Syllabus

Master of Biomedical Science

MBS 636: Biostatistics

Credits - 3

Description

This course introduces the summarization, analysis, interpretation, and presentation of research data. Topics include sampling, experimentation, numerical and graphical descriptive statistics, confidence intervals, and hypothesis testing. Inferential hypothesis tests introduced include correlation, analysis of 2-way tables, t-tests, ANOVA, and linear and logistic regression. At the end of the course, students should be able to use and evaluate the more commonly used statistical tests in relevant research publications and communicate clearly about statistical results within research teams.

Materials

A STATA license is required for this course. You will be eligible for the student license with your UNE email address. The 6-month STATA/BE license is the recommended option for this course

All other resources are provided in Brightspace

Learning Objectives and Outcomes

Course Objectives

  • Define basic statistical concepts, including measures of central tendency and variation, and techniques for visualizing data.
  • Explain population sampling and sources of error in health studies
  • Compare different study designs, including experimental design.
  • Discuss hypothesis testing, including the calculation and interpretation of p-values and confidence intervals for hypothesis testing.
  • Perform and interpret the results from chi-square and fisher’s exact testing, T-tests, ANOVA, correlation and linear regression, and logistic regression.

Assignments

Discussions

There is a discussion assignment each week that requires students to engage with their peers about topics related to the course content. The initial post for each week will have students find a publication that used the statistical measure(s) covered in the week and discuss their use and interpretation. Students must then respond to at least two of their peers before the end of the week to further build on the discussion.

Weekly Assignments

Each week, students will complete an assignment that uses the statistical measures covered during the week. The Framingham Heart Study will be the basis for the data being analyzed. Most weeks, this analysis will be completed in STATA. Students will need to complete the steps in the assignment, download the code and any visualizations, and then interpret the results, collating all parts into a single document for grading. 

Proctored Exams

There are two proctored exams in this course. The midterm covers the first three weeks of the course, and the final covers the final four weeks. Proctoring is done through Honorlock.

You will have two attempts for the Midterm and Final Exams. The first attempt of the midterm must be taken by the due date, while the second attempt may be taken at any time before the end of the course. However, it is encouraged to take the second attempt soon after the first, as this material is fundamental to the remaining units.

Grading Policy

Your grade in this course will be determined by the following criteria:

Grade Breakdown

CategoryPointsPercentage
Academic Integrity Agreement80.8%
Discussions (7 @ 36 points each)25225.2%
Weekly Assignments (7 @ 70 points each)49049.0%
Proctored Exams (2 @ 125 points each)25025.0%
Total1000100%

Schedule

Course Schedule

Summer A

  • Course Start date: 5/13/2026
  • Course End date: 6/28/2026

Week 1: Wednesday – Sunday
Week 2: Monday – Sunday
Week 3: Monday – Sunday
Week 4: Monday – Sunday
Week 5: Monday – Sunday
Week 6: Monday – Sunday
Week 7: Monday – Sunday

Review specific assessment instructions in Brightspace. All learning materials are provided within the course. 

 

Week 1: Basic Statistical Concepts

Learning Objectives

  1. Define basic statistical concepts, including measures of central tendency and variation, and techniques for visualizing data.
  2. Import data and run descriptive analyses in STATA.
  3. Discuss the use of basic statistical concepts in public-facing articles.

Assignments Due

  • Week 1 Discussion: Introductions; Finding and interpreting measures of central tendency and variation 
    • Initial Post due by Friday at 11:59 PM ET
    • Two peer responses due by Sunday at 11:59 PM ET
  • Week 1 Assignment: Calculating measures of central tendency and variation
    • Due by Sunday at 11:59 PM ET

Week 2: Population Sampling, Sources of Error, and Study Designs

Learning Objectives

  1. Explain population sampling and related sources of error in health studies.
  2. Compare different study designs, including experimental designs like randomized control trials.
  3. Create graphs to visualize variable distribution.

Assignments Due

  • Week 2 Discussion: Finding and interpreting measures of central tendency and variation from scholarly sources
    • Initial Post due by Friday at 11:59 PM ET
    • Two peer responses due by Sunday at 11:59 PM ET
  • Week 2 Assignment: Creating graphs using STATA
    • Due by Sunday at 11:59 PM ET

Week 3: Measures of Disease Frequency and Association

Learning Objectives

  1. Discuss hypothesis testing, including the application of p-values and confidence intervals to hypothesis testing.
  2. Calculate and interpret measures of disease frequency and association.
  3. Interpret p-values and confidence intervals.

Assignments Due

  • Week 3 Discussion: Find a scholarly article with p-values and interpret the value
    • Initial Post due by Friday at 11:59 PM ET
    • Two peer responses due by Sunday at 11:59 PM ET
  • Week 3 Assignment: Calculating and interpreting measures of disease frequency and association
    • Due by Sunday at 11:59 PM ET
  • Proctored Midterm Exam
    • Due by Sunday at 11:59 PM ET

Week 4: Chi-square and Fisher’s Exact Testing

Learning Objectives

  1. Perform and interpret the results from chi-square and Fisher’s exact testing.
  2. Interpret the results of chi-square and Fisher’s exact testing in peer-reviewed articles.

Assignments Due

  • Week 4 Discussion: Find an article that uses chi-square or Fisher’s exact test and interpret
    • Initial Post due by Friday at 11:59 PM ET
    • Two peer responses due by Sunday at 11:59 PM ET
  • Week 4 Assignment: Chi-square and Fisher’s exact testing
    • Due by Sunday at 11:59 PM ET

Week 5: T-Tests and ANOVA

Learning Objectives

  1. Perform and interpret the results from two-sample t-tests and ANOVA.
  2. Perform a Bonferroni test.
  3. Analyze the use of two-sample t-tests and ANOVA in peer-reviewed articles.

Assignments Due

  • Week 5 Discussion: Find an article that uses a T-test or ANOVA and interpret
    • Initial Post due by Friday at 11:59 PM ET
    • Two peer responses due by Sunday at 11:59 PM ET
  • Week 5 Assignment: T-tests and ANOVA
    • Due by Sunday at 11:59 PM ET

Week 6: Correlation and Linear Regression

Learning Objectives

  1. Perform and interpret the results from correlation and linear regression.
  2. Analyze the use of linear regression in peer-reviewed articles.

Assignments Due

  • Week 6 Discussion: Find a peer-reviewed article that uses a linear regression and interpret
    • Initial Post due by Friday at 11:59 PM ET
    • Two peer responses due by Sunday at 11:59 PM ET
  • Week 6 Assignment: Correlation and Regression
    • Due by Sunday at 11:59 PM ET

Week 7: Logistic Regression

Learning Objectives

  1. Perform and interpret the results from logistic regression.
  2. Analyze the use of logistic regression in peer-reviewed articles.

Assignments Due

  • Week 7 Discussion: Find a peer-reviewed article that uses a logistic regression and interpret the results
    • Initial Post due by Friday at 11:59 PM ET
    • Two peer responses due by Sunday at 11:59 PM ET
  • Week 7 Assignment: Logistic Regression
    • Due by Sunday at 11:59 PM ET
  • Proctored Final Exam
    • Due by Sunday at 11:59 PM ET

Student Resources

Online Student Support

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.

UNE Libraries:

UNE Student Academic Success Center

UNE's Student Academic Success Center (SASC) offers a range of free online services to support your academic achievement. Writing support, ESOL support, study strategy and learning style consultations, as well as downloadable resources, are available to all matriculating students. To make an appointment for any of these services, go to une.tutortrac.com. For more information and to view and download writing and studying resources, please visit:

Accommodations

Any student who would like to request, or ask any questions regarding, academic adjustments or accommodations must contact the Student Access Center at (207) 221-4438 or pcstudentaccess@une.edu. Student Access Center staff will evaluate the student's documentation and determine eligibility of accommodation(s) through the Student Access Center registration procedure.

Online Peer Support

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.

Information Technology Services (ITS)

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.

Career Ready Program

The College of Professional Studies supports its online students and alumni in their career journey!

The Career Ready Program provides tools and resources to help students explore and hone in on their career goals, search for jobs, create and improve professional documents, build professional network, learn interview skills, grow as a professional, and more. Come back often, at any time, as you move through your journey from career readiness as a student to career growth, satisfaction, and success as alumni.

Policies

Use of Artificial Intelligence

Generative AI (GenAI) applications (e.g., ChatGPT, Gemini, Copilot, and similar tools) are increasingly used in academic and professional environments. In the MBS program, AI tools may be used in limited and transparent ways that support learning. They may not substitute for independent scientific reasoning, writing, analysis, or demonstration of mastery of course learning outcomes.

The use of AI in academic work falls under the MBS Academic Integrity Agreement and must align with our commitment to honest, responsible, and professional scholarship. Students should always be able to demonstrate the originality of submitted work if improper use of AI is suspected.

In situations where AI tools are used as a resource, students must:

  • Ensure that all submitted academic work demonstrates their own learning and mastery of course objectives.
  • Acknowledge every instance of AI use in-text at the point where it was used. AI use should not be listed in the References section.
  • Include a brief description of how the AI tool was used, followed by the AI tool name, model/version (if available), manufacturer/owner, and date used in parentheses. Students should consult the AI citation section of the AMA style guide for additional details.
  • Take full responsibility for the accuracy, interpretation, and conclusions presented in their work.
  • Critically evaluate AI output for errors, bias, and potential risks to vulnerable or underrepresented populations.
  • Follow any additional course or assignment-specific AI restrictions provided in assignment instructions.

Failure to acknowledge AI use in submitted work constitutes a violation of academic integrity and will be treated as plagiarism under the MBS Academic Integrity Policy and Student Handbook.

Penalties for AI misuse will follow the MBS program's academic integrity escalation structure. A first offense will result in a zero on the assignment with no opportunity for resubmission. Additional or severe violations may result in course failure and/or referral for program-level review, which may include dismissal from the program.

Turnitin Originality Check and Plagiarism Detection Tool

The College of Professional Studies uses Turnitin to help deter plagiarism and to foster the proper attribution of sources. Turnitin provides comparative reports for submitted assignments that reflect similarities in other written works. This can include, but is not limited to, previously submitted assignments, internet articles, research journals, and academic databases.

Make sure to cite your sources appropriately as well as use your own words in synthesizing information from published literature. Webinars and workshops, included early in your coursework, will help guide best practices in AMA citation and academic writing.

You can learn more about Turnitin in the guide on how to navigate your Similarity Report.

Technology Requirements

Please review the technical requirements for UNE Online Graduate Programs: Technical Requirements

Hardware

All proctored exams require the use of an external webcam to ensure a secure testing environment. Here is an example of a UNE approved external webcam. Please ensure compatibility with your computer before purchasing. Any external webcam with a wide-angle view (90° or greater) that can clearly show your face, hands, and workspace will meet this requirement. If you have questions regarding the external webcam requirement, please reach out to biomedicalscience@une.edu. Proctored exams completed with an internal webcam will not be credited.

Course Evaluation Policy

Course surveys are one of the most important tools that University of New England uses for evaluating the quality of your education, and for providing meaningful feedback to instructors on their teaching. In order to assure that the feedback is both comprehensive and precise, we need to receive it from each student for each course. Evaluation access is distributed via UNE email at the beginning of the last week of the course.

Late Policy

Assignments: 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 and your student support specialist if you are not able to meet an assignment deadline. Arrangements for extenuating circumstances may be considered by faculty.

Attendance Policy

6- to 8-week courses: Students taking online graduate courses through the College of Professional Studies will be administratively dropped for non-participation if a graded assignment/discussion post is not submitted before Sunday at 11:59 pm ET of the first week of the term. Reinstatement is at the purview of the Dean's Office.

10+ -week courses: Students taking online graduate courses through the College of Professional Studies will be administratively dropped for non-participation if a graded assignment/discussion post is not submitted before Friday at 11:59 pm ET of the second week of the term. Reinstatement is at the purview of the Dean's Office.

Student Handbook Online - Policies and Procedures

The policies contained within this document apply to all students in the College of Professional Studies. It is each student's responsibility to know the contents of this handbook.

UNE Online Student Handbook

UNE Course Withdrawal

Please contact your Enrollment and Retention Counselor if you are considering dropping or withdrawing from a course. Tuition charges may still apply. Students are strongly urged to consult with Student Financial Services, as course withdrawals may affect financial aid or Veterans benefits.

Academic Integrity

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. For information about plagiarism and academic misconduct, please visit UNE Plagiarism Policies.

Academic dishonesty includes, but is not limited to the following:

  1. Cheating, copying, or the offering or receiving of unauthorized assistance or information.
  2. Fabrication or falsification of data, results, or sources for papers or reports.
  3. Action which destroys or alters the work of another student.
  4. Multiple submissions of the same paper or report for assignments in more than one course without permission of each instructor.
  5. Plagiarism, the appropriation of records, research, materials, ideas, or the language of other persons or writers and the submission of them as one's own.

Charges of academic dishonesty will be reviewed by the Program Director. 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.