ST 501-001:
Fundamentals of Statistical Inference I
Fall Session, 2018
Detailed Course Syllabus



Course:

ST 501-001 Fundamentals of Statistical Inference I

Time:

10:15am -- 11:30am: Mondays & Wednesdays

Place:

2229 SAS Hall

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Instructor:

Sujit K. Ghosh

Email:

sujit.ghosh@ncsu.edu

Telephone

515-2570

Office:

5116 SAS Hall (5th floor)

Office hours:

3:00pm -- 5:00pm: Mondays (or by appointment)

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Teaching Assistant:

Min Zhang

Email:

mzhang27@ncsu.edu

Office:

1101 SAS Hall (Statistics Tutorial Center)

Office hours:

1:15pm -- 3:00pm: Tuesdays


Class links: Course Materials | Private Tutors |

Course prequisite: MA 242 (or an equivalent course if approved by the instructor)

Required text: Rice A. J. (2007). Mathematical Statistics and Data Analysis, 3rd Edition. Cengage Learning. (ISBN-10: 1337823619 I ISBN-13: 9781337823616)

Data sets and Errata for the text: Download from this Data sets and Errata

Grades: It is the student's responsibility to be aware of their grades in the course and the appropriate level of work required. The final grade in this course will depend on the following:
Item
Portion of Grade
Homework (Assigned roughly weekly)
15% of grade (lowest two scores dropped)
Midterm Exam I (Oct 3rd, 2018, 10:15-11:30)
30% of grade
Midterm Exam II (Nov 7th, 2018, 10:15-11:30)
30% of grade
Final R project (Dec 3rd, 2018, 5:00PM, ET)
25% of grade
The course uses the standard NCSU grading scale.

Incomplete (IN) grades are given only as specified in university regulations. Students who wish to audit the course with satisfactory status must register officially for the course and will be required to obtain 75% or greater on the homework assignments to receive credit. There is no requirement to take the exams or do the R project.

Homework: There will about 10 homework assignments during the semester with the lowest two assignment scores being dropped. Many of the assignments will include a programming portion that will require the use of R and so students are highly encouraged to explore basic statistical methods using R. As the lowest two scores are dropped, no late assignments are accepted.

Midterm Exams: Both midterm exams are closed book and closed notes. However, students will be provided with a formula sheet by the instructor for each exam so that memorization is not required. All exams are cumulative. Students who are unable to attend an exam for a legitimate unavoidable reason may take a make-up exam only if the student provides suitable documentation of the delay (at least two days prior to the scheduled exam day) and they are able to take the make-up in a very timely manner. If a make-up exam can't be taken, one of the midterm exams will be reweighted for the missing midterm exam. Students are required to take at least one of the two midterm exams otherwise a grade of F will be assigned. The midterm exams are limited to 1.25 hours.

Final R Project: Students will be introduced to the use of R software and are encouraged to learn introductory R using online R resources. Toward the end of the semester, there will be a larger R project done in small groups. This will serve as the replacement of in-class final exam. Details of the final project will be provided after the second midterm exam.

Calculator: Students may wish to use a basic calculator that can do addition, subtraction, multiplication, division and square roots. Note you must use a basic calculator only, use of calculators that store information is not allowed. You shouldn't really need a calculator as the exam focuses more on the work rather than plugging things into a calculator.

Students with disabilities: Reasonable accommodations will be made for students with verifiable disabilities. Any student who feels they may need an accommodation based on the impact of a disability should contact the instructor privately to discuss your specific needs. In order to take advantage of available accommodations, students must register with Disability Services for Students at 1900 Student Health Center, Campus Box 7509, 515-7653. For more information on NC State's policy on working with students with disabilities, please click here

Academic Misconduct: Cheating, plagiarism and other forms of academic dishonesty will not be tolerated. To create a fair and equitable environment, the instructor aggressively enforces the universities policies on academic misconduct. All exams are to be completed individually. Although working together on written assignments to overcome obstacles is encouraged, each student must compose and write their own answers, explanations, analyses, and reports unless otherwise specified. All cases of academic misconduct will be handled as set out in university policies. For additional information see: Student Conduct Policies
Course goals: First of a two-semester sequence in probability and statistics taught at a calculus-based level. Probability: discrete and continuous distributions, expected values, transformations of random variables, sampling distributions. Students should gain an understanding of probability and random variables in order to have the foundation to conduct statistical inference in ST 502.

Course Outline:
Basic Probability and Counting
Random Variables and Expectations
Common Parameteric Distributions
Transformation of Random Variables
Joint and Conditional Distributions
Measures of Associations
Limit Theorems and Delta Method
Statistical Estimation (a very brief intro)

Calendar of Events:
8/22/18 (Wednesday: First day of classes
8/28/18 (Tuesday): Last day to add a course without permission
09/03/18 (Monday): Labor day (no class)
10/03/18 (Monday): Midterm Exam I
10/19/18 (Friday): Drop/Revision deadline
11/07/18 (Monday): Midterm Exam II
12/03/18 (Monday): Final R Project due
12/05/18 (Wednesday): Last day of classes
12/14/18: No in-class Final exam

Communication: Students are expected to check their NCSU email regularly. Students who do not use their NCSU email should arrange to have this email forwarded to an account they do use. Due to university regulations the instructor can send course announcements only to NCSU email addresses.

Online Class Evaluation: Online class evaluations will be available for students to complete during the last two weeks of class (November 20 - December 1). All evaluations are confidential; instructors will never know how any one student responded to any question, and students will never know the ratings for any particular instructors.
Click ClassEval for further information.

Last updated on: August 15, 2018