Hello, dear friend, you can consult us at any time if you have any questions, add WeChat: daixieit

ADEC 7310 Data Analytics

Spring 2022

Course Description

This course is designed to introduce students to the concepts and data-based tools of statistical analysis commonly employed in Applied Economics. In addition to learning the basics of statistical and data analysis, students will learn to use the statistical software package Stata or R to conduct various empirical analyses. Our focus will be on learning to do statistical analysis, not just on learning statistics. The ultimate goal of this course is to prepare students well for ADEC 7320.01, Econometrics.

Course Delivery: online

Textbooks (with ISBN ) & Readings (Required)

All articles/handouts will be available in Canvas unless otherwise noted.

https://leanpub.com/os

Diez, D, Barr, C, Cetinkaya-Rundel, M. 2015. OpenIntro Statistics. 4 th Edition.

“OpenIntro Statistics 3rd Edition strives to be a complete introductory textbook of the highest caliber. Its core derives from the classic notions of statistics education and is extended by recent innovations. The textbook meets high quality standards and has been used at Princeton, Vanderbilt, UMass Amherst, and many other schools.”

Other equipment / material requirements (optional)

R Statistical Software (Free: https://cran.r-project.org/)

Textbooks & Readings (Recommended)

None

Canvas

Canvas is the Learning Management System (LMS) at Boston College, designed to help faculty and students share ideas, collaborate on assignments, discuss course readings and materials, submit assignments, and much more - all online. Your course will make significant use of Canvas this semester; you should familiarize yourself with this important tool. For more information and training resources for using Canvas, click here. 

In the case of any technical difficulties or concerns, please contact [email protected] or 617-552-HELP (4357) for immediate assistance. Canvas requires particular computer specifications and wifi access. It is important that you plan accordingly.

NOTE: If a face-to-face class session is cancelled, please go to Canvas to learn how that session will be taught.

Course Outcomes

By the end of this course, students will:

1. Demonstrate competency across cultural settings and will learn the impact of culture, gender, and age in ADEC 7310 as demonstrated by appropriate synchronous and asynchronous communication.

2. Demonstrate ethical competency pertaining to data analysis as demonstrated by assignment submissions and projects.

3. Apply intermediate level, practical knowledge of data analysis and econometrics, as demonstrated by assignments and projects.

4. Apply a statistical/econometric software package, as demonstrated by use of R in assignments and projects.

Assessments and Grading Policy

In this course, there are four graded components.

Weekly discussions (Objectives 1 through 4)

Weekly assignments (Objectives 1 through 4)

Midterm (Objectives 1 through 4)

Final (Objectives 1 through 4)

Discussions (8 x 2%=16%). Post your initial response (written or video) to Discussion #1 early in the learning week - no later than WEDNESDAY at 11:59 pm EST; then respond to a minimum of two other posts (text only) from classmates by SUNDAY at 11:59 pm EST. No late posts are accepted. The rubric follows:

Criteria                                    Not completed                     Below Graduate Level               Graduate Level

Initial post answers the             0                                        .5                                           1

requirement

Follow-up discussions                0                                        .5                                           1

contribute to learning

Total                                        0                                         1                                           2

Assignments (5 x 10% = 50%). Each week by SUNDAY at 11:59 pm EST, you will be required to submit homework based on the week’s learning. The homework will be completed using R where appropriate.

Midterm Assignment (17%). During week 4, you will be assigned a take-home, applied data analysis midterm. The rubric for this midterm will be posted to Canvas. The assignment is due SUNDAY at 11:59 pm EST at the end of week 4.

Final Assignment (17%). During week 7, you will compete in an applied data analysis final. The rubric for this final will be posted to Canvas. The assignment is due SUNDAY at 11:59 pm EST at the end of week 7.

Deadlines and Late Work

Due to the compressed nature of this course, late homework is accepted up to 5 days after the assignment due date. The penalty without a priori coordination is 20% / day. No late examinations or discussion posts are accepted.

Course Assignments

Most students should spend nine hours each week working to master the content in this course. The weekly schedule and assignments follow.

Assessment Grading Breakdown Course Component               Percentage

Discussion Participation (8 total x 2% each)                           16%

Assignments (5 total x 10% each)                                         50%

Midterm Assignment                                                            17%

Final Assignment                                                                 17%

Extra credit is not provided for graduate-level work.

The graduate grading system for Woods College is as follows.

A (4.00), A- (3.67)

B+ (3.33), B (3.00)

B- (2.67)

C (2.00)

F (.00)

All students can access final grades through Agora after the grading deadline each semester. Students who complete course evaluations can access grades earlier, as they are posted.

Course Assignments

Most students should spend nine hours each week working to master the content in this course. The weekly schedule and assignments follow.

Course Schedule

Topic                                                               Reading                       Homework            Discussion

Introduction to Data / Summarizing Data            Chapters 1 and 2                  #1                 #1 / #2

Probability                                                       Chapter 3                            #2                     #3

Distributions of Random Variables                      Chapter 4                             #3                    #4

Foundations for Inference                                 Chapter 5                         Midterm                 #5

Inference for Categorical / Numerical Data          Chapter 6 and 7                   #4                     #6

Introduction to Regression                                Chapter 8                            #5                      #7

Multiple and Logistic Regression                         Chapter 9                           Final                    #8

Participation/Attendance

Participating in class is an important component of learning. Students are expected to participate in and complete all discussions, assignments, and assessments. Grading rubrics apply for late discussion posts. 

Consistent with BC’s commitment to creating a learning environment that is respectful of persons of differing backgrounds, we believe that every reasonable effort should be made to allow members of the university community to observe their religious holidays without jeopardizing their academic status. Students are responsible for reviewing course syllabi as soon as possible, and for communicating with the instructor promptly regarding any possible conflicts with observed religious holidays. Students are responsible for completing all class requirements for days missed due to conflicts with religious holidays.

Accommodation and Accessibility

Boston College is committed to providing accommodations to students, faculty, staff and visitors with disabilities. Specific documentation from the appropriate office is required for students seeking accommodation in Woods College courses. Advanced notice and formal registration with the appropriate office is required to facilitate this process. There are two separate offices at BC that coordinate services for students with disabilities:

● The Connors Family Learning Center (CFLC) coordinates services for students with LD and ADHD.

● The Disabilities Services Office (DSO) coordinates services for all other disabilities.

Find out more about BC’s commitment to accessibility at www.bc.edu/sites/accessibility.

Scholarship and Academic Integrity

Students in Woods College courses must produce original work and cite references appropriately. Failure to cite references is plagiarism. Academic dishonesty includes, but is not necessarily limited to, plagiarism, fabrication, facilitating academic dishonesty, cheating on exams or assignments, or submitting the same material or substantially similar material to meet the requirements of more than one course without seeking permission of all instructors concerned. Scholastic misconduct may also involve, but is not necessarily limited to, acts that violate the rights of other students, such as depriving another student of course materials or interfering with another student’s work. Please see the Boston College policy on academic integrity for more information.

Health Integrity Policy

Particularly during this time of the COVID-19 pandemic, we must take even greater measures to care for ourselves, for each other and for our community. Therefore, we are asking that all Woods College students care for themselves by monitoring their health and washing their hands thoroughly before class. We ask that students demonstrate their care for others by wearing a mask/cloth face covering at all times when in the buildings on campus, maintain appropriate physical distancing and to not attend class if feeling unwell.