What This Document Is
This document is a final exam paper for Math 128, Calculus II, at Washington University in St. Louis. It’s designed to comprehensively assess a student’s understanding of the core concepts covered throughout the semester. The exam format consists primarily of multiple-choice questions, requiring both computational skills and conceptual grasp of calculus principles. It includes a reference table for normal distribution calculations.
Why This Document Matters
This resource is invaluable for students currently enrolled in Calculus II (or a similar course) who are preparing for their final examination. It’s particularly useful for self-assessment, identifying areas of strength and weakness, and familiarizing yourself with the types of questions and the overall exam structure. Studying a past exam can help reduce test anxiety and improve performance by providing a realistic practice experience. It’s best utilized after completing coursework and practicing problem-solving independently.
Common Limitations or Challenges
Please note that this document represents *one* past exam and may not perfectly reflect the content or difficulty of future exams. The specific topics emphasized and the question style may vary. This resource does not include detailed solutions or explanations; it’s intended as a practice tool, not a substitute for understanding the underlying mathematical principles. Access to the full document is required to view the questions and attempt solutions.
What This Document Provides
* A full set of multiple-choice questions covering a range of Calculus II topics.
* Questions assessing understanding of concepts like income concentration (Lorenz curve & Gini index).
* Problems requiring integration techniques.
* Applications of continuous compounding and income streams.
* Multivariable calculus problems involving critical points and function analysis.
* Least squares regression and predictive modeling exercises.
* Probability and statistics problems, including probability density functions, expected values, and medians.
* Taylor polynomial applications for function approximation and integration.
* An included normal distribution table for reference.
