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The final examination has been graded.
The exam had mean 101, standard deviation 28, and median 102. Scores ranged from 2 to 159 out of 180.

The graded exams will not be available until January, but final exam scores by SUID are available for viewing at the Final Examination Grades page.

Happy Holidays!

The final exam will be given on Wednesday, December 11, 8:30-11:30am in Braun Auditorium in the Mudd Chemistry Building.
Students who have a conflict with the regular exam can request to take an alternate final examination on Thursday, December 12, 8:30-11:30am.

If you need any special arrangements for the final exam or are unable to take the regular exam, please complete the web form by Sunday, December 1, so we can make the necessary arrangements.

The topics for the exam are listed in the Examination Study Guide posted on the Handouts page. A past final exam is also posted there, but solutions will not be provided.

The exam is open-book and open-notes with any materials from this quarter's class. No electronic devices are permitted so calculations will be kept as simple as possible, and you will receive complete credit for setting up the calculations clearly and correctly, even if you do not carry them out.

Note that he last two lectures, December 4 and 6, will be a course review, and together we will solve the posted past final exam.
The last problem sessions will be on Friday, December 6.
There will be office hours during Finals Week:
Sunday, Dec 8, 7-9pm, Thornton 110
Monday, Dec 9, 9-11am, Huang 304
Tuesday, Dec 10, 3:45-7:45pm, Huang 203

Please pick up any of your graded papers that are still in the submission cabinet on the terrace (basement) level of Huang. Any papers still in the cabinet will be discarded early in January.

Office Hours are:
Sundays, 7-9pm, Thornton 110
Mondays, 8:45-9:30am (in the classroom)
Wednesdays, 8:45-9:30am (in the classroom)
Wednesdays, 2-3:30pm, Huang 218
Wednesdays, 3:30-5pm, Oct 2 and 9 in Huang 139, Oct 16 on in Huang B007
Thursdays, 1:15-2:45pm, Huang B019
Fridays, 8:45-9:30am (in the classroom)

Class meets Mondays, Wednesdays, Fridays, 9:30-10:45, in 380-380C.
The syllabus, study guide, lecture notes, and solution sets are posted on the Handouts page.

There will be problem sessions starting Friday, September 27 at 1:15 and 2:15 in Thornton 110.

Students can register for the class on Axess but not for sections. Do not be alarmed by the warning that there is no capacity in the sections.

Course Objective

This is a fast-paced, fundamental course designed to develop an understanding of uncertain phenomena using the theory of probability. The course objective is to provide students with conceptual and intuitive insights into probabilistic reasoning and the ability to understand and solve real world problems.

Intended Audience

For students seeking an introduction to probability theory and applications, this course is designed to develop their intuition and model building skills. You should acquire Ways of Thinking in Formal Reasoning (intuitively understand a number of fundamental probabilistic reasoning concepts based on a mathematical foundation) and Applied Quantitative Reasoning (solve real world problems under uncertainty by structuring them, building models, and analyzing those models). This course also satisfies the Distributional Breadth GER in Engineering and Applied Science.

It is intended for undergraduate students and should be taken for five units.
Graduate students in MS&E should enroll in a similar but separate course, MS&E 220.

Course Summary

Concepts and tools for the analysis of problems under uncertainty, focusing on model building and communication: the structuring, processing, and presentation of probabilistic information. Examples from legal, social, medical, engineering, and physical problems provide motivation and illustrations of modeling techniques. Spreadsheets will be used to illustrate and solve problems as a complement to analytical closed-form solutions.

Topics include axioms of probability, probability trees, belief networks, random variables, distributions, conditioning, inference, expectation, change of variables, and limit theorems.

Prerequisite: Mathematics 51.

Required Textbook

The required textbook for the course is Sheldon Ross, A First Course in Probability, Prentice Hall, 2014 (Ninth Edition). It is on reserve in the Engineering Library, and it is possible to use the eighth edition instead.


Additional information is in the syllabus posted on the Handouts page and at syllabus.stanford.edu.