GRE Quantitative Reasoning - Skills

The Quantitative Reasoning sections of the GRE are intended to evaluate mathematical knowledge and the student's ability to perform complex quantitative analysis in the context of graduate education. Although the skills tested are applicable to a wide range of graduate and professional fields, the GRE has been specifically designed to evaluate achievement and aptitude in Arithmetic, Algebra, Geometry, and Data Analysis. The content in all four skill areas is generally no more sophisticated than a second level course in algebra, and does not include trigonometry, calculus, or higher-level math.

Arithmetic Concepts

Arithmetic concepts tested on the GRE include integers, fractions, exponents and roots, decimals, real numbers, ratios, and percents. In order to solve problems related to these issues, students must understand categories and properties of numbers such as factorability and divisibility, leaset common multiples, greatest common divisors, quotients, remainders, prime numbers, estimation, percent, ratio, rate, and absolute value.

Algebra Concepts

Algebra concepts covered by the GRE include operations with algebraic expressions, rules of exponents, solving linear and quadratic equations, solving linear inequalities, working with functions and applications, coordinate geometry, and graphs of functions. The skillset required for this content includes factoring and simplifying equations, setting up and manipulating mathematical relationships, and analyzing graphical information including slopes and intercepts of lines.

Geometry Concepts

Geometry concepts on the GRE include lines and angles, polygons, triangles, quadrilaterals, circles, and three-dimensional figures. Required skills for these problem types include understanding parallel and perpendicular lines, categories of triangle including isosceles, equilateral, and 30/60/90-degree triangles, the Pythagorean theorem, and properties of three-dimensional figures including area, perimeter, and volume. Students will not be evaluated on their ability to construct or evaluate geometric proofs.

Data Analysis Concepts

GRE Data Analysis concepts include basic descriptive statistics, interpretation of data in tables and graphs, elementary probability, random variables and probability distributions, and counting methods; inferential statistics is not tested.

Test Preparation

ETS offers some of the best public information about the GRE, including detailed descriptions of the different types of problems that will be presented in each section, sample problems, preparation tips, test taking strategies, and comprehensive information about the test's purpose and methodology.

For students who are looking for more targeted review materials, Manhattan Review offers preparation books in specific content area. For Quantitative Reasoning, Manhattan Review offers books in Math Essentials, Number Properties, Arithmetics, Algebra, Geometry, Word Problems, Combinatorics & Probability, and Statistics & Data Interpretation. The complete series is designed to be your best GRE test prep companion as you navigate the road to a successful testing outcome. Students who enroll in Manhattan Review online courses will be given access to the Math Essentials and Cominatorics and Probability guides, as well as a Quantitative Question Bank with over 600 questions, 100 of which have alternate solution approaches provided. For students who understand their strengths and weaknesses, Manhattan Review preparation materials offer an incomparable opportunity to focus on improving your understanding of the concepts that are most difficult for you.

Test Validity

ETS conducts validity studies to ensure that the test is accurately measuring aptitude and knowledge of skills that are important to success in graduate school. Specifically, in the Quantitative Reasoning sections the test is measuring the abilities to read and understand quantitative information, interpret and analyze quantitative information including drawing inferences from data, and using mathematical methods to solve quantitative problems.