Survey of Calculus 2 covers first-order differential equations, multivariable calculus, constrained optimization, infinite sequences and series, approximation methods, and probability, with models from business and social sciences.
Quizzes and exams were described as brutal and distinct from lectures, while homework remained simple.
What you’ll be able to do
Recall the algebraic and geometric properties of polynomial and power functions and use these properties to resolve practical problems.
Use definitions, properties, and theory related to the concept of the derivative to perform standard computations and analyze functions (e.g., use Lagrange multipliers to optimize multivariate functions, etc.).
Use definitions, properties and theory related to limits, sequences, and series to determine convergence, divergence, and limit values as possible (e.g., geometric sums, use limit values as approximations to long term behavior, etc.).
Use definitions, properties, and theory related to integrals to perform standard computations and analyze functions (e.g., numerical integration, multiple integrals, etc.).
Use definitions, properties, and theory related to differential equations to produce families of solutions and resolve initial value problems (e.g., first-order linear and separable ordinary differential equations, etc.).
Use functions to model practical behavior, analyze those functions using calculus concepts, and interpret that analysis in a practical context (e.g., identify concavity and use it to make investment decisions, model an annuity through a geometric series and determine its total present value, determine total change from a marginal rate, etc.).
Produce informal arguments and formal computations in English using proper mathematical terminology, notation, and logic.
“Used by” includes alternatives; linked courses may
have other requirements. This is a best-effort interpretation; check the
catalog requirements above.
Raw average: 4.90/5 from 49
quality ratings. The adjusted rating blends this with the UW review average
(3.66/5), weighted as 20
additional ratings. Smaller samples stay closer to that average. Each
captured review is counted once in the prior; this does not correct who
chooses to leave a review.
RMP profile ↗ · All captured review dates; profile matched by name.
No course-specific feedback yet.
Historical instructors & teaching patterns
ALEXANDER HANHART is recorded teaching in Fall 2017. Recorded history may be incomplete and does not establish a future schedule.
ANDREJ ZLATOS is recorded teaching in Spring 2011. Recorded history may be incomplete and does not establish a future schedule.
BOGUK KIM is recorded teaching in Spring 2010. Recorded history may be incomplete and does not establish a future schedule.
CHANGHONG MOU is recorded teaching in Fall 2022, Spring 2023. Recorded history may be incomplete and does not establish a future schedule.
DAVID DIAMONDSTONE is recorded teaching in Spring 2013. Recorded history may be incomplete and does not establish a future schedule.
EUGENIA MALITSKY is recorded teaching in Fall 2021. Recorded history may be incomplete and does not establish a future schedule.
HSIAN-HUA TSENG is recorded teaching in Fall 2008. Recorded history may be incomplete and does not establish a future schedule.
LEAH RINECK is recorded teaching in Spring 2022. Recorded history may be incomplete and does not establish a future schedule.
MARKO BUDISIC is recorded teaching in Fall 2014, Spring 2016. Recorded history may be incomplete and does not establish a future schedule.
PRERNA GERA is recorded teaching in Spring 2020. Recorded history may be incomplete and does not establish a future schedule.
SERGEY BOLOTIN is recorded teaching in Fall 2015. Recorded history may be incomplete and does not establish a future schedule.
YANNAN QIU is recorded teaching in Spring 2009. Recorded history may be incomplete and does not establish a future schedule.
Recorded history may be incomplete and does not establish a future
schedule.
Calendar & sections
Spring 2027
Schedule loads here as you scroll.
Section
Mode
Enrolled / capacity
Waitlist
LEC 001
Classroom Instruction
0 / 254
0
DIS 306
Classroom Instruction
0 / 30
0
DIS 302
Classroom Instruction
0 / 30
0
DIS 303
Classroom Instruction
0 / 30
0
DIS 304
Classroom Instruction
0 / 30
0
DIS 305
Classroom Instruction
0 / 30
0
DIS 307
Classroom Instruction
0 / 30
0
DIS 308
Classroom Instruction
0 / 30
0
DIS 309
Classroom Instruction
0 / 30
0
DIS 310
Classroom Instruction
0 / 30
0
Times are Central. Select a meeting for
details; export includes recorded dates for the selected sections. Enrollment reflects scan time.
Students found the course easy when taught by Prof. Mou, who provided clear lectures and organized notes.
Recent recorded grades — Spring 2025: 3.14 GPA, 50.2% A/AB (n=217 letter grades); Fall 2025: 2.93 GPA, 40.5% A/AB (n=222 letter grades); Spring 2026: 3.35 GPA, 55.4% A/AB (n=242 letter grades).
difficulty & workload
Past student reviews · Prerna Gera
Quizzes and exams were described as brutal and distinct from lectures, while homework remained simple.
Past student reviews · Leah Rineck
One student found the instructor disorganized and unprepared, reporting a hostile teaching environment.
Topics
First order differential equations
Multivariable calculus and constrained optimization
Infinite sequences and series, methods of approximation
Probability
Models and applications from business and social sciences
Skills
Solving first-order differential equations, multivariable calculus, constrained optimization, analyzing infinite sequences and series, and using methods of approximation.
Modeling practical behavior with functions, analyzing them using calculus concepts, and interpreting the results in business and social science contexts.
Grades
Historical instructor
Spring 2027 · Projected
Before grades are released
2.852.85–3.683.68average GPA
Approximate 80% prediction interval
0.04.0
About this estimate
The course’s semester-average GPA, not an individual student’s grade.
The center uses 5
same-season terms, weighted toward
recent results.
The range uses the finite-sample 80th-percentile rank of absolute errors
from earlier same-season forecasts. Each forecast uses only records from
earlier terms. At least four forecasts are required; bounds are rounded
outward and limited to 0–4. This is an empirical estimate: changing
instructors or grading policies can reduce its coverage.
8 earlier forecasts · 0.15 GPA average error.
Grades over time
Through Spring 2027
More grade details Grade mix, volume & source data
Where this course fits relative to
Latest available grades · Spring 2026 · all course levels
3.353.35GPA
Higher than 1919% of other courses in this group.
Course GPAs · red marks this course’s range
242242letter grades
More recorded grades than 9090% of other courses in this group.
Typical course in this group: 66.066.0 letter grades.
About this comparison
1280 courses over the same term, each with at least 30 recorded
letter grades. Cross-listed courses count once. GPA is not a measure
of difficulty or teaching quality. The typical course is the median by
recorded grade count; tied values are not counted as lower. Grade
counts describe course scale, not unique students or typical section
size.
Descriptions compare GPA with this group’s average: at least 0.20
higher or lower; otherwise close to average. Section size uses median
recorded enrollment: small up to 30, mid-sized 31–99, large 100+.
Lectures and discussion/lab sections are described separately.
Sources & history
UW–Madison
Catalog & offerings
Descriptions, prerequisites, and recorded course offerings.
Catalog observation history
Observations at scan time; dates do not imply when a catalog change took effect.