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  • EN 550.122: Chance And Risk

    3.00 Credits
    Johns Hopkins University

    The course will help students develop an appreciation of probability and randomness, and an understanding of its applications in real life situations involving chance and risk. Applications, controversies, and paradoxes involving risk in business and economics, health and medicine, law, politics, sports, and gambling will be used to illustrate probabilistic concepts such as independence, conditional probability, expectation, and variance. The course is intended primarily for humanities and social science majors. There is no prerequisite beyond high school mathematics. The course is not open to students who have taken AP Calculus BC, AP Statistics, 550.111, 550.112 or more than one semester of Calculus.
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  • EN 550.171: Discrete Mathematics

    4.00 Credits
    Johns Hopkins University

    Prereq: Four years of high school mathematics Introduction to the mathematics of finite systems. Logic; Boolean algebra; induction and recursion; sets, functions, relations, equivalence, and partially ordered sets; elementary combinatorics; modular arithmetic and the Euclidean algorithm; group theory; permutations and symmetry groups; graph theory. Selected applications. The concept of a proof and development of the ability to recognize and construct proofs are part of the course.
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  • EN 550.211: Probability and Statistics for the Life Sciences

    4.00 Credits
    Johns Hopkins University

    This is an introduction to statistics aimed at students in the life sciences. The course will provide the necessary background in probability with treatment of independence, Bayes theorem, discrete and continuous random variables and their distributions. The statistical topics covered will include sampling and sampling distributions, confidence intervals and hypothesis testing for means, comparison of populations, analysis of variance, linear regression and correlation. Analysis of data will be done using Excel. Prerequisite: Calculus I
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  • EN 550.230: Intro To Biostatistics

    4.00 Credits
    Johns Hopkins University

    3 years HS math. A self-contained course covering various data analysis methods used in the life sciences. Topics include types of experimental data, numerical and graphical descriptive statistics, concepts of (and distinctions between) population and sample, basic probability, fitting curves to experimental data (regression analysis), comparing groups in populations (analysis of variance), methods of modeling probability (contingency tables and logistic regression).
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  • EN 550.251: Math Models/Decision Mkg

    4.00 Credits
    Johns Hopkins University

    Prereq: One semester of calculus This course is an introduction to management science and the quantitative approach to decision making. Our focus will be on deterministic models, in which we assume that all problem parameters are known with certainty. The covered topics may include Linear and Integer Programming, Network Models, Inventory Models (Stationary Demand), Nonlinear Programming, Goal Programming, and Dynamic Programming. We emphasize model development and case studies, using spreadsheets and other computer software. The applications we study occur in manufacturing and transportation systems, as well as in finance and general management.
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  • EN 550.282: A Hands-On Introduction to MATLAB

    1.00 Credits
    Johns Hopkins University

    This is a first course in programming MATLAB for students in the mathematical sciences. MATLAB is widely used in research and industry for numerical calculations, plotting of functions and data, and the creation of user interfaces. Short tutorial lectures will be followed by problem solving sessions. Topics emphasized will be basic programming in the MATLAB environment and the practical solution of problems in matrix calculations, differential equations, signal and image processing, and machine learning.
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  • EN 550.283: Introduction to R

    1.00 Credits
    Johns Hopkins University

    This is an introductory course in R for both undergraduate and graduate students. R is a programming language and software environment that provides a wide variety of statistical and graphical techniques, including linear and nonlinear modeling, classical statistical tests, time-series analysis, etc. We will discuss data structures, data entry and manipulation, graphical procedures, statistical models, and programming in R. No previous programming experience is required.
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  • EN 550.291: Lin Alg & Diff Equations

    4.00 Credits
    Johns Hopkins University

    Prereqs: One year of Calculus, computing experience ( AS.110.106 OR AS.110.108 ) AND ( AS.110.107 or AS.110.109 ) An introduction to the basic concepts of linear algebra, matrix theory, and differential equations that are used widely in modern engineering and science. Intended for engineering and science majors whose program does not permit taking both 110.201 and 110.302.
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  • EN 550.310: Probability & Statistics for the Physical and Information Sciences & Engineering

    4.00 Credits
    Johns Hopkins University

    Prereq: one year of calculus. Recommended corequisite: multivariable calculus. - Students cannot receive credit for both 550.310 and 550.311. Students cannot receive credit for 550.310 after having received credit for 550.420 or 550.430. An introduction to probability and statistics at the calculus level, intended for engineering and science students planning to take only one course on the topics. This course will be at the same technical level as 550.311. Students are encouraged to consider 550.420-430 instead. Combinatorial probability, independence, conditional probability, random variables, expectation and moments, limit theory, estimation, confidence intervals, hypothesis testing, tests of means and variances, goodness-of-fit. Prerequisite: one year of calculus. Recommended corequisite: multivariable calculus.
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  • EN 550.311: Prob/Stat-Bio Sci & Eng

    4.00 Credits
    Johns Hopkins University

    Prerequisite: One year of calculus; Corequisite: 110.202 recommended An introduction to probability and statistics at the calculus level, intended for students in the biological sciences planning to take only one course on the topics. This course will be at the same technical level as 550.310. Students are encouraged to consider 550.420-430 instead. Combinatorial probability, independence, conditional probability, random variables, expectation and moments, limit theory, estimation, confidence intervals, hypothesis testing, tests of means and variances, and goodness-of-fit will be covered. Students cannot receive credit for both 550.310 and 550.311. Students cannot receive credit for 550.311 after having received credit for 550.420 or 550.430.
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