This course provides you with an introduction to the procedures used in the summarization, analysis, interpretation, and presentation of research data. Topics include sampling, experimentation, measurement, descriptive statistics, correlation, probability, confidence intervals, testing hypotheses, 2-way tables, and simple linear regression. This course is deliberately broad and not intended to give students an in-depth understanding of statistical testing, analysis of categorical data or regression analysis. Rather, its intent is to provide an overview of some of the main areas of statistics and a working knowledge of basic summary statistics, graphs, and simple statistical tests for hypothesis testing. At the end of the course, a student should be able to evaluate simple statistical tests for hypothesis usage in everyday life and their own discipline, especially in relevant research publications; and interact knowledgeably with statisticians in planning, conducting, analyzing and reporting research projects.
FC 3: Analyze quantitative and qualitative data using biostatistics, informatics, computer-based programming and software, as appropriate.
FC 4: Interpret results of data analysis for public health research, policy or practice.
NOTE: Watch the lecture videos each week for directions on using SAS to complete your work. Working with SAS begins in Week 3.
Discussions: Initial discussion posts must be submitted by Sunday at 11:59 PM. For most weeks, that means you must have completed the reading by this time. Responses must be completed by Wednesday at 11:59 PM of the week the question is assigned.
Quiz: In Week 4, you will complete a quiz covering information from Weeks 1–4. You will have one opportunity to take this quiz.
Written Assignments: In Weeks 2, 3, 5, 6, and 8, you will complete written assignments. For each assignment carefully read through the prompt and review the rubric.
Final Project:
This course provides you with an introduction to the procedures used in the summarization, analysis, interpretation, and presentation of research data. The final project for this course will apply the skills you learn in these areas to a public health data set and integrate the results into a final report. This report will be similar to a research article that you would submit to a journal, except that you will not be performing original research.
Please review the Final Project Document for a full description of the assignment requirements and expectations. This assignment will be submitted in Week 7. Throughout the course, you will work on pieces of your final project.
Your grade in this course will be determined by the following criteria:
Discussions | 6 Discussions @ 3 points each=18 points |
Week 2 Written Assignment | 8 points |
Week 3 Written Assignment | 10 points |
Module 4 Quiz | 10 points |
Week 5 Written Assignment | 8 points |
Week 6 Written Assignment | 8 points |
Final Project: Written Report | 30 points |
Week 8 Written Assignment | 8 points |
TOTAL | 100 points |
Grade | Points Grade | Point Average (GPA) |
A | 94 – 100% | 4.00 |
A- | 90 – 93% | 3.75 |
B+ | 87 – 89% | 3.50 |
B | 84 – 86% | 3.00 |
B- | 80 – 83% | 2.75 |
C+ | 77 – 79% | 2.50 |
C | 74 – 76% | 2.00 |
C- | 70 – 73% | 1.75 |
D | 64 – 69% | 1.00 |
F | 00 – 63% | 0.00 |
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
Weekly Outcomes:
Readings:
Videos:
Assignments:
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:
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.
Weekly Outcomes:
Readings:
Videos:
Assignments:
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:
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.
Weekly Outcomes:
Readings:
Videos:
Assignments:
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.
Weekly Outcomes:
Readings:
Videos:
Assignments:
Quiz: Weeks 1-4
Weekly Outcomes:
Readings:
Videos:
Assignments:
In your response to your peer’s initial post compare your answers.
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.
Weekly Objectives:
Readings:
Videos:
Assignments:
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.
Weekly Outcomes:
Readings:
Videos:
Assignments:
In your response to your peer’s initial post comment on other variables that might potentially confound the relationship between the two displayed variables.
Please see the final project document for details on the required components of this report and guidelines for submission.
Weekly Outcomes:
Readings:
Videos:
Assignments:
Datasets are provided within the course. Your paper should use subheadings that divide the submission into the sections above.
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'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:
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.
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.
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.
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.
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
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.
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.
Please review the technical requirements for UNE Online Graduate Programs: Technical Requirements
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.
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.
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.
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.
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:
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.