Basic Information

The Mathematics Placement Exam is not a pass-fail exam!

The placement exam is online.  You may use any non-graphing calculator on the exam.  The exam has four separately timed parts.  

The placement exam gives a measure of a student's mathematical skills at the time it is taken, and the results are used to advise students on the appropriate mathematics course in which to enroll in order to complete the mathematics requirement for a particular program of study.

The entry-level mathematics courses at UMCP require the permission of the department before students may register.  This is achieved primarily by the results on the Placement exam.  Statistics indicate that the majority of students who enroll in a math course beyond that indicated by the placement exam either withdraw from the course or earn D's or F's.

The entry-level mathematics courses: Math 003, 007, 013, 015, 107, 113, 115, 120, 135, 140, and Stat 100 are placed on a horizontal scale as shown below. Students may register for the course that they place into or any course that is to the left of their placement.

 003   007   013   015   107   113   S100   115   120   135   140

Except for Math 003, 007, 013, 015  any of the courses on the list will serve to satisfy the University's Fundamental Studies Mathematics requirement. Math 003 is a non-credit course which serves as preparation for credit courses, and has a special fee.  Math 007 prepares you for Math 107 and becomes Math 107 after 5 weeks.  The same is true for Math 013 becoming Math 113, and Math 015 becoming Math 115.  These too have a special fee.  Math 107 is an applications course requiring a strong Algebra I background. Math 113 requires a strong Algebra II background and is a preparation for Math 120.  Stat 100 is a noncalculus introduction to probability and statistics. Math 115 is a precalculus course that requires a very strong background in Algebra II and is a preparation for Math 140.  Math 120 is a calculus course for non-science majors.  Math 135 is a calculus course for life science majors.  It too requires a very strong precalculus background like Math 140 obtained by completing Math 115.  Math 140 is a first course in calculus for science and engineering students. 

What happens if a student doesn't place into the course that they need for their course of study? A student may retake the placement exam to improve a placement. However, a student may take the placement exam only once during an academic year semester and is allowed to retake it only once during the summer. Any retake should be preceded by careful review and preparation (see below).

There are also course sequences which will take a student from his/her current mathematical level to the target program of study. There are advisors at orientation to help students plan an appropriate sequence of courses once the placement exam results are available. For instance, suppose a student needs Math 140 for a major but places into Math 107. Since Math 107 is not a preparation for Math 140, the student has several options, including the following: study independently over the summer and retake the placement exam; take Math 003, followed by Math 115 and then Math 140; or take Math 015 and then Math 140. The last type of option, involving the courses Math 007, 013 and 015, is discussed on the Developmental Math Program web page.

How to Prepare for the Exam

The Mathematics Placement Exam consist of 67 questions covering four main areas: arithmetic, algebra I, algebra II, and trigonometry. Topics include: simplification of expressions, exponents, linear equations in one and two variables, slope, systems of equations, inequalities, absolute value, quadratic, cubic, exponential, and logarithmic functions, roots of polynomials, composition of functions, and trigonometric functions.

To prepare for the placement exam, any review of Algebra I and II is helpful.  Other resources are described in the section below on retaking the placement exam.

It is recommended that students take a sample placement exam and review topics when necessary. Only students planning to take Math 140 need to demonstrate knowledge of trigonometry.

Go on to the sample placement exam.

The sample exam is not timed.  The actual exam is.

Preparing to Retake the Math Placement Exam

FACT: You will save at least one semester of taking math by taking the time to do a careful review and placing in a course required for your major.

FACT: Just retaking the Placement Exam is VERY unlikely to place you in your desired math course. Experience has shown that students who do not have a substantial review before retaking the exam seldom change their original placement. A word to the wise ...

REVIEW!         REVIEW!         REVIEW!         REVIEW!

You received four scores from your Placement Exam.

The topics associated with PART I - Arithmetic - are the following:

  • Basic artithmetic oeprations including order of operations
  • Fractions, decimals, percents and ratios
  • Exponents

The topics associated with PART II - Elementary Algebra - are the following:

  • Operations on polynomials, including factoring
  • Linear and quadratic equations in one variable
  • Linear inequalities
  • Systems of first degree equations
  • Functions
  • Graphing of first degree equations, inequalities and functions

Topics associated with PART III - Intermediate Algebra - are all topics in Elementary Algebra plus the following:

  • Absolute value
  • Rational equations
  • Laws of exponents/fractional exponents
  • Formulas - solving for one variable in terms of other variables
  • Composition and inverses of functions
  • Radical expressions/equations
  • Exponential Functions
  • Logarithmic Functions
  • Conic sections

(Mastery of all of the above topics would likely place you into a credited math course.)

Topics from PART IV include the following:

  • Basic Trigonometry
  • Trigonometric Equations
  • Periodic Functions

(Knowledge of these topics is needed for placement in a calculus sequence.)

BOOKS, SOFTWARE, VIDEOS TO USE FOR REVIEW

You have a sense of the topics that you know and the ones that you have forgetten. As you use the following resources, pick the topics you need to review. For example, if you obtain an Elementary or Intermediate Algebra text, go directly to the chapters with the topics you need to review. Similarly, if you use software, videos and web pages you may want to go directly to the portion covering topics you need to review.

You don't need to (and should not try to) use all the resources below. They provide different presentations of the same mathematics, and no matter how many resources you assemble, in the end there is no escaping the work of studying the mathematics. Use what works best for you.

Books:

  • For Elementary Algebra: Schaums Outline Series, College Algebra, Murray, Spiegel and Wagner.
  • For Intermediate Algebra: Schaums Outline Series, College Mathematics, second edition, Ayres and Schmidt.

Check your local library for other elementary and intermediate algebra resources.

Review Courses:

Algebra Brush-up courses may be available at your local high school or community college.

Tutorial web pages:

Search the WEB for Intermediate Algebra Review Material.  Much is free and self-help.  Below are listed just a few. 

The references above are suggestions. A change in your placement will depend primarily on the amount and quality of the review you do.

You may also want to take the sample placement exam

The sample exam is not timed.  The actual exam is.

Taking the Math Placement Exam

The next session of the exam will open on March 12, 2025.

Students needing a retake: email name and UID to to be set up.

Follow the link below to take the Mathematics Placement Exam
go.umd.edu/math-place

Archives: F2011-S2012 F2012-S2013 F2013-S2014 F2014-S2015 F2015-S2016 F2016-S2017 F2017-S2018 F2018-S2019 F2019-S2020 F2021-S2022 F2022-S2023 F2023-S2024 

  • Numerical Analysis for Operator Learning in SciML

    Speaker: Christoph Schwab (ETH Zurich) - https://math.ethz.ch/research/applied-mathematics-numerical-analysis-scientific-computing/christoph-schwab.html

    When: Tue, September 3, 2024 - 3:30pm
    Where: Kirwan Hall 3206
  • Aziz Lecture: Multilevel approximation of Gaussian random fields

    Speaker: Christoph Schwab (ETH Zurich) - https://math.ethz.ch/research/applied-mathematics-numerical-analysis-scientific-computing/christoph-schwab.html

    When: Wed, September 4, 2024 - 3:15pm
    Where: Kirwan Hall 3206
  • Runge-Kutta methods are stable

    Speaker: Eitan Tadmor (University of Maryland) - https://www.math.umd.edu/~tadmor/

    When: Tue, September 10, 2024 - 3:30pm
    Where: Kirwan Hall 3206
  • Weights and applications in numerics

    Speaker: Abner Salgado (University of Tennessee, Knoxville) - https://sites.google.com/utk.edu/abnersg/

    When: Tue, September 17, 2024 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=0f98cef1-69eb-46de-8c5b-b1ee0158fd27
  • Multilevel diffusion: Infinite dimensional score-based diffusion models

    Speaker: Nicole Tianjiao Yang (Emory University) - https://nicoletyang.github.io/

    When: Tue, September 24, 2024 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=434417b2-66a7-4fa5-bef1-b1f5015ed100
  • Numerical schemes for solving the Cahn-Hilliard equation and other energy based systems

    Speaker: Giordano Tierra (University of North Texas) - https://www.math.unt.edu/~gt0141/

    When: Tue, October 1, 2024 - 3:30pm
    Where: Kirwan Hall 3206
  • Nonlocal Attention Operator: Towards an Interpretable Foundation Model for Physical Systems

    Speaker: Yue Yu (Lehigh University) - https://www.lehigh.edu/~yuy214/

    When: Tue, October 8, 2024 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=6eb7ec88-a299-4d1d-b3da-b203015f7839
  • Stochastic-Gradient-based Algorithms for Solving Nonconvex Constrained Optimization Problems

    Speaker: Frank E. Curtis (Industrial and Systems Engineering, Lehigh University) - https://coral.ise.lehigh.edu/frankecurtis/

    When: Tue, October 15, 2024 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=926453eb-5a94-4eab-a948-b20a01565457
  • Multiphysics problems related to brain clearance, sleep and dementia

    Speaker: Kent Mardal (University of Oslo ) - https://kent-and.github.io/

    When: Tue, October 22, 2024 - 3:30pm
    Where: Online
  • AdaBB: A Parameter-Free Gradient Method for Convex Optimization

    Speaker: Shiqian Ma (Rice University) - https://sqma.rice.edu/

    When: Tue, October 29, 2024 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=c0d1241c-6522-4b1a-8bc3-b21801583843
  • Macroscopic Dynamics for Chemical Reactions: Large deviation and Wasserstein diffusion approximation

    Speaker: Yuan Gao (Purdue University) - https://yuangaogao.github.io/

    When: Tue, November 5, 2024 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=5a47c268-2e27-4756-83e5-b21f016ce455
  • Learning a robust shape parameter for radial basis functions approximation with continual learning

    Speaker: Maria Han Vega (Ohio State University) - https://hanveiga.com/

    When: Tue, November 12, 2024 - 7:45am
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=686113c1-afc6-41d1-9234-b226016b1838
  • Canceled

    When: Tue, November 19, 2024 - 3:30pm
    Where: Kirwan Hall 3206
  • Transport information geometric computations

    Speaker: Wuchen Li (University of South Carolina) - https://people.math.sc.edu/wuchen/

    When: Tue, December 3, 2024 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=73c2db92-b497-442d-8408-b23b01759321
  • Quantum Eigenvalue(phase) Estimation: From Quantum Data to Classical Signal Processing

    Speaker: Zhiyan Ding (University of California, Berkeley) - https://math.berkeley.edu/~zding.m/

    When: Thu, December 12, 2024 - 2:00pm
    Where: Kirwan Hall 3206
  • Some progress on low rank methods for time dependent equations

    Speaker: Yingda Cheng (Virginia Tech) - https://yingdacheng.github.io/

    When: Tue, February 4, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=403cf24f-05f9-466b-85aa-b27a01681c5d
  • Optimal Sampling in Least-Squares Methods

    Speaker: Albert Cohen (Sorbonne Université) - https://www.ljll.fr/cohen/

    When: Tue, February 11, 2025 - 3:30pm
    Where: https://umd.zoom.us/j/97661035379?pwd=eW4xR2xFL3paQ3VCTXd6bjNXNlJNUT09
  • Dynamic Generative AI for Uncertainty Quantification

    Speaker: Feng Bao (Florida State University) - https://www.math.fsu.edu/~bao/

    When: Tue, February 25, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=dcea5240-c0b4-4f77-8136-b28f01651d49
  • Computation of origami-inspired structures and mechanical metamaterials

    Speaker: Frederic Marazzato (University of Arizona) - https://sites.google.com/view/marazzaf/home

    When: Tue, March 11, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8796cc66-27e8-42b9-8b36-b29d015a0c76
  • TBA

    Speaker: TBA (TBA) - TBA

    When: Tue, March 25, 2025 - 3:30pm
    Where: Kirwan Hall 3206
  • Discontinuous Galerkin methods for Maxwell’s equations

    Speaker: Peter Monk (University of Delaware) - https://sites.udel.edu/monk/

    When: Tue, April 1, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=33f49515-d74a-4435-95bb-b2b2015a30d4
  • On the Local Linear Convergence of ADMM for Solving SDPs under Strict Complementarity

    Speaker: Heng Yang (Harvard University) - https://hankyang.seas.harvard.edu/

    When: Tue, April 8, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=bf9b52ab-5228-4a5c-a284-b2b9016002e1
  • Data Driven Modeling for Scientific Discovery and Digital Twins

    Speaker: Dongbin Xiu (The Ohio State University) - https://sites.google.com/view/dongbin-xiu

    When: Tue, April 15, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=1ae71f02-8959-4058-ba58-b2c001597272
  • 𝐻² conforming virtual element discretization of nondivergence form elliptic equations

    Speaker: Guillaume Bonnet (Université Paris-Dauphine) - https://www.ceremade.dauphine.fr/~bonnet/

    When: Thu, April 17, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=de71a275-f7f9-4400-998b-b2c70168c62a
  • Quantum signal processing and nonlinear Fourier analysis: a dialogue

    Speaker: Lin Lin (University of California, Berkeley) - https://math.berkeley.edu/~linlin/

    When: Tue, April 22, 2025 - 3:30pm
    Where: https://umd.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=8c974a95-1ae5-45df-95bc-b2c7016768ee
  • Martingale deep learning for very high-dimensional quasi-linear partial differential equations and stochastic optimal controls

    Speaker: Wei Cai (Southern Methodist University) - https://people.smu.edu/cai/

    When: Tue, April 29, 2025 - 3:30pm
    Where: Kirwan Hall 3206
  • Applied Math Colloquium: The Mean-Field Ensemble Kalman Filter

    Speaker: Andrew Stuart (California Institute of Technology) - https://www.eas.caltech.edu/people/astuart

    When: Tue, May 6, 2025 - 3:30pm
    Where: Kirwan Hall 3206
  • Aziz Lecture: Allowing Image And Text Data To Communicate

    Speaker: Andrew Stuart (California Institute of Technology) - https://www.eas.caltech.edu/people/astuart

    When: Wed, May 7, 2025 - 3:15pm
    Where: Kirwan Hall 3206