ALY6010:Probability Theory and Introductory Statistics
Hello, dear friend, you can consult us at any time if you have any questions, add WeChat: daixieit
Course Syllabus
Course Information
Course Title ALY6010: Probability Theory and Introductory Statistics
Course Number (CRN)
Term and Year
Start and End Dates
Credit Hours
Course Format
Location (if 100% online, note Northeastern’s learning management system, Canvas Login URL: https://canvas.northeastern.edu/)
Meeting Days/Times (if not 100% online)
Instructor Information
Full Name
NEU Email Address
(Virtual) Office Hours (include location, hours, days, or “Email me to schedule an appointment”)
Second Point of Contact
In the event that some concern about the course arises and is not addressed by the instructor, please contact:
Full Name – Dr. Thomas Goulding
NEU Email Address – t.goulding@northeastern.edu
Iffor any reason you wish to express a concern about anything that may impact your success in a course, first speak directly with your Instructor. If you need additional support, please contact your Academic Advisor.
NuFLEX Requirements
Should this course fall under the Hybrid NuFlex policy, please refer to any and all supplemental materials pertaining to class attendance, participation, and other aspects impacting student and/or instructor engagement. For additional information, please refer to your advisor.
Technical Requirements
Courses are available on Northeastern University’s Canvas at the following link: http://canvas.northeastern.edu. Canvas Technical support and resources including 24/7 phone (1-833-450- 3937), and chat can be found on the help icon in Canvas. Northeastern Technical support can be accessed at 617-373-4357 (xHELP) orhelp@northeastern.edu.
Each student is responsible for their access to the internet for purposes of this course and for research. Internet access is a required component of this course and will not be accepted as an excuse for missed work . If you know that you will be traveling, then make sure you plan accordingly.
Note regarding e-mail/voicemail: If you e-mail, please include your name and class title. Please allow up to 48 hours for an email reply. If you leave a voicemail, please remember to include your name, class title, and phone number.
Course Prerequisites
N/A
Course Description
Introduces statistics for business analytics from an analysis-of-data viewpoint. Topics include frequency distributions; measures of location; mean, median, mode; measures of dispersion; variance; graphic presentation; elementary probability; populations and samples; sampling distributions; categorical data; regression and correlation; and analysis of variance. Explores the use of statistical software in data analysis. Lab sessions emphasize hands-on application of probability and statistics in Excel and data problem solving with advanced Excel techniques.
Course Materials
Bluman Elementary Statistics: A Step by Step Approach 10th edition, McGrawHill ISBN 978-1-260-04200-9
R. Kabacoff, R in Action 2nd edition, Manning, ISBN 978-1-617-29138-8
Program Learning Outcomes (PLOs)
PLO1: Demonstrate the foundational knowledge and skills critical to pursue data analytics as a process in relation to statistics and math.
PLO2: Articulate and effectively defend the significance and implications of the work in data analytics in terms of challenges and trends in a local, national or global context.
SAIL Baseline Mapping
Enter 5 for Central, 4 for Significant, 3 for Moderate, 2 for Minimal, 1 for Potential, or 0 for None |
Enter 1 for Passive Engagement, 2 for Active Engagement, or 3 for Generative Engagement |
||||
Social Consciousness & Commitment |
Global Mindset |
Intellectual Agility |
Personal & Professional Effectiveness |
Well- Being |
Level of Engagement |
2 |
2 |
4 |
4 |
1 |
3 |
Refer to SAIL for Web at https://sail.northeastern.edu/about/
Course Learning Outcomes
Based on satisfactory completion of this course, a student should be able to:
CLO1: Develop strategic and operational questions based on the data and the need of the organization CLO2: Use data analysis techniques (hypothesis testing, correlation, t-testing, variance, and single variable linear regression) to answer research questions
CLO3: Use “R” to perform computations and a wide range of statistical techniques
CLO4: Interpret the results from data analysis techniques
CLO5: Explain the implications of the results from data analysis for the purpose of answering essential business questions
Expectations
• Workload
o One (1) academic credit requires 50 minutes a week of classroom or faculty instruction and about two hours of out of class student work for a 15-week course; 100 minutes a week of classroom or direct faculty instruction and about 3.5 hours of out of class student work for a 7.5-week course.
o For a three-credit course, students should expect 2.5 hours a week of classroom or faculty instruction and a minimum of 5 hours of out of class student work for a 15-week course; 5 hours of classroom or direct faculty instruction and a minimum of 10 hours of out of class student work for a 7.5-week course.
o APA citations
Attendance Policy
As the weekly class session is a vital part of the learning experience, all students are expected to attend every week, be on time for the start of class, and stay until the end ofclass.
However, in the event of extraordinary, legitimate and unavoidable situations, students may be excused for lateness or absence. Extraordinary, legitimate and unavoidable situations include personal illness, urgent family business, work-related issues, transportation-related issues, religious requirements. If at all possible, students should let the instructor know by e-mail about the excused absence or lateness before class.
Policy on late work
Each assignment is due on the date indicated - late assignments will not receive any points. There are no make-up dates, extensions, or re-works for the assignments after they are handed in, except for documented personal emergencies or special permission granted by the instructor in writing. Special permission must be requested in writing to the instructor at least two days prior to the due date of the assignment.
Course Methodology
Each week, you will be expected to:
1. Review the week's learning objectives.
2. Complete all assigned readings (approximate time spent: 2 hours).
3. Complete all lecture materials for the week (approximate time spent: 1.5 hours).
4. Participate in the Discussion Board (approximate time spent:1.5 hours).
5. Complete and submit all assignments and tests by the due dates (approximate time spent: 5-8 hours).
Participation/Discussion Board [ALL STUDENTS – ALL COURSE DELIVERY MODES]
• At least one Primary responses are due by 11:59pm EST on the Thursday of each week
• At least two secondary response are due by 11:59pm EST on the Sunday of each week
During each week, learners are required to post a “primary response” by Thursday, 11:59 P.M. (Eastern), and a minimum of two replies to the primary posts of other students by Sunday, 11:59 P.M. (Eastern) – a minimum of three postings for each discussion question. Primary responses that are posted after Thursday will not be accepted. Note that the replies for the week 6 discussions are due by the Saturday of week 6 by 11:59 P.M. (Eastern).
• The primary response should consist of a minimum of 200 words, and each reply should contain at least 80 words.
• Learners are expected to post their responses to the weekly discussion questions on at least two different days of the week so that there will be enough time for fruitful correspondences with the instructor and/or with other learners throughout the week.
• Last minute postings that are empty of substance and essence will result in significant point deductions.
• When responding to the Discussion forum, learners should support their comments with logical reasoning and with the techniques of data analysis. Simply stating that agree or disagree without further describing why will not be accepted as a valid discussion.
• Copying and pasting from any source into the discussion board is considered a form of plagiarism and is unacceptable.
To facilitate interaction, students are expected to review the online postings on a regular basis even after they have posted their own minimum required postings. Please treat your classmates and the instructors with the utmost respect. Inappropriate posts will be removed immediately. The instructor reserves the right to penalize students for repeated violations of the participation policy (and/or Academic Integrity Policy) within a course. In the discussion board and in class, high quality contributions advance the class discussions and do not simply summarize the material that was assigned. Quality contributions take into account not only the instructor’s questions but also yourclassmates’ contributions. Please be mindful that the Discussion Board is a space for academic exchanges. As a result, students are accountable for using proper and exacting punctuation, spelling, and grammar. In addition, you may be required to reference all outside sourcesin correct citation format. It is crucial that all participants maintain a high regard for proper decorum in the Discussion Board.
Evaluation Standards
All assignment rubric are included in the assignment documents and visible from the Canvas assignments
Grading
Graduate Programs Final Grading Scale
95-100% A |
87-89.9% B+ |
77-79.9% C+ |
69.9% or below F |
84-86.9% B |
74-76.9% C |
||
90-94.9% A- |
80-83.9% B- |
70-73.9% C- |
Grade Breakdown:
Title
Description
Grade (Pts or %)
1 |
Discussions |
6 total |
10% |
2 |
R Practice Assignments |
6 total |
20% |
3 |
Quizzes |
6 total |
10% |
4 |
Final Project and Milestone assignments |
2 milestone assignments and final project |
60% |
|
Total |
|
100% |
2023-04-15