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I have over 8 years experience tutoring all levels of undergraduate mathematics in addition to experience as an Adjunct Professor of Mathematics at NYU-Poly. I hold a B.S. in Mathematics from NYU-Poly, an M.S. in Risk Management from St. John's University, and I am currently… Read more

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Biostatistics
Elementary Education:

Homeschool:

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I am currently studying Risk Management and Insurance at the PhD level. I have a high level preparation for the first two actuarial exams:

Exam P–Probability

Exam FM–Financial Mathematics

Exam P

Probability theory and its application to insurance and risk management problems are discussed. Counting techniques, conditional probability, Bayes' Theorem, discrete random variables, specific discrete distributions such as Binomial, Poisson, Negative Binomial and Uniform, moment generating functions and functions of two random variables.

Exam FM

Calculating present and accumulated values for various streams of cash flows as a basis for future use in: reserving, valuation, pricing, asset/liability management, investment income, capital budgeting and valuing contingent cash flows

I have tutored Biostatistics at NYU for 1 semester.

Statistical methods used in biology, including probability, statistical distributions, regression, correlation and tests. ANOVA, Principal Components Analysis (PCA), as well as tests of significance and non-parametric statistics.

I have taken BC Calculus in high school with a 5 on the AP exam. I also took Multivariable Calculus at NYU. In addition, I have over 5 years experience tutoring Calculus and Multivariable Calculus at NYU.

Calculus I

Functions of one variable. Limits, derivatives of functions defined by graphs, tables and formulas, differentiation rules for power, polynomial, exponential and logarithmic functions, derivatives of trigonometric functions, the product and quotient rule, the chain rule, applications of the chain rule, maxima and minima, optimization.

Calculus II

Definite integrals, theorems about integrals, anti-derivatives, second fundamental theorem of calculus, techniques of integration, introduction to ordinary differential equations, improper integrals, numerical methods of integration, applications of integration, sequences, series, power series, approximations of functions via Taylor polynomials, Taylor series.

Calculus III

Multivariable Calculus. Analysis of functions of several variables, vector valued functions, partial derivatives and multiple integrals. Optimization techniques, parametric equations, line integrals, surface integrals and major theorems concerning their applications.

Calculus IV

Calculus of vector fields: the various differential operators (grad, curl, div) that can be applied to a function or vector field, types of integrals of vector fields (line integrals, surface integrals), and the fundamental theorems (Green, Stokes, divergence or Gauss) relating differentiation and integration of vector fields. The last part of the course is an introduction to the theory of functions of a complex variable. This theory is important in many applications of mathematics, physics, and engineering.

I have experience advising students on career development and resume and cover letter writing. I know networking techniques and how to use websites such as Linkedin.

I advised high school students on choosing the right major based on their interests and potential career path. I guided students in choosing the right college which is a good fit for their abilities as well as based on various college rankings.

I have taken Ordinary Differential Equations at NYU. In addition, I tutored Ordinary Differential Equations at NYU for 4 years.

First order differential equations: modeling and solving. Stability of autonomous equations. Higher order linear ordinary differential equations: Solution bases, Wronskian and initial value problems. Linear system of first-order differential equations with constant coefficients: Elimination and eigenvalue method of solution. Elementary concepts of numerical analysis. Numerical solution of initial value problems for ordinary differential equations.

I have taken Topics in Econometrics and Advanced Financial Econometrics at NYU. I tutored econometrics at NYU for 1 year. In addition, my PhD research involves extensive use of econometrics.

Identification and estimation of simultaneous equations models; model specification and testing; estimation of discrete choice models; and the analysis of duration models. Models such as OLS, probit, logit. Cross-section data, panel data and financial time series.

I have taken courses in Economic Theory of Choice and Information economics at the PhD level at Temple University. I have also taken undergraduate macroeconomics at NYU.

Microeconomics (Intermediate and Advanced), Math for Economists, Macroeconomics

Microeconomics

Supply and Demand Curves. Production Function: Inputs, Outputs, Costs. Average Product, Marginal Product. Law of Diminishing Marginal Returns. Utility theory and risk aversion. Elasticity and marginal rate of technical substitution. Perfect Competition vs. Monopolistic Competition.

Macroeconomics

Macroeconomic theory applied to aggregate supply and demand and their components, designing and implementing macroeconomic policy goals and forecasting GDP and its components.

Math for Economists

Applications of mathematics to economics: functions, simultaneous equations; linear models and matrix algebra; determinants, inverse matrix, Cramer’s rule; differentiation and optimization of functions of one or more variables; quadratic forms, characteristic roots and vectors, constrained optimization; interpretation of the Lagrange multiplier. Techniques applied to examples from the theory of the firm and consumer behavior.

I have taken courses such as Corporate Finance, Investments/Portfolio Theory, Risk Management, and Asset Pricing at NYU. I have also taken courses in Credit Risk, Market Risk, and Operational Risk at St. John's University. Currently, I am taking PhD level finance courses at Temple University.

Corporate Finance

The theory, the methods, and the concerns of corporate finance. 1) the time value of money and capital budgeting techniques; 2) uncertainty and the trade-off between risk and return; 3) security market efficiency; 4) optimal capital structure, and 5) dividend policy decisions.

Investments/Portfolio Theory

portfolio theory; equilibrium models of security prices, including the capital asset pricing model and arbitrage pricing theory; empirical behavior of security prices; market efficiency; performance evaluation; and fixed-income markets.portfolio theory; equilibrium models of security prices, including the capital asset pricing model and arbitrage pricing theory; empirical behavior of security prices; market efficiency; performance evaluation; and fixed-income markets.

Risk Management (Insurance Side)

Risk identification and evaluation, the need for insurance, the effects of limited liability, theory of moral hazard, and adverse selection.

Risk Management/Derivatives & Option Pricing (Finance Side)

Risk finance and attitudes; Value at Risk; Risk measurement principles; valuation and expected utility and their relevance in the valuation and the pricing of financial investments; management of derivatives. Fundamental principles of the Arrow-Debreu state preference theory used to price derivatives and other assets in complete markets. Risk neutral-Binomial models in option pricing; and the Black-Scholes model for pricing options.

I have taken undergraduate and graduate Linear Algebra at NYU. In addition, I have 4 years of experience tutoring Linear Algebra at NYU.

Vector concepts. Linear transformations. Matrices and Determinants. Characteristic roots and eigenfunctions. Basic ideas of linear algebra: Fields, vector spaces, basis, dependence, independence, dimension. Relation to solving systems of linear equations and matrices. Homomorphisms, duality, inner products, adjoints and similarity.

I have taken undergraduate and graduate probability at NYU. In addition, I tutored probability to both undergraduate and graduate students at NYU for over 4 years.

Counting techniques, axiomatic definition of probability, conditional probability, independence of events, Bayes Theorem. Random variables. Discrete and continuous distributions. Joint distributions. Expectation. Functions of a random variable. Central limit theorem. Moment generating functions.

I have 2 years experience tutoring SAT math. In addition, I have developed special tips and tricks for dealing with many SAT Math problems. I have a customized approach to teaching SAT students based on the score they wish to attain as well as their math ability.

I use STATA extensively in my PhD research. I am familiar with almost all of the econometric techniques available in STATA as well as data manipulation.

I have taken AP Statistics with a 4 on the AP exam, Data Analysis I/II at NYU, Mathematical Statistics at NYU, Applied Statistics at NYU, and Multivariate Analysis at Temple University. I also tutored statistics at NYU for 4 years. In addition, my PhD research involves extensive use of statistics.

Sampling distributions, tests of hypotheses, significance tests, point and interval estimation, regression and analysis of variance.

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