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The Resource A mathematics course for political and social research, Will H. Moore & David A. Siegel

A mathematics course for political and social research, Will H. Moore & David A. Siegel

Label
A mathematics course for political and social research
Title
A mathematics course for political and social research
Statement of responsibility
Will H. Moore & David A. Siegel
Creator
Contributor
Author
Subject
Genre
Language
eng
Summary
Political science and sociology increasingly rely on mathematical modeling and sophisticated data analysis, and many graduate programs in these fields now require students to take a ""math camp"" or a semester-long or yearlong course to acquire the necessary skills. The problem is that most available textbooks are written for mathematics or economics majors, and fail to convey to students of political science and sociology the reasons for learning often-abstract mathematical concepts. A Mathematics Course for Political and Social Research fills this gap, providing both a primer for m
Cataloging source
IDEBK
http://library.link/vocab/creatorDate
1962-2017
http://library.link/vocab/creatorName
Moore, Will H.
Illustrations
illustrations
Index
index present
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
http://library.link/vocab/relatedWorkOrContributorName
Siegel, David A.
http://library.link/vocab/subjectName
  • Mathematics
  • Mathematics
  • Mathematics
  • MATHEMATICS
  • MATHEMATICS
  • Mathematik
  • Politische Wissenschaft
  • Methodologie
  • Mathematik
  • Political Science, other
  • Political Science
  • Social Sciences
Label
A mathematics course for political and social research, Will H. Moore & David A. Siegel
Instantiates
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • 1.3.
  • 8.4.
  • Two Examples
  • 8.5.
  • Exercises
  • III.
  • Probability
  • 9.
  • Introduction to Probability
  • 9.1.
  • Basic Probability Theory
  • Operators
  • 9.2.
  • Computing Probabilities
  • 9.3.
  • Some Specific Measures of Probabilities
  • 9.4.
  • Exercises
  • 9.5.
  • Appendix
  • 10.
  • Introduction to (Discrete) Distributions
  • 1.4.
  • 10.1.
  • Distribution of a Single Concept (Variable)
  • 10.2.
  • Sample Distributions
  • 10.3.
  • Empirical Joint and Marginal Distributions
  • 10.4.
  • Probability Mass Function
  • 10.5.
  • Cumulative Distribution Function
  • Relations
  • 10.6.
  • Probability Distributions and Statistical Modeling
  • 10.7.
  • Expectations of Random Variables
  • 10.8.
  • Summary
  • 10.9.
  • Exercises
  • 10.10.
  • Appendix
  • 1.5.
  • 11.
  • Continuous Distributions
  • 11.1.
  • Continuous Random Variables
  • 11.2.
  • Expectations of Continuous Random Variables
  • 11.3.
  • Important Continuous Distributions for Statistical Modeling
  • 11.4.
  • Exercises
  • Level of Measurement
  • 11.5.
  • Appendix
  • IV.
  • Linear Algebra
  • 12.
  • Fun with Vectors and Matrices
  • 12.1.
  • Scalars
  • 12.2.
  • Vectors
  • 1.6.
  • 12.3.
  • Matrices
  • 12.4.
  • Properties of Vectors and Matrices
  • 12.5.
  • Matrix Illustration of OLS Estimation
  • 12.6.
  • Exercises
  • 13.
  • Vector Spaces and Systems of Equations
  • Notation
  • 13.1.
  • Vector Spaces
  • 13.2.
  • Solving Systems of Equations
  • 13.3.
  • Why Should I Care?
  • 13.4.
  • Exercises
  • 13.5.
  • Appendix
  • 1.7.
  • 14.
  • Eigenvalues and Markov Chains
  • 14.1.
  • Eigenvalues, Eigenvectors, and Matrix Decomposition
  • 14.2.
  • Markov Chains and Stochastic Processes
  • 14.3.
  • Exercises
  • V.
  • Multivariate Calculus and Optimization
  • Proofs, or How Do We Know This?
  • 15.
  • Multivariate Calculus
  • 15.1.
  • Functions of Several Variables
  • 15.2.
  • Calculus in Several Dimensions
  • 15.3.
  • Concavity and Convexity Redux
  • 15.4.
  • Why Should I Care?
  • I.
  • 1.8.
  • 15.5.
  • Exercises
  • 16.
  • Multivariate Optimization
  • 16.1.
  • Unconstrained Optimization
  • 16.2.
  • Constrained Optimization: Equality Constraints
  • 16.3.
  • Constrained Optimization: Inequality Constraints
  • Exercises
  • 16.4.
  • Exercises
  • 17.
  • Comparative Statics and Implicit Differentiation
  • 17.1.
  • Properties of the Maximum and Minimum
  • 17.2.
  • Implicit Differentiation
  • 17.3.
  • Exercises
  • 2.
  • Algebra Review
  • 2.1.
  • Basic Properties of Arithmetic
  • 2.2.
  • Algebra Review
  • 2.3.
  • Computational Aids
  • Building Blocks
  • 2.4.
  • Exercises
  • 3.
  • Functions, Relations, and Utility
  • 3.1.
  • Functions
  • 3.2.
  • Examples of Functions of One Variable
  • 3.3.
  • Preference Relations and Utility Functions
  • 1.
  • 3.4.
  • Exercises
  • 4.
  • Limits and Continuity, Sequences and Series, and More on Sets
  • 4.1.
  • Sequences and Series
  • 4.2.
  • Limits
  • 4.3.
  • Open, Closed, Compact, and Convex Sets
  • Preliminaries
  • 4.4.
  • Continuous Functions
  • 4.5.
  • Exercises
  • II.
  • Calculus in One Dimension
  • 5.
  • Introduction to Calculus and the Derivative
  • 5.1.
  • Brief Introduction to Calculus
  • 1.1.
  • 5.2.
  • What Is the Derivative?
  • 5.3.
  • Derivative, Formally
  • 5.4.
  • Summary
  • 5.5.
  • Exercises
  • 6.
  • Rules of Differentiation
  • Variables and Constants
  • 6.1.
  • Rules for Differentiation
  • 6.2.
  • Derivatives of Functions
  • 6.3.
  • What the Rules Are, and When to Use Them
  • 6.4.
  • Exercises
  • 7.
  • Integral
  • 1.2.
  • 7.1.
  • Definite Integral as a Limit of Sums
  • 7.2.
  • Indefinite Integrals and the Fundamental Theorem of Calculus
  • 7.3.
  • Computing Integrals
  • 7.4.
  • Rules of Integration
  • 7.5.
  • Summary
  • Sets
  • 7.6.
  • Exercises
  • 8.
  • Extrema in One Dimension
  • 8.1.
  • Extrema
  • 8.2.
  • Higher-Order Derivatives, Concavity, and Convexity
  • 8.3.
  • Finding Extrema
Control code
ocn851157136
Dimensions
unknown
Extent
1 online resource (xix, 430 pages)
File format
unknown
Form of item
online
Isbn
9780691159959
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Note
JSTOR
Other physical details
illustrations
http://library.link/vocab/ext/overdrive/overdriveId
22573/ctt2z005n
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)851157136
Label
A mathematics course for political and social research, Will H. Moore & David A. Siegel
Publication
Antecedent source
unknown
Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Content category
text
Content type code
  • txt
Content type MARC source
rdacontent
Contents
  • 1.3.
  • 8.4.
  • Two Examples
  • 8.5.
  • Exercises
  • III.
  • Probability
  • 9.
  • Introduction to Probability
  • 9.1.
  • Basic Probability Theory
  • Operators
  • 9.2.
  • Computing Probabilities
  • 9.3.
  • Some Specific Measures of Probabilities
  • 9.4.
  • Exercises
  • 9.5.
  • Appendix
  • 10.
  • Introduction to (Discrete) Distributions
  • 1.4.
  • 10.1.
  • Distribution of a Single Concept (Variable)
  • 10.2.
  • Sample Distributions
  • 10.3.
  • Empirical Joint and Marginal Distributions
  • 10.4.
  • Probability Mass Function
  • 10.5.
  • Cumulative Distribution Function
  • Relations
  • 10.6.
  • Probability Distributions and Statistical Modeling
  • 10.7.
  • Expectations of Random Variables
  • 10.8.
  • Summary
  • 10.9.
  • Exercises
  • 10.10.
  • Appendix
  • 1.5.
  • 11.
  • Continuous Distributions
  • 11.1.
  • Continuous Random Variables
  • 11.2.
  • Expectations of Continuous Random Variables
  • 11.3.
  • Important Continuous Distributions for Statistical Modeling
  • 11.4.
  • Exercises
  • Level of Measurement
  • 11.5.
  • Appendix
  • IV.
  • Linear Algebra
  • 12.
  • Fun with Vectors and Matrices
  • 12.1.
  • Scalars
  • 12.2.
  • Vectors
  • 1.6.
  • 12.3.
  • Matrices
  • 12.4.
  • Properties of Vectors and Matrices
  • 12.5.
  • Matrix Illustration of OLS Estimation
  • 12.6.
  • Exercises
  • 13.
  • Vector Spaces and Systems of Equations
  • Notation
  • 13.1.
  • Vector Spaces
  • 13.2.
  • Solving Systems of Equations
  • 13.3.
  • Why Should I Care?
  • 13.4.
  • Exercises
  • 13.5.
  • Appendix
  • 1.7.
  • 14.
  • Eigenvalues and Markov Chains
  • 14.1.
  • Eigenvalues, Eigenvectors, and Matrix Decomposition
  • 14.2.
  • Markov Chains and Stochastic Processes
  • 14.3.
  • Exercises
  • V.
  • Multivariate Calculus and Optimization
  • Proofs, or How Do We Know This?
  • 15.
  • Multivariate Calculus
  • 15.1.
  • Functions of Several Variables
  • 15.2.
  • Calculus in Several Dimensions
  • 15.3.
  • Concavity and Convexity Redux
  • 15.4.
  • Why Should I Care?
  • I.
  • 1.8.
  • 15.5.
  • Exercises
  • 16.
  • Multivariate Optimization
  • 16.1.
  • Unconstrained Optimization
  • 16.2.
  • Constrained Optimization: Equality Constraints
  • 16.3.
  • Constrained Optimization: Inequality Constraints
  • Exercises
  • 16.4.
  • Exercises
  • 17.
  • Comparative Statics and Implicit Differentiation
  • 17.1.
  • Properties of the Maximum and Minimum
  • 17.2.
  • Implicit Differentiation
  • 17.3.
  • Exercises
  • 2.
  • Algebra Review
  • 2.1.
  • Basic Properties of Arithmetic
  • 2.2.
  • Algebra Review
  • 2.3.
  • Computational Aids
  • Building Blocks
  • 2.4.
  • Exercises
  • 3.
  • Functions, Relations, and Utility
  • 3.1.
  • Functions
  • 3.2.
  • Examples of Functions of One Variable
  • 3.3.
  • Preference Relations and Utility Functions
  • 1.
  • 3.4.
  • Exercises
  • 4.
  • Limits and Continuity, Sequences and Series, and More on Sets
  • 4.1.
  • Sequences and Series
  • 4.2.
  • Limits
  • 4.3.
  • Open, Closed, Compact, and Convex Sets
  • Preliminaries
  • 4.4.
  • Continuous Functions
  • 4.5.
  • Exercises
  • II.
  • Calculus in One Dimension
  • 5.
  • Introduction to Calculus and the Derivative
  • 5.1.
  • Brief Introduction to Calculus
  • 1.1.
  • 5.2.
  • What Is the Derivative?
  • 5.3.
  • Derivative, Formally
  • 5.4.
  • Summary
  • 5.5.
  • Exercises
  • 6.
  • Rules of Differentiation
  • Variables and Constants
  • 6.1.
  • Rules for Differentiation
  • 6.2.
  • Derivatives of Functions
  • 6.3.
  • What the Rules Are, and When to Use Them
  • 6.4.
  • Exercises
  • 7.
  • Integral
  • 1.2.
  • 7.1.
  • Definite Integral as a Limit of Sums
  • 7.2.
  • Indefinite Integrals and the Fundamental Theorem of Calculus
  • 7.3.
  • Computing Integrals
  • 7.4.
  • Rules of Integration
  • 7.5.
  • Summary
  • Sets
  • 7.6.
  • Exercises
  • 8.
  • Extrema in One Dimension
  • 8.1.
  • Extrema
  • 8.2.
  • Higher-Order Derivatives, Concavity, and Convexity
  • 8.3.
  • Finding Extrema
Control code
ocn851157136
Dimensions
unknown
Extent
1 online resource (xix, 430 pages)
File format
unknown
Form of item
online
Isbn
9780691159959
Level of compression
unknown
Media category
computer
Media MARC source
rdamedia
Media type code
  • c
Note
JSTOR
Other physical details
illustrations
http://library.link/vocab/ext/overdrive/overdriveId
22573/ctt2z005n
Quality assurance targets
not applicable
Reformatting quality
unknown
Sound
unknown sound
Specific material designation
remote
System control number
(OCoLC)851157136

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      32.771354 -117.193327
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