CALCULUS

Instructional goals

The course aims to provide first-year economics students with the main mathematical tools that are used to analyse and solve a wide range of problems in economics, business, finance and insurance. This will be their first step towards achieving a broad training in quantitative disciplines, as well as a good methodological training for the analysis and critical interpretation of economic and business dynamics. This will allow them to acquire the useful tools for the formulation, implementation and control of decisions in the work contexts in which they will operate.

Intended learning outcomes

Knowledge and understanding: By the end of the course, students will have acquired a wide range of mathematical tools and will be able to understand and solve numerous theoretical and applied problems in economics, business and finance. Ability to apply knowledge and understanding: By the end of the course, students will be able to apply quantitative tools to business decisions, to the analysis of economic phenomena and to the resolution of economic and business problems in the work contexts in which they will operate. Autonomy of judgment: By the end of the course, students will be able to develop a critical capacity in identifying the most suitable solution to the proposed problem, even in highly innovative contexts. Communication skills: By the end of the course, students will be able to develop both written and oral communication skills and to highlight the relationships between the theoretical concepts and the most important economic and managerial applications. Learning ability: By the end of the course, students will be able to stay up to date and improve their skills in examining the quantitative aspects of economics and management.

Course Contents

The mathematical analysis for functions of a single variable allows the students to introduce the fundamental mathematical tools (limits, derivatives, integrals) for the definition and study of the mathematical models in economics. The functions of several variables make it possible to develop models that are closer to real life economics. To this end, the tools already introduced for the functions of single variable are suitably adapted to the new context. The study of the matrices and the linear systems allows the design of models capable of including large amounts of data. The explanation is accompanied by economic examples to illustrate the importance, in real life’s settings, of the tools acquired tools in during the course.

Reference Books

Essential Mathematics for Economic Analysis 6th Edition by Knut Sydsaeter, Peter Hammond, Arne Strom, Andrés Carvajal, Pearson

Teaching Methods

The teaching activity will consist of: - frontal teaching and tutoring - material for in-depth study of the topics available on the learn.luiss.it page of the course. The teacher and the teaching assistants will set up weekly office hours to help students.

Assessment Method

Student evaluation will be based on individual performance, class participation, and overall involvement. For students with consistent attendance, grading will be determined according to several criteria. Class participation and assignments are an important component: active engagement and the timely completion of weekly assignments may earn students whole or partial bonus points. The midterm exam accounts for 50 percent of the final grade before bonuses. It will be administered during the course break, between the sixth and seventh week, and will consist of multiple-choice questions and written exercises, with points assigned according to question difficulty. The exam is graded on a 0–30 scale, with a minimum passing score of 18. Students may also choose to reject their midterm grade, provided they comply with the rules and deadlines announced during the course. The final exam makes up the remaining 50 percent of the final grade before bonuses, or 100 percent if the midterm grade is not considered. The format mirrors that of the midterm, including multiple-choice questions and written exercises, and is also graded on a 0–30 scale with a minimum passing score of 18. Bonus points are applied only to final exam scores, with rounding carried out exclusively at the end. After each written exam and before the official posting of grades, students will have the opportunity to review their work during a scheduled meeting with the instructors. Exam sessions will be held in December 2025 and January 2026, when students may retake the midterm and/or the final exam. Additional sessions will take place in May and September 2026, during which a single comprehensive exam covering material from both the midterm and the final will be offered.

Thesis assignment criteria

Interview with the teacher after the exam.

Week 1

Introducing functions of one variable. Graphs of functions. Linear and quadratic functions. Polynomials. Power, exponential and logarithmic functions. Economic applications. TA sessions on the lectures of the present week.

Week 2

Functions and their properties Shifting grafts. New functions from old (operations on functions, compound and piecewise defined functions). Inverse functions. Graphs of equations and graphs of functions. Economic applications. TA sessions on the lectures of the present week.

Week 3

Limits and Their Properties Informal definition of limit. Rules for calculating limits. One-sided limits. Infinite limits. Limits at infinity. Continuity and limits. Properties of continuous functions. Economic applications. TA sessions on the lectures of the present week

Week 4

Differentiation The Derivative and the Tangent Line Problem. Continuity and differentiability. Basic Differentiation Rules. Product and Quotient Rules. Higher-Order Derivatives The Chain Rule. The derivative of exponential and logarithmic functions. Economic applications. TA sessions on the lectures of the present week

Week 5

Using the derivative. Increasing and decreasing functions and the first derivative test. Concavity and the second derivative test. Derivative for compound functions. Linear approximation. Quadratic approximation. Elasticity. The Intermediate Value Theorem. L’Hopital’s rule. Economic applications. TA sessions on the lectures of the present week.

Week 6

Optimization of one-variable functions. Global and local extrema of a function. Fermat’s Theorem. The Extreme and Mean Value Theorems. First and second derivative tests for local extrema. Tests for global extrema. Curve sketching. Economic applications. TA sessions on the lectures of the present week.

Week 7

Matrix Algebra. Matrices and vectors. Systems of linear equations. Matrix addition and multiplication. The transpose. Gaussian elimination. Economic applications. TA sessions on the lectures of the present week.

Week 8

Determinants and Inverses Determinant of a square matrix. Basic rules for determinants. Expansion by cofactors. The inverse of a matrix. Cramer's rule. Economic applications. TA sessions on the lectures of the present week.

Week 9

Geometric interpretation of vectors. Lines and planes. Linear independence and matrix rank. Economic applications. TA sessions on the lectures of the present week.

Week 10

Integration Indefinite integrals. Area and definite integrals. Properties of definite integrals TA sessions on the lectures of the present week.

Week 11

Integration Integration by parts and by substitution. Economic Applications. Functions of Several Variables Introduction. Graphs and level curves. Partial Derivatives TA sessions on the lectures of the present week.

Week 12

Functions of several variables Local extreme points. Finding extrema. Economic Applications. TA sessions on the lectures of the present week.