MAT2615 Assignment 3 Solutions 2026
Full Solutions By TA tutor iQ level
UNISA
DUE: 31-07-2026
,Question 1: Critical Points and Extrema
f(x, y) = x² − 6x + 3y² − y³
Part (a): Finding Critical Points
Critical points occur where both partial derivatives equal zero simultaneously.
Compute partial derivatives:
∂𝑓
𝑓𝑥 = = 2𝑥 − 6
∂𝑥
∂𝑓
𝑓𝑦 = = 6𝑦 − 3𝑦 2
∂𝑦
Set equal to zero:
𝑓𝑥 = 0 ⟹ 2𝑥 − 6 = 0 ⟹ 𝑥 = 3
𝑓𝑦 = 0 ⟹ 6𝑦 − 3𝑦 2 = 0 ⟹ 3𝑦(2 − 𝑦) = 0 ⟹ 𝑦 = 0 or 𝑦 = 2
Critical points: (3, 0) and (3, 2)
Part (b): Classify using Theorem 10.2.9 (Second Derivative Test)
Compute second-order partial derivatives:
𝑓𝑥𝑥 = 2, 𝑓𝑦𝑦 = 6 − 6𝑦, 𝑓𝑥𝑦 = 0
The discriminant (Hessian determinant) is:
𝐻(𝑥, 𝑦) = 𝑓𝑥𝑥 ⋅ 𝑓𝑦𝑦 − (𝑓𝑥𝑦 )2 = (2)(6 − 6𝑦) − 0 = 12 − 12𝑦
At (3, 0):
𝐻(3,0) = 12 − 12(0) = 12 > 0
Since 𝐻 > 0and 𝑓𝑥𝑥 = 2 > 0: (3, 0) is a local minimum.
𝑓(3,0) = 9 − 18 + 0 − 0 = −9
, At (3, 2):
𝐻(3,2) = 12 − 12(2) = 12 − 24 = −12 < 0
Since 𝐻 < 0: (3, 2) is a saddle point (minimax value).
𝑓(3,2) = 9 − 18 + 12 − 8 = −5
Global extrema (by inspection):
As 𝑥 → +∞with 𝑦 = 0: 𝑓(𝑥, 0) = 𝑥 2 − 6𝑥 → +∞
As 𝑦 → +∞with 𝑥 = 3: 𝑓(3, 𝑦) = −9 + 3𝑦 2 − 𝑦 3 → −∞
Therefore:
• The local minimum at (3, 0) with value −9 is NOT a global minimum (f is
unbounded below)
• There is no global maximum (f is unbounded above)
Full Solutions By TA tutor iQ level
UNISA
DUE: 31-07-2026
,Question 1: Critical Points and Extrema
f(x, y) = x² − 6x + 3y² − y³
Part (a): Finding Critical Points
Critical points occur where both partial derivatives equal zero simultaneously.
Compute partial derivatives:
∂𝑓
𝑓𝑥 = = 2𝑥 − 6
∂𝑥
∂𝑓
𝑓𝑦 = = 6𝑦 − 3𝑦 2
∂𝑦
Set equal to zero:
𝑓𝑥 = 0 ⟹ 2𝑥 − 6 = 0 ⟹ 𝑥 = 3
𝑓𝑦 = 0 ⟹ 6𝑦 − 3𝑦 2 = 0 ⟹ 3𝑦(2 − 𝑦) = 0 ⟹ 𝑦 = 0 or 𝑦 = 2
Critical points: (3, 0) and (3, 2)
Part (b): Classify using Theorem 10.2.9 (Second Derivative Test)
Compute second-order partial derivatives:
𝑓𝑥𝑥 = 2, 𝑓𝑦𝑦 = 6 − 6𝑦, 𝑓𝑥𝑦 = 0
The discriminant (Hessian determinant) is:
𝐻(𝑥, 𝑦) = 𝑓𝑥𝑥 ⋅ 𝑓𝑦𝑦 − (𝑓𝑥𝑦 )2 = (2)(6 − 6𝑦) − 0 = 12 − 12𝑦
At (3, 0):
𝐻(3,0) = 12 − 12(0) = 12 > 0
Since 𝐻 > 0and 𝑓𝑥𝑥 = 2 > 0: (3, 0) is a local minimum.
𝑓(3,0) = 9 − 18 + 0 − 0 = −9
, At (3, 2):
𝐻(3,2) = 12 − 12(2) = 12 − 24 = −12 < 0
Since 𝐻 < 0: (3, 2) is a saddle point (minimax value).
𝑓(3,2) = 9 − 18 + 12 − 8 = −5
Global extrema (by inspection):
As 𝑥 → +∞with 𝑦 = 0: 𝑓(𝑥, 0) = 𝑥 2 − 6𝑥 → +∞
As 𝑦 → +∞with 𝑥 = 3: 𝑓(3, 𝑦) = −9 + 3𝑦 2 − 𝑦 3 → −∞
Therefore:
• The local minimum at (3, 0) with value −9 is NOT a global minimum (f is
unbounded below)
• There is no global maximum (f is unbounded above)