{"product_id":"mathematics-for-social-scientists-9781506304212","title":"Mathematics for Social Scientists","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eWritten for social science students who will be working with or conducting research, \u003cstrong\u003eMathematics for Social Scientists\u003c\/strong\u003e 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.\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTrade Review\u003c\/b\u003e\u003cbr\u003e\"Students in the social and behavioral sciences increasingly need a solid foundation of mathematical knowledge to be able to contribute to the research literature and be able to keep themselves current on new methodology. Unfortunately, math department classes really are not tailored to their needs. \u003cstrong\u003eMathematics for Social Scientists\u003c\/strong\u003e, on the other hand, is clearly aimed at what students need to be able to advance in subsequent methodology courses and in their future careers. It is written in an inviting and clear manner, without ever sacrificing rigor.\" -- Jay Verkuilen\u003cbr\u003e\"Many students entering higher-level statistics classes have somehow forgotten their basic statistics or were never properly exposed to more than a cookbook explanation. More often than not, a student will leave the course without an understanding of probability, random variables, basic distribution theory and concepts etc. Without some background, it proves difficult for students to catch up with these ideas when they are introduced (or assumed to be known) in more advanced courses. This gap is especially pronounced between those students who were exposed to basic probability in a previous course and those who were not. \u003cstrong\u003eMathematics for Social Scientists \u003c\/strong\u003ewill be a great resource for an instructor wishing to add this content to a basic statistics course as well as for the motivated self-learner.\" -- Dan Powers\u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003ePart I: ALGEBRA, PRECALCULUS, AND PROBABILITY 1. Algebra Review    Numbers    Fractions    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 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","brand":"SAGE Publications Inc","offers":[{"title":"Default Title","offer_id":51863335534935,"sku":"9781506304212","price":104.01,"currency_code":"GBP","in_stock":false}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0817\/1739\/5799\/files\/9781506304212.jpg?v=1759920328","url":"https:\/\/bookcurl.com\/products\/mathematics-for-social-scientists-9781506304212","provider":"Book Curl","version":"1.0","type":"link"}