EC223 A1 Statistical analysis - Spring 2025 - Department of Economics

Course description: This is an introductory mathematical statistics course, covering probability theory, statistical inference, and an introduction to regression analysis. The course aims at providing students with the necessary background to progress to higher level econometrics and applied economics courses. Effective Fall 2023, this course fulfills a single unit in each of the following BU Hub areas: Quantitative Reasoning I, Critical Thinking.

Prerequisite courses: CAS EC101, CAS EC102, CAS MA225

The required software: Stata is a statistical software product popular with economists and financial experts. I recommend purchasing your own Stata license through the BU information technology department (check their website at

https://www.bu.edu/casit/information/purchasing-software/). It will re-direct you to the Stata website, where you will see different options. I recommend the $145 Stata/BE for one year

(especially if you plan to take ec224 next semester).

Instead of purchasing your own Stata software, students can utilize the computers in the BU library and in CAS 327 at 685 Commonwealth Avenue.  Student ID card access can be requested (students can set up the card for access in CAS 331 between 9 am – 5 pm. The cards will give access between 8 am – 10 pm, 7 days a week, and we ask students to be aware of the room availability as it is also used for lectures and lab sections. The schedule of classes in CAS 327 is posted on their door as well as online at http://www.bu.edu/casit/computer-labs/. The building doors are typically open until 11 pm most weekday evenings.

The required textbook: “ Mathematical Statistics With Applications,” by Jay Devore, Kenneth

Berk, Matthew Carlton. Springer Publisher, 3rd  edition, 2021. It is available as a free file in a .pdf format online:

https://link.springer.com/content/pdf/10.1007/978-3-030-55156-8.pdf

The reference textbook for the course is Statistics for Business and Economics by Newbold, Carlson, Thorne. “ Mathematical Statistics With Applications,” Pearson Publisher, 9th  edition, 2023. NOT required. Why is it useful? It provides an exceptionally clear explanation of the major concepts in probability and mathematical statistics without using calculus. Great for those who would like to understand mathematics not only at the formal level, but with their heart. Various versions are available (unfortunately, not for free) via the Barnes & Noble bookstore on campus.

Blackboard: All the materials from the course will be posted on the blackboard course site. The announcements will be sent via blackboard email – so please check it regularly. It is the students’ responsibility to keep up with the course requirements (i.e., you will need to go through all the course materials on blackboard, as well as keep pace with online quizzes and assignments). Please note that I do not plan to record lectures on the regular basis. If you cannot keep pace with the course material, please contact me immediately so that we can resolve any potential issues.

Grading:

I’ll base the course grade on students’ scores on:

1.   Two midterm exams (20% of the final grade each)

2.   Final exam (20% of the final grade)

3.   Homework & Stata Assignments (15% of the final grade; online, approximately each week)

4.   Short Quizzes (10% of the final grade; online, approximately each other week; the lowest- score quiz will be dropped)

5.   Empirical Team Project (15% of the final grade)

Built-in grade flexibility:

Active participation in class is encouraged and rewarded, such as asking interesting questions related to the material and answering my questions in class. If a student exhibits a very active participation in class, the participation score will be weighed higher in the final grade.

Note on missed midterm exams: There will be no makeup exam for the midterm exams.  If you  miss a midterm, then the points for the missed exam will be automatically added to your final    exam. If a student misses the final exam, I must be contacted on the day of the exam and every effort must be made to take the makeup exam as soon as possible, to avoid an incomplete grade in the course. Exams will be given in class in person unless otherwise indicated.

Preparing for the Exams:

The structure of knowledge in mathematical statistics is strongly hierarchic in that each successive lecture tends to build on prior material in a rather systematic fashion.  As such it is very easy to fall behind if you miss a class and do not study the missed material before the subsequent lecture.  All exams will be based on questions drawn from the material covered in the textbook, lectures, and problem sets (including the assigned homework problems and in-class Stata assignments).  In other words, all material associated with the course may appear on exams, including lecture material that is not in the textbook (please note that all supplemental materials will be posted on blackboard).

Quizzes (online format):

Short online quizzes are 20-minute tests based on the recently covered material only and

formatted as multiple choice and true/false questions. The links to quizzes are under the

respective week learning module (folder) on blackboard course site. Read the instructions

carefully before taking the quiz. Quizzes are to be submitted via blackboard link online. Late

submissions will not be graded (resulting in a zero score for the late quiz). The due date will be  clearly indicated for each assignment; the deadline is firm. Late submissions will not be graded.

Once again: absolutely no make-ups for the missed quizzes. However, the lowest-score quiz will be dropped. So do not worry if you happened to miss one quiz – your quiz grade will not be affected in case if you get sick.

Homework Assignments (problem sets; online format):

It is encouraged that students work together on the homework assignments because better

learning of the material usually occurs through student discussion and interaction. Homework

assignments will be posted on the course site and will require the on-line submission by the end of a due date (indicated in the assignment link). The online format of the homework

assignments will be like that of the quizzes. The only difference is that the homework

assignment will not have a time limit (i.e., you do not need to complete the assignment in one setting within 20 minutes) and there will be the unlimited number of attempts (only two in

quizzes, with the second attempts only for technical issues during the first attempt). Homework assignments are to be submitted via blackboard assignment online. Late assignments will not

be graded (due date will be clearly indicated for each assignment). Once more: the deadline is firm. Late assignments will not be graded. NO extra projects for the missed homework will be  given.

Empirical homework: Stata Assignments (print-out format): Stata assignments will be posted on the course site, following Stata session in class (please feel free to seek TF’s help on all your

Stata assignments; cooperation with classmates is also encouraged). Just like with the

theoretical homework assignments, late Stata assignments will not be graded (due date will be clearly indicated for each assignment). Once more: the deadline is firm. Late Stata assignments will not be graded.

Final Project: The individual empirical projects will be an important part of the course, that will be built on the empirical assignments in Stata and will allow the students to fill the gap between the statistical theory and applied data analysis. The details will be explained in the class. During one of the Stata sessions, I will provide the students with the exemplary questions they will need to address in their final project.

Students with Documented Disabilities: If you have a disability that necessitates extra time for exams, or any other accommodations, you will need to give me a note from the BU office of Disabilities Services at least one week before exam so that I can make necessary arrangements.

Academic conduct. The Boston University academic conduct policies are available at http://www.bu.edu/academics/policies/academic-conduct-code/

Tentative Course Outline

I.           Basic Concepts of Probability Theory.

II.          Discrete random variables and their probability  distributions.

III.         Continuous random variables and their probability distributions.

IV.         Foundations of Bayesian analysis.

V.         Sampling and sampling distributions. Central limit theorem and law of large numbers.

VI.         Point versus interval estimation. Construction of confidence intervals.

VII.       Methods of estimation (least squares, method of moments, maximum likelihood)

VIII.      Estimators and their properties.

IX.         Parametric hypotheses testing.

X.          Bivariate regression analysis (time permitting).

XI.         Empirical data analysis and presentation – concepts and implementation in Stata.

XII.       Tentatively (subject to change):

Midterm #1 is on February 18, in class and midterm #2 is on March 18th, in class

XIII.       Final exam is at 3pm-5pm, on Tuesday, May 6, in class.