Syllabus

Schedule

Week 1: Aug 24 – Aug 31
Week 2: Aug 31 – Sep 7
Week 3: Sep 7 – Sep 14
Week 4: Sep 14 – Sep 21
Week 5: Sep 21 – Sep 28
Week 6: Sep 28 – Oct 5
Week 7: Oct 5 – Oct 12
Week 8: Oct 12 – Oct 16

Week 1: Fundamentals of Biostatistics in Public Health Research

Weekly Outcomes:

• Review datasets for use in a report and the development of research questions.
• Determine the types of variables in a dataset for use in the development of a report.

Readings:

• Sullivan Textbook: Chapter 1
• Review the website in the course about types of data: Laerd Statistics

Videos:

• Video: Course Introduction [Dr. Liam O’Brien]
• Weekly Lecture: Week 1 [Dr. Liam O’Brien]
• Research Questions [Dr. Liam O’Brien]

Assignments:

• Discussion: Begin by introducing yourself to the class. What is your background in Biostatistics? What are you most excited about? In what ways will this course come in handy for your Public Health Career? 
• Discussion: Introduction to Final Project – Choosing Variables, Developing a Question) — For the final project (and associated discussions and assignments) you will work with pre-existing data from one of these three studies:
  • The Framingham Heart Study, a long-term ongoing cohort study which collects data to examine risk factors associated with cardiovascular disease
  • The Bay State Medical Center Birth Weight Study, a case control study which collected data to examine risk factors associated with low birth weight
  • The Nurses Health Study, which contains a subset of data collected to examine possible relationships between various risk factors and breast cancer.

Enter the Final Project Datasets and Supplemental Materials folder (also available via the sidebar) and read the two MS-Word documents there which describe the background of these two studies and provide a variable codebook for the data available. After reviewing these documents and the Excel files associated with them, select whichever one of these datasets aligns best with your research interests.

Then, in your initial post:

• Identify 10 variables in your selected dataset that might be of interest
• Note whether each variable is categorical (nominal, dichotomous, ordinal) or continuous (interval, ratio) as described in the ‘Laerd Statistics’ reading this week
• Propose 5 research questions that could be asked using these variables (note that each question should reference two variables)
• Explain why you find these questions of interest

For example, using data from the Birth Weight Dataset, one might ask if there is an association between the presence of uterine irritability (categorical-dichotomous) and low birth weight (categorical-dichotomous), as uterine irritability is a risk factor for giving birth to low weight babies. 

Week 2: Studies and Experiments

Weekly Outcomes:

• Examine a research paper to determine if it is an observational study or an experiment.
• Describe how a representative sample is taken from a population through the description of a study provided in a research paper.
• Review a research paper to understand how the experiment of study was designed.
• Develop research questions based upon a chosen dataset for the development of a report. 

Readings:

• Sullivan Textbook: Chapters 2.1 through 2.4
  Abram KM, Teplin LA, McClelland GM, Dulcan MK. Comorbid
• Psychiatric Disorders in Youth in Juvenile Detention. Arch Gen Psychiatry. 2003;60(11):1097-1108. 

Videos:

• Weekly Lecture: Week 2

Assignments:

• Discussion: Research Questions — Referring back to the feedback you received from your peers and your instructor on your potential research questions and their associated variables, finalize three research questions relating to your selected dataset. Make sure the variables used in the final questions you select are of the following format:
  • Continuous response and continuous explanatory variable
  • Categorical response and categorical explanatory variable
  • Continuous response and categorical explanatory variable (note: the categorical variable must be dichotomous for this question)

Each research question should have a clear explanatory and response variable. Review, as necessary, the ‘Laerd Statistics’ reading from last week which explains data types and the difference between response variables (also referred to as dependent or outcome variables) and explanatory variables (also referred to as independent or predictor variables).

Then, in your initial post, list your three finalized research questions, indicating the variable types.

For example, using data from the Framingham Heart Study dataset, one question might be: ‘Is there a significant difference in total serum cholesterol levels [TOTCHOL] (continuous-ratio) (response) between smokers and non-smokers [CURSMOKE] (categorical-dichotomous) (explanatory)?’

In your response post to your peers, provide feedback on their finalized research questions, which will become the foundation of each student’s final project. Consider the following questions as you review your peers’ research questions: 

• • Is each research question clearly stated? 
  • Does each research question relate to the dataset?
  • Do the three research questions meet the data type requirements? 
  • Does each research question identify response and explanatory variables correctly?

 

• Written Assignment: In this assignment, review the “Comorbid Psychiatric Disorders in Youth in Juvenile Detention” paper.  Read through the article paying careful attention to the section describing how the subjects were selected and the study or experiment was designed, then answer the following questions.
  • What is the population that the researchers are studying?
  • Describe how the data was collected:
  • How was the sample chosen?
  • Do you think the sample is representative of the population?  Explain.
  • Is this an experiment or a study? Make sure to clearly explain how you came to this conclusion and support your claim.
  • Describe how this experiment/study was designed and what type of experiment/study it is.
  • Do you think the results of this experiment/study could be applied to youth detention centers, in your own state or region?  Explain.

Your written response should be no more than 2 double-spaced pages. This assignment will be graded using the Week 2 Written Assignment Rubric.

Note: As you complete this assignment, keep in mind that the formatting of the journal article you are reviewing is similar to what you will be submitting for your final project.

Week 3: Summarizing Data

Weekly Outcomes:

• Utilize appropriate graphical techniques to display data.
• Utilize appropriate numerical summaries to summarize data.
• Utilize appropriate verbal summaries to interpret results

Readings:

• Sullivan Textbook: Chapter 4 and 12

Videos: 

• Week 3 Lecture
• Intro Bar Charts and Tables
• Histograms and Box Plots
• Scatterplots and Correlation

Assignments: 

• Written Assignment:

An important first step in data analysis is to examine the variables that will be used to answer research questions by creating numerical and graphical summaries.  To do this, you will utilize SAS.  

Be sure you review the lecture and the SAS tutorial videos before completing this assignment. 

Examine the numerical and graphical summaries you created.  Provide a one-sentence verbal summary for each indicating what it tells you about the data.

Please submit the research questions, numerical summaries, graphical summaries, and verbal summaries all in a single Word document.  

Week 4: Confidence Intervals

Weekly Outcomes: 

• Construct confidence intervals using SAS.
• Interpret confidence intervals.

Readings: 

• Sullivan Textbook: Chapters 6.1 through 6.6.1 (not 6.6.2 or 6.6.3)

Videos: 

• Week 4 Part 1
• Week 4 Part 2

Assignments:

• Discussion: Confidence Intervals — The focus this week is on confidence intervals. Utilize the following information and answer the questions below. A 95% confidence interval obtained from a sample of 100 outpatients for the true population mean normal mean systolic blood pressure is given by (114 mmHG, 120 mmHG). 
  • Provide a correct interpretation of this interval. Can you think of other interpretations that would also be correct?
  • This confidence interval came from a single sample, would we get the same interval if we obtained a different set of 100 patients? What does this imply about your interpretation of the given interval? 
  • If we wanted a 99% confidence interval instead, can you tell whether it would be narrower or wider? Can you tell by how much? 

Quiz: Weeks 1-4

Week 5: Hypothesis Testing

Weekly Outcomes: 

• Utilize the basic steps of hypothesis testing to evaluate research questions involving a single sample.
• Relate information provided by a hypothesis test to information provided by a confidence interval.

Readings: 

• Sullivan Textbook: Chapters 7.1 through 7.3 and 7.6 (skip 7.4 and 7.5)

Videos:

• Week 5 Part 1
• Week 5 Part 2 
• SAS Tutorial: Correlation Test [Dr. Liam O’Brien]

Assignments: 

• Discussion: P-values — Everyone has seen or heard of a p-value. 
  • Consider your exposure and define what the p-value represents. 
    • Why can we compare it to alpha (the significance level of the test)? 
  • Last week we discussed confidence intervals. Consider what a p-value tells you that a confidence interval does not? 
    • What does a confidence interval tell you that a p-value does not? Which one is more useful? 
• Make sure your response is in your own words and that your ideas are supported by reputable sources. 

In your response to your peer’s initial post compare your answers. 

• How do your p-value definitions differ? 
• Consider your peers’ thoughts on the information gained from a p-value and a confidence interval. Do you agree or disagree? Why?

 

• Written Assignment — Now that you have used descriptive statistics and examined the data numerically and also graphically, you are ready to begin answering your research questions using inferential statistics.  Descriptive statistics describe the data in the sample, while inferential statistics allows one to take those results and hopefully make inferences about the population from which the sample was drawn.  To do this, one must perform hypothesis testing.

In this assignment, you will define the steps needed to evaluate the continuous response and continuous explanatory variable research question and perform the appropriate hypothesis test with SAS.  Make sure you explicitly show all five steps and consider any necessary assumptions that were discussed in the lecture.

Week 6: Hypothesis Testing Part 2

Weekly Objectives: 

• Discuss how the size of a sample affects conclusions through the examination of a study’s confidence intervals.
• Evaluate research questions through the completion of appropriate hypothesis testing involving two samples.

Readings: 

• Sullivan Textbook: Chapters 7.5, 7.7, and 7.9
• Paolo Boffetta, Paolo et al. Fruit and Vegetable Intake and Overall Cancer Risk in the European Prospective Investigation Into Cancer and Nutrition (EPIC)JNCI J Natl Cancer Inst (2010) 102 (8): 529-537 doi:10.1093/jnci/djq072 first published online April 6, 2010. 
• Faber J, Fonseca LM. How sample size influences research outcomes. Dental Press J Orthod. 2014 July-Aug;19(4):27-9. 

Videos: 

• Week 6 Part 1
• Week 6 Part 2

Assignments: 

• Discussion: Confidence Intervals Part 2 — Read the Faber (2014) article on the influence of sample size and then the Boffetta et al (2010) article of the relationship between fruit and vegetable consumption and reduced cancer risk. Examine the confidence intervals reported in the abstract (note that a hazard ratio (HR) of 1 means no change in risk) and comment on their sizes. Are they statistically significant? How does the size of the samples affect your opinion of the conclusions reached?

 

• Written Assignment — Continue with hypothesis testing using SAS for your remaining two research questions.  One question uses a categorical response and categorical explanatory variable, and the last question uses a continuous response and categorical-dichotomous explanatory variable.

Be sure to watch the lectures before beginning this assignment as the parameter, the nature of the hypotheses, the statistical test needed, etc. do change when the data type changes, so you will not be performing a correlation test for these two questions.

Your submission needs to clearly discuss each step to properly evaluate your two remaining research questions. You should divide up your document with subheadings for each step. Be sure to restate your research questions at the beginning of the assignment.

Reminder: Next week your Final Project is due. 

Week 7: Linear Regression

Weekly Outcomes: 

• Perform a linear regression to interpret the slope and intercept of the regression line
• Utilize a dataset to complete a professional report. 

Readings:

• Sullivan Textbook: Chapter 9.3

Videos: 

• Lecture: Week 7
• SAS Tutorial: Simple Linear Regression

Assignments:

• Discussion: Linear Regression — Up until this point you have assessed two continuous variables using a correlation. This week you will run a simple linear regression to address your research question relating your two continuous variables together. Take the regression equation you obtain from SAS and interpret the slope of the line. What information does this give you that you weren’t able to obtain by running a simple correlation? Note that this regression does not need to be included in your final project. 

In your response to your peer’s initial post comment on other variables that might potentially confound the relationship between the two displayed variables. 

• Final Project Submission — As a Public Health professional presentation of research findings is an important skill. Now that you have answered your three research questions it is time to consolidate your results and appropriate statistical inferences you drew from them into a final report, which should be similar to a research article one would submit for publication.

Please see the final project document for details on the required components of this report and guidelines for submission.

Week 8: Analysis of Variance

Weekly Outcomes: 

• Perform a one-way ANOVA using SAS to compare means across more than two groups.

Readings: 

• Sullivan Textbook: Chapter 7.8

Videos: 

• Weekly Lecture: Week 8
• SAS Tutorial: Oneway ANOVA [Dr. Liam O’Brien]

Assignments:

• Written Assignment — Using the provided dataset, determine whether the mean birthweight for infants differs significantly according to mothers’ smoking status by using a one way ANOVA in SAS. Make sure to include all 5 hypothesis testing steps in your writeup.  

Datasets are provided within the course. Your paper should use subheadings that divide the submission into the sections above. 

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.

Questions? Visit the Student Support Public Health page

UNE Libraries:

• Library Access for all students: Your library login ID and password are the same as the ones you use to log into Brightspace.
• Public Health Databases: https://library.une.edu/library-materials/find/research-by-subject/public-health/
• Library Questions: Ask a librarian or phone library staff at (207) 602-2361 or (207) 221-4330.

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. The SASC also offers tutoring for GPH 712 Epidemiology, GPH 716 Biostatistics, GPH 717 Applied Epidemiology, GPH 718 Biostatistics II, and GPH 719 Research Methods. 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:

• UNE Student Academic Success Center

Information Technology Services (ITS)

• ITS Contact: Toll Free Help Desk 24 hours/7 days per week at 1-877-518-4673

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

Passing Grade Statement

A grade of 80% or higher is required to pass the course. A grade lower than 80% will result in you having to repeat the course. Obtaining two "Fs" in the program will result in dismissal from the program.

AMA Writing Style Statement

The American Medical Association Manual (AMA) of Style, 11th edition is the required writing format for this course. Additional support for academic writing and AMA format is provided throughout the coursework as well as at the UNE Portal for Online Students.

Online resources: AMA Style Guide

Artificial Intelligence (AI) Statement

Learning to use Artificial Intelligence (AI) responsibly and ethically is an important skill in today’s society. AI is not a substitute for developing and enhancing skills in creativity, logic, critical thinking, analysis, evaluation, theorization, and writing essential to a public health professional. If you choose to use AI tools, such as ChatGPT and DALL-E2, they must be used wisely and intelligently to deepen your understanding of a subject matter and support learning. You are not allowed to use AI tools to generate your work. Content produced using AI tools cannot be used as a substitute for your original work.

Students in the Graduate Programs in Public Health (GPPH) must take ultimate responsibility for the accuracy of AI-generated content used in any work. You are expected to think critically about the results and alignment with the questions or tasks in the assignment and never substitute AI-generated results for professional human judgment and logic. GPPH students are also expected to understand that the information generated is not always accurate and, in some cases, propagates discrimination and bias. You must stay abreast of AI best practices, and the changing risks and benefits, and monitor AI for biases and risks for vulnerable populations and underrepresented groups.

Within GPPH, using AI-generated content in academic work falls under our academic integrity policies. All instructors will continue to use our AI detection software for each assignment submitted so it will be flagged.

Using any AI tool in your work must be acknowledged in-text every time it is used, not in your list of references. You will include a summary of what the AI tool was used to do, followed by the AI tool brand name, version/extension #, manufacturer/owner, and date used in parentheses.

For example, 

Themes from participant responses were identified using a chatbot session (ChatGPT, model GPT-4, OpenAI, May 17, 2024).

Failure to acknowledge the inclusion of AI-generated content in any work submitted violates our academic integrity policies and will be considered an infraction with the associated penalties for plagiarism as outlined in the Student Handbook.

The Student Orientation has a module "Artificial Intelligence Literacy for Students", please refer to this module for more information about navigating the use of AI.

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 APA 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

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

Students are responsible for submitting work by the date indicated in Brightspace.

Quizzes and Tests: Quizzes and tests must be completed by the due date. They will not be accepted after the due date.

Assignments: Unless otherwise specified, 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.

Student Handbook Online - Policies and Procedures

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

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 https://www.une.edu/studentlife/plagiarism.

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.