Math 265: Intro to Probability and Statistics for Data Science

Meetings: 1:10 pm -- 2:25 pm, TuTh, BH 244

Instructor: Chaojie Yuan

E-mail: yuan13@iu.edu

Office Hours: 11am -- 12pm or by appointment.

Course materials will be based on the book:

Jay L. Devore, Probability and Statistics for Engineering and the Sciences, 9th edition.

Prerequisites: M211 and A201 or equivalent. We will occasionally encounter topics for which I will provide additional review/instruction.

Course Description: Covers elementary concepts of probability and statistics for data science, including combinatorics, conditional probability, independence, random variables, discrete and continuous distributions, moments, statistical inference, point estimation, quantiles, confidence intervals, test of hypotheses, and related topics. Introduces the application of data analysis to the social and natural sciences.

Assignments:

1. There will be an assignment due approximately once per week. A component of some assignments will involve short coding problems in “R” demonstrating the mathematical techniques learned.

2. Assignments will be announced, usually on Tuesday, on Canvas and due the following Wednesday (11:59pm). It is your responsibility to check the Canvas site. Late assignments will not be accepted, but two lowest scores will be dropped at the end of the semester.

3. Assignments must be uploaded to Canvas as a single PDF file by the due date. If there is a coding component then this may be submitted as a separate PDF. More details will be given when coding problems are assigned. Please make sure that the PDF is easily legible.

4. You must show your work on the assignments; a correct numerical solution without accompanying work will be marked as incorrect.

5. Understanding the homework problems is necessary for developing a solid grasp of the material. In addition, it will provide vital problem-solving experience that you will need for the exams.

6. You are encouraged to work together on the assignments, but the final writeup and/or code must be your own.

Exams: There will be two term exams during our class period and a final exam. No books or notes are permitted, and cheating will not be tolerated. Calculators are not allowed during the exam. Exam schedules have been determined, and any make-up exams need to be scheduled one week in advance.

Exam I: 1:10 pm -- 2:25 pm Thursday, Sep 30 (during class)

Exam II: 1:10 pm -- 2:25 pm Thursday, Nov 11 (during class)

Final Exam: 5:25pm -- 7:25pm Thursday, December 16. Location TBD.

Academic Misconduct: The Department of Mathematics expects its students to comply fully with Indiana University policies on academic integrity. The Penalties for a student caught cheating in M118 may include a final course grade of F* (the star tells the registrar that the F is due to cheating) along with probation, suspension, or expulsion from the University. Academic misconduct will be reported to the Office of Student Ethics. Students should review the Code of Student Rights, Responsibilities, and Conduct, posted at: http://studentcode.iu.edu/

Grading Policy:

• Term Exams 1 and 2: 20% each for a total of 40%.

• Final Exam: 40%

• Assignments: 20%

The class grading scale (numerical intervals corresponding to each letter grade) will be set at the end of the course, but a raw score of 90% is guaranteed to be at least an A-, 80% at least a B-, 70% at least a C-, and 60% at least a D-.