UQAM · MAT1115

UQAM MAT1115 tutoring

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Course overview

MAT1115 is multivariable calculus, with a review of one-variable methods. The official content links partial derivatives and local approximation to constrained optimization, then develops multiple integration and coordinate changes. The title Calcul I should not be read as a limits-only introduction.

Topics include Partial and directional derivatives, Gradient and optimization, Lagrange multipliers, Double/triple integrals and Jacobians.

MAT1115 topics to review

Partial and directional derivativesGradient and optimizationLagrange multipliersDouble/triple integrals and Jacobians

Common difficulties

  • Normalizing a direction vector before interpreting a derivative per unit distance
  • Making integration bounds and a Jacobian describe the same region

Preparing for this course

Refresh the chain rule, elementary antiderivatives, dot products and vector lengths. Sketch a region from inequalities and practise stating which variable is held fixed. These habits help connect one-variable calculations with surfaces and spatial regions.

Registration requirements

Consult the official course description for prerequisites, restrictions and section details.

Check the official course catalogue

Try a course problem

Let f(x,y)=x2+xy+y2f(x,y)=x^2+xy+y^2 be a real-valued function of the coordinates xx and yy. Find its directional derivative at (1,2)(1,2) in the direction of (3,4)(3,4), using the rate per unit distance convention. Estimate the value of ff after moving a distance of 0.010.01 from that point in this direction. Would specifying (6,8)(6,8) as the direction change the answer?

Show the reasoning
  1. Find the gradient at the starting point

    The gradient ∇f\nabla f is the vector of partial derivatives, each found while holding the other coordinate fixed: ∇f(x,y)=(2x+y,x+2y)\begin{aligned}&\nabla f(x,y)\\&=(2x+y,x+2y)\end{aligned}. At the starting point, ∇f(1,2)=(4,5)\nabla f(1,2)=(4,5).

  2. Normalize the direction vector to length 1, then calculate the rate per unit distance

    The length of (3,4)(3,4) is 32+42=5\sqrt{3^2+4^2}=5, so the unit direction vector is u=(3/5,4/5)u=(3/5,4/5).

    Let Duf(1,2)D_u f(1,2) denote the rate of change per unit distance in this direction. It is the dot product Duf(1,2)=∇f(1,2)⋅u=4(3/5)+5(4/5)=32/5=6.4\begin{aligned}&D_u f(1,2)\\&=\nabla f(1,2)\cdot u\\&=4(3/5)+5(4/5)\\&=32/5=6.4\end{aligned}.

  3. Estimate the value after moving a distance of 0.01

    Let s=0.01s=0.01 be the distance moved. The displacement is su=(0.006,0.008)su=(0.006,0.008), so the new point is (1.006,2.008)(1.006,2.008).

    Since f(1,2)=7f(1,2)=7, the estimate is f(1.006,2.008)≈f(1,2)+sDuf(1,2)=7+0.01(6.4)=7.064\begin{aligned}&f(1.006,2.008)\\&\approx f(1,2)+sD_u f(1,2)\\&=7+0.01(6.4)\\&=7.064\end{aligned}. This is an approximation because it keeps only the starting value and the linear change.

  4. Check the error and compare the two direction vectors

    Direct substitution gives f(1.006,2.008)=7.064148f(1.006,2.008)=7.064148. The omitted quadratic terms are (0.006)2+(0.006)(0.008)+(0.008)2=0.000148\begin{aligned}&(0.006)^2+(0.006)(0.008)\\&\quad +(0.008)^2=0.000148\end{aligned}, exactly the difference.

    Using (3,4)(3,4) without normalizing would give a rate of 3232 per unit of its path parameter, not per unit distance. The vector (6,8)(6,8) has length 1010 and normalizes to the same uu, so the requested directional derivative and estimate do not change.

For multiple-integral practice, learn to sketch the region, choose slice bounds and reverse the order of integration. Practise double-integral regions and bounds

How tutoring can help

You can start with a question, an unfamiliar concept or any work you have already tried. Your tutor can connect derivatives and optimization to a sketch, so you can explain which variable changes and which constraint applies. For multiple integrals, you can draw the region together and compare slice directions to see why particular bounds work.

Exam preparation for MAT1115

Select mixed problems from your current outline rather than practising only one derivative rule at a time. Require a unit-vector check for directional derivatives, a constraint check for optimization and a region/Jacobian check for coordinate changes. Rework one problem with altered bounds or a reversed direction to test whether the method transfers.

Use your section’s outline to choose the chapters to review. We work through permitted practice and comparable problems, without completing graded assignments or exams on your behalf.

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MAT1115 · official course reference