates Data Types and Structures Version Control Creating and Debugging Code Help Commands Microsoft Windows Functions Examples and Demonstrations Preferences Symbolic Math Toolbox ADDITIONAL RESOURCES INDEX.
- (source: Nielsen Book Data)9781584885238 20160528
(source: Nielsen Book Data)9781584885238 20160528
Law Library (Crown)
Law Library (Crown) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA297 .D38 2005 | Unknown 2-hour loan |
LAW-362-01
- Course
- LAW-362-01 -- Foundations Of Statistical Inference
- Instructor(s)
- Strnad, James Frank
5. Bayesian statistics : an introduction [2004]
- Book
- xv, 351 p. : ill. ; 24 cm.
- 1. Preliminaries. 2. Bayesian inference for the Normal Distribution. 3. Some other common distributions. 4. Hypothesis testing. 5. Two-sample problems. 6. Correlation, regression and ANOVA. 7. Other topics. 8. Hierarchical models. 9. The Gibbs sampler. Common statistical distributions. Tables. R programs. Further reading. References. Index.
- (source: Nielsen Book Data)9780340814055 20160528
(source: Nielsen Book Data)9780340814055 20160528
- 1. Preliminaries. 2. Bayesian inference for the Normal Distribution. 3. Some other common distributions. 4. Hypothesis testing. 5. Two-sample problems. 6. Correlation, regression and ANOVA. 7. Other topics. 8. Hierarchical models. 9. The Gibbs sampler. Common statistical distributions. Tables. R programs. Further reading. References. Index.
- (source: Nielsen Book Data)9780340814055 20160528
(source: Nielsen Book Data)9780340814055 20160528
Law Library (Crown)
Law Library (Crown) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA279.5 .L44 2004 | Unknown 2-hour loan |
LAW-362-01
- Course
- LAW-362-01 -- Foundations Of Statistical Inference
- Instructor(s)
- Strnad, James Frank
6. Introduction to mathematical statistics [2004]
- Book
- xiii, 704 p. : ill. ; 25 cm.
- 1. Probability and Distribution. 2. Multivariate Distributions. 3. Some Special Distributions. 4. Unbiasedness, Consistency, and Limiting Distributions. 5. Introduction to Inference. 6. Maximum Likelihood Methods. 7. Sufficiency. 8. Optimal Tests of Hypotheses. 9. Inferences about Normal Models. 10. Nonparametric Statistics. 11. Bayesian Statistics. 12. Comparison of Least Squares and Robust Procedures for Linear Models. Appendix A. Regularity Conditions. Appendix B. R-Functions.
- (source: Nielsen Book Data)9780130085078 20160528
(source: Nielsen Book Data)9780130085078 20160528
- 1. Probability and Distribution. 2. Multivariate Distributions. 3. Some Special Distributions. 4. Unbiasedness, Consistency, and Limiting Distributions. 5. Introduction to Inference. 6. Maximum Likelihood Methods. 7. Sufficiency. 8. Optimal Tests of Hypotheses. 9. Inferences about Normal Models. 10. Nonparametric Statistics. 11. Bayesian Statistics. 12. Comparison of Least Squares and Robust Procedures for Linear Models. Appendix A. Regularity Conditions. Appendix B. R-Functions.
- (source: Nielsen Book Data)9780130085078 20160528
(source: Nielsen Book Data)9780130085078 20160528
Law Library (Crown)
Law Library (Crown) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA276 .H59 2004 | Unknown 2-hour loan |
LAW-362-01
- Course
- LAW-362-01 -- Foundations Of Statistical Inference
- Instructor(s)
- Strnad, James Frank
- Book
- xiii, 480 p. : ill. ; 25 cm.
- The Bayesian method-- inference and decisions-- general principles and theory-- subjective probability-- non-subjective theories-- prior distributions-- model comparison-- robustness and model criticism-- computation-- Marcov Chain Monte Carlo-- the linear model-- generalized linear models-- nonparametric models-- other standard models-- short case studies.
- (source: Nielsen Book Data)9780340807521 20160528
(source: Nielsen Book Data)9780340807521 20160528
- The Bayesian method-- inference and decisions-- general principles and theory-- subjective probability-- non-subjective theories-- prior distributions-- model comparison-- robustness and model criticism-- computation-- Marcov Chain Monte Carlo-- the linear model-- generalized linear models-- nonparametric models-- other standard models-- short case studies.
- (source: Nielsen Book Data)9780340807521 20160528
(source: Nielsen Book Data)9780340807521 20160528
Law Library (Crown)
Law Library (Crown) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA279.5 .O35 2004 | Unknown 2-hour loan |
QA279.5 .O35 2004 | Unknown 2-hour loan |
LAW-362-01
- Course
- LAW-362-01 -- Foundations Of Statistical Inference
- Instructor(s)
- Strnad, James Frank
8. Applied Bayesian modelling [2003]
- Book
- xii, 457 p. : ill. ; 25 cm.
- Preface. The Basis for, and Advantages of, Bayesian Model Estimation via Repeated Sampling. Hierarchical Mixture Models. Regression Models. Analysis of Multi Level Data. Models for Time Series. Analysis of Panel Data. Models for Spatial Outcomes and Geographical Association. Structural Equation and Latent Variable Models. Survival and Event History Models. Modelling and Establishing Causal Relations: Epidemiological Methods and Models. Index.
- (source: Nielsen Book Data)9780471486954 20160528
(source: Nielsen Book Data)9780471486954 20160528
- Preface. The Basis for, and Advantages of, Bayesian Model Estimation via Repeated Sampling. Hierarchical Mixture Models. Regression Models. Analysis of Multi Level Data. Models for Time Series. Analysis of Panel Data. Models for Spatial Outcomes and Geographical Association. Structural Equation and Latent Variable Models. Survival and Event History Models. Modelling and Establishing Causal Relations: Epidemiological Methods and Models. Index.
- (source: Nielsen Book Data)9780471486954 20160528
(source: Nielsen Book Data)9780471486954 20160528
Law Library (Crown)
Law Library (Crown) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA279.5 .C649 2003 | Unknown 2-hour loan |
LAW-362-01
- Course
- LAW-362-01 -- Foundations Of Statistical Inference
- Instructor(s)
- Strnad, James Frank
- Book
- xx, 459 p. : ill. ; 25 cm.
- Background and Introduction. Likelihood Inference and the Generalized Linear Model. The Bayesian Setup. The Normal and Student's-T Models. The Bayesian Prior. Assessing Model Quality. Bayesian Hypothesis Testing and the Bayes Factor. Bayesian Posterior Simulation. Basics of Markov Chain Monte Carlo. Bayesian Hierarchical Models. Practical Markov Chain Monte Carlo.
- (source: Nielsen Book Data)9781584882886 20160527
(source: Nielsen Book Data)9781584882886 20160527
- Background and Introduction. Likelihood Inference and the Generalized Linear Model. The Bayesian Setup. The Normal and Student's-T Models. The Bayesian Prior. Assessing Model Quality. Bayesian Hypothesis Testing and the Bayes Factor. Bayesian Posterior Simulation. Basics of Markov Chain Monte Carlo. Bayesian Hierarchical Models. Practical Markov Chain Monte Carlo.
- (source: Nielsen Book Data)9781584882886 20160527
(source: Nielsen Book Data)9781584882886 20160527
Law Library (Crown)
Law Library (Crown) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA279.5 .G55 2002 | Unknown 2-hour loan |
LAW-362-01
- Course
- LAW-362-01 -- Foundations Of Statistical Inference
- Instructor(s)
- Strnad, James Frank
- Book
- viii, 310 p. : ill. ; 25 cm.
At the beginning of the twentieth century, H. G. Wells predicted that statistical thinking would be as necessary for citizenship in a technological world as the ability to read and write. But in the twenty-first century, we are often overwhelmed by a baffling array of percentages and probabilities as we try to navigate in a world dominated by statistics. Cognitive scientist Gerd Gigerenzer says that because we haven't learned statistical thinking, we don't understand risk and uncertainty. In order to assess risk -- everything from the risk of an automobile accident to the certainty or uncertainty of some common medical screening tests -- we need a basic understanding of statistics. Astonishingly, doctors and lawyers don't understand risk any better than anyone else. Gigerenzer reports a study in which doctors were told the results of breast cancer screenings and then were asked to explain the risks of contracting breast cancer to a woman who received a positive result from a screening. The actual risk was small because the test gives many false positives. But nearly every physician in the study overstated the risk. Yet many people will have to make important health decisions based on such information and the interpretation of that information by their doctors. Gigerenzer explains that a major obstacle to our understanding of numbers is that we live with an illusion of certainty. Many of us believe that HIV tests, DNA fingerprinting, and the growing number of genetic tests are absolutely certain. But even DNA evidence can produce spurious matches. We cling to our illusion of certainty because the medical industry, insurance companies, investment advisers, and electioncampaigns have become purveyors of certainty, marketing it like a commodity. To avoid confusion, says Gigerenzer, we should rely on more understandable representations of risk, such as absolute risks. For example, it is said that a mammography screening reduces the risk of breast cancer by 25 percent. But in absolute risks, that means that out of every 1,000 women who do not participate in screening, 4 will die; while out of 1,000 women who do, 3 will die. A 25 percent risk reduction sounds much more significant than a benefit that 1 out of 1,000 women will reap. This eye-opening book explains how we can overcome our ignorance of numbers and better understand the risks we may be taking with our money, our health, and our lives.
(source: Nielsen Book Data)9780743205566 20160605
(source: Nielsen Book Data)9780743205566 20160605
At the beginning of the twentieth century, H. G. Wells predicted that statistical thinking would be as necessary for citizenship in a technological world as the ability to read and write. But in the twenty-first century, we are often overwhelmed by a baffling array of percentages and probabilities as we try to navigate in a world dominated by statistics. Cognitive scientist Gerd Gigerenzer says that because we haven't learned statistical thinking, we don't understand risk and uncertainty. In order to assess risk -- everything from the risk of an automobile accident to the certainty or uncertainty of some common medical screening tests -- we need a basic understanding of statistics. Astonishingly, doctors and lawyers don't understand risk any better than anyone else. Gigerenzer reports a study in which doctors were told the results of breast cancer screenings and then were asked to explain the risks of contracting breast cancer to a woman who received a positive result from a screening. The actual risk was small because the test gives many false positives. But nearly every physician in the study overstated the risk. Yet many people will have to make important health decisions based on such information and the interpretation of that information by their doctors. Gigerenzer explains that a major obstacle to our understanding of numbers is that we live with an illusion of certainty. Many of us believe that HIV tests, DNA fingerprinting, and the growing number of genetic tests are absolutely certain. But even DNA evidence can produce spurious matches. We cling to our illusion of certainty because the medical industry, insurance companies, investment advisers, and electioncampaigns have become purveyors of certainty, marketing it like a commodity. To avoid confusion, says Gigerenzer, we should rely on more understandable representations of risk, such as absolute risks. For example, it is said that a mammography screening reduces the risk of breast cancer by 25 percent. But in absolute risks, that means that out of every 1,000 women who do not participate in screening, 4 will die; while out of 1,000 women who do, 3 will die. A 25 percent risk reduction sounds much more significant than a benefit that 1 out of 1,000 women will reap. This eye-opening book explains how we can overcome our ignorance of numbers and better understand the risks we may be taking with our money, our health, and our lives.
(source: Nielsen Book Data)9780743205566 20160605
(source: Nielsen Book Data)9780743205566 20160605
Law Library (Crown)
Law Library (Crown) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA273.15 .G54 2002 | Unknown 2-hour loan |
QA273.15 .G54 2002 | Unknown 2-hour loan |
LAW-362-01
- Course
- LAW-362-01 -- Foundations Of Statistical Inference
- Instructor(s)
- Strnad, James Frank
- Book
- xii, 180 p. : ill. ; 24 cm.
- Introduction The Need for Analysis of Variance (ANOVA) Means, Variances, Sums of Squares and Degrees of Freedom Independent Group ANOVAs One-Factor Independent Groups ANOVA Multiple Comparisons: Independent Groups t-Tests Two-Factor Independent Groups ANOVA Repeated Measures ANOVAs One-Factor Repeated Measures ANOVA Multiple Comparisons: Dependent Measures t-Tests Two-Factor Mixed Measures ANOVA Two-Factor Repeated Measures ANOVA Overview and Final Thoughts Some Tips for Tests on ANOVA Every Day Benefits of a Feel for Statistics and for Evaluating Data.
- (source: Nielsen Book Data)9780803970755 20160618
(source: Nielsen Book Data)9780803970755 20160618
- Introduction The Need for Analysis of Variance (ANOVA) Means, Variances, Sums of Squares and Degrees of Freedom Independent Group ANOVAs One-Factor Independent Groups ANOVA Multiple Comparisons: Independent Groups t-Tests Two-Factor Independent Groups ANOVA Repeated Measures ANOVAs One-Factor Repeated Measures ANOVA Multiple Comparisons: Dependent Measures t-Tests Two-Factor Mixed Measures ANOVA Two-Factor Repeated Measures ANOVA Overview and Final Thoughts Some Tips for Tests on ANOVA Every Day Benefits of a Feel for Statistics and for Evaluating Data.
- (source: Nielsen Book Data)9780803970755 20160618
(source: Nielsen Book Data)9780803970755 20160618
Law Library (Crown)
Law Library (Crown) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA279 .T86 2001 | Unknown 2-hour loan |
LAW-362-01
- Course
- LAW-362-01 -- Foundations Of Statistical Inference
- Instructor(s)
- Strnad, James Frank
- Book
- xvii, 419 p. : ill., maps ; 24 cm.
- Approaches for Statistical Inference. The Bayes Approach. The Empirical Bayes Approach. Performance of Bayes Procedures. Bayesian Computation. Model Criticism and Selection. Special Methods and Models. Case Studies. Appendices.
- (source: Nielsen Book Data)9781584881704 20160528
(source: Nielsen Book Data)9781584881704 20160528
- Approaches for Statistical Inference. The Bayes Approach. The Empirical Bayes Approach. Performance of Bayes Procedures. Bayesian Computation. Model Criticism and Selection. Special Methods and Models. Case Studies. Appendices.
- (source: Nielsen Book Data)9781584881704 20160528
(source: Nielsen Book Data)9781584881704 20160528
Law Library (Crown)
Law Library (Crown) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA279.5 .C36 2000 | Unknown 2-hour loan |
LAW-362-01
- Course
- LAW-362-01 -- Foundations Of Statistical Inference
- Instructor(s)
- Strnad, James Frank
13. Time series analysis [1994]
- Book
- xiv, 799 p. : ill. ; 26 cm.
- Preface Difference Equations 2Lag Operators 3Stationary ARMA Processes 4Forecasting 5Maximum Likelihood Estimation 6Spectral Analysis 7Asymptotic Distribution Theory 8Linear Regression Models 9Linear Systems of Simultaneous Equations 10Covariance-Stationary Vector Processes 11Vector Autoregressions 12Bayesian Analysis 13The Kalman Filter 14Generalized Method of Moments 15Models of Nonstationary Time Series 16Processes with Deterministic Time Trends 17Univariate Processes with Unit Roots 18Unit Roots in Multivariate Time Series 19Cointegration 20Full-Information Maximum Likelihood Analysis of Cointegrated Systems 21Time Series Models of Heteroskedasticity 22Modeling Time Series with Changes in Regime A Mathematical Review B Statistical Tables C Answers to Selected Exercises D Greek Letters and Mathematical Symbols Used in the Text Author Index Subject Index.
- (source: Nielsen Book Data)9780691042893 20160528
(source: Nielsen Book Data)9780691042893 20160528
- Preface Difference Equations 2Lag Operators 3Stationary ARMA Processes 4Forecasting 5Maximum Likelihood Estimation 6Spectral Analysis 7Asymptotic Distribution Theory 8Linear Regression Models 9Linear Systems of Simultaneous Equations 10Covariance-Stationary Vector Processes 11Vector Autoregressions 12Bayesian Analysis 13The Kalman Filter 14Generalized Method of Moments 15Models of Nonstationary Time Series 16Processes with Deterministic Time Trends 17Univariate Processes with Unit Roots 18Unit Roots in Multivariate Time Series 19Cointegration 20Full-Information Maximum Likelihood Analysis of Cointegrated Systems 21Time Series Models of Heteroskedasticity 22Modeling Time Series with Changes in Regime A Mathematical Review B Statistical Tables C Answers to Selected Exercises D Greek Letters and Mathematical Symbols Used in the Text Author Index Subject Index.
- (source: Nielsen Book Data)9780691042893 20160528
(source: Nielsen Book Data)9780691042893 20160528
Law Library (Crown)
Law Library (Crown) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA280 .H264 1994 | Unknown 2-hour loan |
LAW-362-01
- Course
- LAW-362-01 -- Foundations Of Statistical Inference
- Instructor(s)
- Strnad, James Frank
14. The cartoon guide to statistics [1993]
- Book
- 230 p. : ill. ; 24 cm.
Written in the same cartoon format as "The Cartoon History of the Universe" and "The Cartoon Guide to the Computer", this book provides a humorous tour through modern statistics as it is practiced in a wide variety of fields - from the humanities to the sciences. The book begins with a brief history of the subject, then proceeds to cover data analysis, probability and all the other topics crucial to the study of statistics. Other books by Larry Gonick include "The Cartoon Guide to Genetics", "The Cartoon Guide to the United States" and "The Cartoon Guide to Physics".
(source: Nielsen Book Data)9780062731029 20160528
(source: Nielsen Book Data)9780062731029 20160528
Written in the same cartoon format as "The Cartoon History of the Universe" and "The Cartoon Guide to the Computer", this book provides a humorous tour through modern statistics as it is practiced in a wide variety of fields - from the humanities to the sciences. The book begins with a brief history of the subject, then proceeds to cover data analysis, probability and all the other topics crucial to the study of statistics. Other books by Larry Gonick include "The Cartoon Guide to Genetics", "The Cartoon Guide to the United States" and "The Cartoon Guide to Physics".
(source: Nielsen Book Data)9780062731029 20160528
(source: Nielsen Book Data)9780062731029 20160528
Law Library (Crown)
Law Library (Crown) | Status |
---|---|
On reserve: Ask at circulation desk | |
QA276.12 .G67 1993 | Unknown 2-hour loan |
QA276.12 .G67 1993 | Unknown 2-hour loan |
QA276.12 .G67 1993 | Unknown 2-hour loan |
LAW-362-01
- Course
- LAW-362-01 -- Foundations Of Statistical Inference
- Instructor(s)
- Strnad, James Frank