This course introduces the students to both descriptive and inferential statistics. Emphasis is placed on the practical use of statistics in the collecting, organizing, analyzing and interpreting of data. Students will learn standard topics such as sampling, bias, organization of data, measures of central tendency and dispersion, correlation and regression, probability, normal and standard normal distributions, confidence intervals and hypothesis testing.
By the end of this course, you will be able to:
Each week has homework assignments aligned with the content modules. These will be completed in Brightspace.
Each week, you will participate in discussions in which you will apply statistics skills and respond to your peers.
There is a course project that is broken up into 3 parts. Part 1 is due in Module 6 (Week 2), Part 2 is due in Module 12 (Week 5) and Part 3 is due in Module 16 (Week 6). You must complete each part of the project in order (ie: you will not be able to access Part 2 materials until Part 1 has been submitted).
Your grade in this course will be determined by the following criteria:
| Assignment | Points | Percentage of Grade |
|---|---|---|
| Weekly Discussions (6 discussions, 30 points each) | 180 | 15% |
| Week 6 Reflection Discussion | 40 | 4% |
| Homework Assignments (15 modules, 32 points each) | 480 | 48% |
| Statistics Project (3 parts, 100 points each) | 300 | 30% |
| Total | 1000 | 100% |
| Grade | Points Grade | Point Average (GPA) |
| A | 93 – 100% | 4.00 |
| A- | 90 – 92.9% | 3.75 |
| B+ | 87 – 89.9% | 3.50 |
| B | 83 – 86.9% | 3.00 |
| B- | 80 – 82.9% | 2.75 |
| C+ | 77 – 79.9% | 2.50 |
| C | 73 – 76.9% | 2.00 |
| C- | 70 – 72.9% | 1.75 |
| D | 60 – 69.9% | 1.00 |
| F | 00 – 59.9% | 0.00 |
Week 1: May 18 – May 24
Week 2: May 25 – May 31
Week 3: Jun 1 – Jun 7
Week 4: Jun 8 – Jun 14
Week 5: Jun 15 – Jun 21
Week 6: Jun 22 – Jun 26 <<Friday
All assignments are due weekly by 11:59 PM ET at the designated times and days recorded below.
| Week | Modules/Assignments | Due Dates |
| 1 |
Modules 1, 2, and 3 Week 1 Discussions:
Homework: Modules 1, 2, and 3 Select topic for Statistics Project |
Discussion (Initial Post) – Friday, 11:59 PM EST Discussions (Response Posts) – Sunday, 11:59 PM EST Homework – Sunday, 11:59 PM EST |
| 2 |
Modules 4, 5, and 6 Week 2 Discussion:
Homework: Modules 4, 5, and 6 Statistics Project Part 1 due |
Discussion (Initial Post) – Friday, 11:59 PM EST EST Discussion (Response Posts) – Sunday, 11:59 PM EST Homework – Sunday, 11:59 PM EST Statistics Project Part 1 – Sunday, 11:59 PM EST |
| 3 |
Modules 7, 8, and 9 Week 3 Discussion:
Homework: Modules 7, 8, 9 |
Discussion (Initial Post) – Friday, 11:59 PM EST Discussion (Response Posts) – Sunday, 11:59 PM EST Homework – Sunday, 11:59 PM EST |
| 4 |
Modules 10 and 11 Week 4 Discussion:
Homework: Modules 10 and 11 Begin working on Statistics Project Part 2 |
Discussion (Initial Post) – Friday, 11:59 PM EST Discussion (Response Posts) – Sunday, 11:59 PM EST Homework – Sunday, 11:59 PM EST |
| 5 |
Modules 12, 13 and 14 Week 5 Discussion:
Homework: Modules 12, 13, 14 Statistics Project Part 2 due on FRIDAY |
Discussion (Initial Post) – Friday, 11:59 PM EST Discussion (Response Posts) – Sunday, 11:59 PM EST Statistics Project Part 2 – Friday, 11:59 PM EST Homework – Sunday, 11:59 PM EST
|
| 6 |
Modules 15 and 16 Week 6 Discussion:
Homework: Modules 15 and 16 Statistics Project Part 3 due |
Discussion (Initial Post) – Wednesday, 11:59 PM EST Discussion (Response Posts) – FRIDAY, 11:59 PM EST Homework – FRIDAY, 11:59 PM EST Statistics Project Part 3 – FRIDAY, 11:59 PM EST |
Your Student Support Specialist is a resource for you. Please don't hesitate to contact them for assistance, including, but not limited to course planning, current problems or issues in a course, technology concerns, or personal emergencies. If you are a current UNE undergraduate taking online Summer Session courses, please continue to work with your Advisor and include them on your outreaches.
Questions? Email: summersessiononline@une.edu.
Your student support specialist monitors course progression and provides assistance or guidance when needed. They can assist questions regarding ordering course materials, University policies, billing, navigating the course in Brightspace, and more.
To request an accommodation a student needs to go through the process with our UNE office. If the student has a current/already established accommodation in place with UNE it is the responsibility of the student to notify the program at summersessiononline@une.edu to ensure it is applied properly.
If you need to inquire about a possible accommodation, please reach out to the Student Access Center by calling 207-221-4418 or send an email to pcstudentaccess@une.edu.
If you are a current UNE undergrad, please continue to work with your coordinator at bcstudentaccess@une.edu and ensure any accommodations you have in place - are put in place for your online Summer Session course(s).
Togetherall is a 24/7 communication and emotional support platform monitored by trained clinicians. It’s a safe place online to get things off your chest, have conversations, express yourself creatively, and learn how to manage your mental health. If sharing isn’t your thing, Togetherall has other tools and courses to help you look after yourself with plenty of resources to explore. Whether you’re struggling to cope, feeling low, or just need a place to talk, Togetherall can help you explore your feelings in a safe supportive environment. You can join Togetherall using your UNE email address.
Students should notify their Student Support Specialist and instructor in the event of a problem relating to a course. This notification should occur promptly and proactively to support timely resolution.
ITS Contact: Toll-Free Help Desk 24 hours/7 days per week at 1-877-518-4673.
Check Brightspace for specific instructor and support specialist contact information.
Online students are required to submit a graded assignment/discussion prior to Sunday evening at 11:59 pm EDT of the first week of the term. If a student does not submit a posting to the graded assignment/discussion by 11:59 pm EDT on Sunday of the first week, the student will be automatically dropped from the course for non-participation.
Your course may have proctored exams. For all proctored exams, an external camera is required. Please see the course for the exact exam requirements, test-taker guidance, proctoring format, and allowances (such as calculators or whiteboards, as indicated in the course). https://success.une.edu/science-prerequisites/honorlock/
Information about exam attempts can be found in your course.
A schedule of lectures and assignments is included in this syllabus.
Courses in the program are equivalent to one-semester courses designed to be completed in 6 or 12 weeks.
Please review the technical requirements for UNE Online Programs: Technical Requirements.
Please review the policies in your confirmation email. Contact summersessiononline@une.edu with any questions.
Students are expected to attempt and complete all graded assignments and proctored exams by the end date of the course.
Unless stated otherwise by your faculty: Late assignments will be accepted up to 3 days late; however, there is a 10% grade reduction (from the total points) for the late submission. After three days, the assignment will not be accepted. Discussion posts: If the initial post is submitted late, but still within the discussion board week, there will be a 10% grade reduction from the total discussion grade (e.g., a 3-point discussion will be reduced by 0.3 points). Any posts submitted after the end of the Discussion Board week will not be graded. Please make every effort ahead of time to contact your instructor if you are not able to meet an assignment deadline. Arrangements for extenuating circumstances may be considered by faculty.
Due to the Family Educational Rights and Privacy Act, only the student may request official transcripts. This may be done online by going to the University of New England Registrar website and following the directions on the page.
The University of New England values academic integrity in all aspects of the educational experience. Academic dishonesty in any form undermines this standard and devalues the original contributions of others. It is the responsibility of all members of the University community to actively uphold the integrity of the academy; failure to act, for any reason, is not acceptable.
Academic dishonesty includes, but is not limited to the following:
Charges of academic dishonesty will be reviewed by the College. Penalties for students found responsible for violations may depend upon the seriousness and circumstances of the violation, the degree of premeditation involved, and/or the student’s previous record of violations. Appeal of a decision may be made to the Dean whose decision will be final. Student appeals will take place through the grievance process outlined in the student handbook.
Generative AI (GenAI) applications (like ChatGPT) have proven to be powerful and effective tools, and students are encouraged to become familiar with and use them. However, as with any tool, students must use GenAI in ways that support learning, not replace it. Learning to use AI responsibly and ethically is an important skill in today’s society.
In their courses, students are not allowed to use advanced automated tools, such as generative AI tools, on assignments unless explicitly directed to do so. Each student is expected to complete each assignment, including labs and quizzes as applicable, without substantive assistance from others, including automated tools.
Using AI-content generators to complete assignments without proper attribution violates academic integrity. By submitting assignments in UNE courses, you pledge to affirm that they are your own work and you attribute use of any and all tools and sources.
Unauthorized Use
Unauthorized use of AI is treated as a violation of academic integrity.
Citing AI Use
If permitted, students should indicate and cite any use of AI tools.
Instructor Responsibility
Instructors should clearly reiterate, using UNE AI Use Policy, how students can use AI tools in their courses, and communicate this policy to students at the beginning of the semester.
Student Responsibility
Students must follow the academic integrity policy of the University of New England.