| Description |
1 online resource : illustrations |
| Contents |
Part I: ALGEBRA, PRECALCULUS, AND PROBABILITY; 1. Algebra Review; Numbers; Functions; Exponents; Roots; Logarithms; Summations and Products; Solving Equations and Inequalities; 2. Sets and Functions; Set Notation; Intervals; Venn Diagrams; Functions; Polynomials; 3. Probability; Events and Sample Spaces; Properties and Probability Functions; Counting Theory; Sampling Problems; Conditional Probability; Bayes' Rule; PART II: CALCULUS; 4. Limits and Derivatives; What is a Limit?; Continuity and Asymptotes; Solving Limits; The Number e; Point Estimates and Comparative Statics; Definitions of the Derivative; Notation; Shortcuts for Finding Derivatives; The Chain Rule; 5. Optimization; Terminology; Finding Maxima and Minima; The Newton-Raphson Method; 6 |
|
Integration; Informal Definitions of an Integral; Riemann Sums; Integral Notation; Solving Integrals; Advanced Techniques for Solving Integrals; Probability Density Functions; Moments; 7. Multivariate Calculus; Multivariate Functions; Multivariate Limits; Partial Derivatives; Multiple Integrals; PART III: LINEAR ALGEBRA; 8. Matrix Notation and Arithmetic; Matrix Notation; Types of Matrices; Matrix Arithmetic; Matrix Multiplication; Geometric Representation of Vectors and Transformation Matrices; Elementary Row and Column Operations; 9. Matrix Inverses, Singularity, and Rank; Inverse of a (2 x 2) Matrix; Inverse of a Larger Square Matrix; Multiple Regression and the Ordinary Least Squares (OLS) Estimator; Singularity, Rank, and Linear Dependency; 10 |
|
Linear Systems of Equations and Eigenvalues; Nonsingular Coefficient Matrices; Singular Coefficient Matrices; Homogeneous Systems; Eigenvalues and Eigenvectors; Statistical Measurement Models |
| Summary |
Written for social science students who will be working with or conducting research, Mathematics for Social Scientists offers a non-intimidating approach to learning or reviewing math skills essential in quantitative research methods. The text is designed to build students' confidence by presenting material in a conversational tone and using a wealth of clear and applied examples. Author Jonathan Kropko argues that mastering these concepts will break students' reliance on using basic models in statistical software, allowing them to engage with research data beyond simple software calculations |
| Notes |
Includes index |
| Bibliography |
Includes bibliographical references and index |
| Subject |
Mathematics.
|
|
Social sciences -- Mathematics -- Textbooks
|
|
Mathematics
|
|
Mathematics
|
|
Social sciences -- Mathematics
|
| Genre/Form |
Textbooks
|
| Form |
Electronic book
|
| ISBN |
9781506304236 |
|
1506304230 |
|
9781506304205 |
|
1506304206 |
|
