SYLLABUS Lamar University, a Member of The Texas State University System, is accredited by the Commission on Colleges of the Southern Association of Colleges and Schools to award Associate, Baccalaureate, Masters, and Doctorate degrees (for more information go to http://www.lamar.edu).

Course Title: Biostatistics Course Number: HLTH 5303 Course Section: 48F Department: Health and Kinesiology Professor: Dr. Israel Msengi, CHES Office Hours: Virtual (online) Wednesday 7-8pm or by appointment. Physical: MW 11:30-2:00pm Contact Information: LU email: [email protected] Office:HHP 211 Phone: 409-880-8716

PERSONAL INTRODUCTION Welcome to Lamar University. My name is Dr. Israel Msengi, and I will be your instructor of record for Biostatistics. By way of a very brief introduction, I earned my baccalaureate in Public Administration with emphasis on Governance and master’s degrees in Community Health and a Doctorate in Community and Public Health. My area of expertise is Environmental Health, but I also enjoy the challenges of Obesogenic Environment research. I joined the faculty at Lamar in the fall of 2008 and I am currently an associate professor for the Department of Health and Kinesiology in the College of Education and Human Development.

COURSE DESCRIPTION Biostatistics is an area of that covers and provides the specialized methodology for collecting and analyzing biomedical, health care, and public health data. This course meets the biostatistics core course requirement for all degrees and concentrations in the Public Health program. Presentation of the principles and methods of data description and elementary parametric and non-parametric statistical analysis as well as sample size estimation are covered. Specific topics include: the collection, classification, and presentation of descriptive data; the rationale of estimation and hypothesis testing; analysis of variance; analysis of contingency tables; correlation and regression analysis; multiple regression, logistic regression, and the statistical control of confounding; sample size and power considerations; and survival analysis. Special attention is directed to the ability to recognize and interpret statistical procedures in articles from the current literature. This course gives students the skills to perform, present, and interpret basic statistical analyses using either the Statistical Analysis System (SAS) or the IBM Statistical Package for the Social Sciences (SPSS). Additionally, students will use Excel data sheets to enter, arrange and do basic data reviews prior to transferring data to dedicated statistical programs.

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COURSE-LEVEL OBJECTIVES By the end of this course, students should be able to assess the role of biostatistics in public health, distinguish between descriptive and inferential statistics, perform, interpret, and communicate the findings of a variety of statistical techniques from both descriptive and inferential statistics in public health. In general, the development and application of statistical reasoning and methods in addressing, analyzing, and solving problems in public health, health care, and biomedical, clinical, and population- based research will be emphasized.

Students who successfully complete this course will be able:

1. Explain the role biostatistics serves in public health and biomedical disciplines 2. Explain to others the statistical analyses in various research reports 3. Explain basic concepts of probability, random variation, and commonly used statistical probability distributions 4. Assess appropriate statistical methods (descriptive or inferential) to be applied in a given research setting, apply these methods, and acknowledge the limitations of those method 5. Distinguish among the different measurement scales and the implications for selection of statistical methods to be used on the basis of these distinctions 6. Analyze health data using statistical programs such as “IBM SPSS Statistics software and interpret the results. 7. Implement computer to communicate, study, and gain knowledge and skills on statistics. 8. Implement numerical, tabular, and graphical descriptive techniques commonly used to characterize and summarize public health data 9. Evaluate IBM SPSS output containing statistical procedures and graphics and interpret it in a public health context 10. Create written synthesis and oral presentations of findings on the basis of statistical analyses for both public health professionals and educated lay audiences.

CEPH Foundational Competencies This course meets the following Council on Education for Public Health (CEPH)’s Core Competencies: 3. Analyze quantitative and qualitative data collection methods using Biostatistics, informatics, computer- based programming and software as appropriate 4. Interpret results of data analysis for public health research, policy and practice

ACADEMIC PREREQUISITES 1. Undergraduate Introductory course to Statistics e.g. Psych 2317, Math 1342, or equivalent.

Methods of Learning Biostatistics: 1. Reading the assigned material, which includes following the numeric examples closely and writing down questions about anything not entirely clear to you. Reading biostatistics requires close study and rereading, not just reading through once as you might an ordinary text book. You will also find it very helpful to work the “Smart Alex’s Tasks?” problems as you complete each chapter. 2. Completing the assigned practice problems (and uploading them on time). Biostatistics is a skill. It is necessary to DO statistics, not just read and understand.

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3. Reading all lecture PPTs, watching video clips that demonstrate how to compute statistics, and ask questions. Be sure to have done the reading first. DON’T fall behind! Required texts: COURSE MATERIALS a. Andy Field (2018). Discovering Statistics using IBM SPSS Statistics, 5th Edition, SAGE Publications Inc, Thousand Oaks, California. ISBN-13: 978-1526419521. There is also a Bundle copy: Discovering Statistics using IBM SPSS Statistics 5e + SPSS v. 24 program. b. This book- “Discovering Statistics Using SPSS 5th Edition” covers material from introductory statistical concepts through very advanced concepts, incorporating SPSS applications throughout. c. Students must also access the Companion Website/Student Study Site (http://studysites.sagepub.com/field4e/study/default.htm) in order to study additional materials, complete homework and other activities. Resources are under “Student Resources” page.

1. CALCULATOR: Use a hand calculator for doing your assignments, also calculators are permitted during exams. I would much prefer you to spend your time developing an understanding of the statistical concepts rather than adding and dividing. A simple calculator that adds, subtracts, divides, multiplies, and takes square roots is all you need. Thus, calculators that also do statistical calculations will be of little help. 2. Statistical Software: You will need access to a software package that can do descriptive statistics, graphics, and inferential statistics. Your course text comes as a bundle with SPSS included. You will need to install SPSS on your computer in order to complete the SPSS assignments. Other statistical software are permitted as long as you know how to use them. If you happen to be on campus, you can use computer labs. Most campus computer labs have IBM SPSS installed in them. a. SPSS = Statistical Product and Service Solutions; a widely used computer program/software for statistical analysis. NOTE: Between 2009 and 2010 the premier software for SPSS was called IBM SPSS Statistics. 3. Online Resources: Go to http://www.learner.org/resources/series65.html# for VIDEO clips series on various statistical tests.

GRADING POLICY AND EVALUATION (700 Possible total points) Grading Scale 1: Your grade will be based on the following set scale. A - 630-700= 90-100% = Outstanding or Exceptional work B - 560-623= 80-89% = Superior or better than average C - 490-553= 70-79% = average or adequate work D- 420-483= 60-69% = An “OK” work F- <413= <59% = unacceptable or work not done I – Incomplete Your final grade will be calculated as follows: (4 exam scores + 2 Discussions + SPSS analysis + interpretation scores ÷ 7

NOTE: There will be NO extra credit or making any special arrangements regarding grades or adjustment of grades. Please do NOT ask for any adjustments to your grade (other than for errors in grading).

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GRADING OF ASSIGNMENTS AND ASSESSMENTS Components of the grading process include the following: 1. Exams = 4 (100 points each) = 400 total 2. Discussions = 2 (50 points each) = 100 total 3. IBM SPSS analysis & interpretation =6 exercises (33.33 each) =200 total

a. NOTE: Scores on assignments are reduced 4 points for up to one due date late. They are reduced 8 points from two due date late or more. You receive 0 for an assignment not completed and turned in.

3: Examinations: There will be 4 exams for this course (as shown above). The nature of the exams will be multiple choice questions. You will be answering from 25 to 50 questions with each question depending on the number of chapters and details of information covered. Each exam will have to be taken on the day and time specified on the syllabus except if you are notified of any changes. The final exam is not comprehensive. You will have a one chance to retake your exam. Retaking your exam does not guarantee a better score the next time around. Email me to ask for an exam reset.

Also: 1. Each of the four exams will cover only the material since the last exam (except to the extent that the previous material is necessary for understanding the new material). 2. There will be NO early exams, and no late exams. The instructor reserves the right to forward the exam taking date if deemed necessary. A missed exam counts as a zero. 3. Those who provide a written medical excuse (confirmed by the instructor calling the physician) can drop a total of ONE of the four exams (the grade will be averaged based on the remaining three exams and the assignments). Majority of other excuses will not be accepted.

J: Assignments: 1. 42.6% of your grade will come from your class assignments & the rest from your exams 2. All assignments must be turned-in by the due dates as indicated in the syllabus 3. Assignments should be typewritten and neatly organized, with assignment title or chapter it belongs, question number, and indicate whether it section “a” or “b” etc. of that particular question. In addition, each paper should have a page number, your name on each page, date, and be submitted via Bb as an attachment. YOU WILL LOSE 4 POINTS IF YOU FAIL TO FOLLOW INSTRUCTIONS 4. Show your work (when working on a problem involving formulas, at the minimum you should show each complete formula in its basic form filled in with numbers, at least one intermediate step, and the final answer). Most of the required formula (expressions) for your assignments can be handled fairly well within Microsoft Word (Press Alt+= to display the math zone in word 2007). Again, if you are not proficient using these expressions work your problems by hand and show only the important steps and the final answer. 5. When writing an essay, you should not use the exact wording in the answers at the back of the text. Use your own words to express your understanding of what you did. 6. Assignments are due as shown on this syllabus. Please see page 8. Submission of assignments will be time sensitive (even a minute late is late!); 4 points are deducted if your assignment is turned in via emails or other means past the due time shown on the Bb, and 8 points are deducted if the assignment is submitted beyond 2 days after the assignment is due.

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7. You are allowed a total, over the entire semester, of four late assignments to receive the deductions stipulated on #6 above.

ONLINE WEB CONFERENCES, THREADED DISCUSSION To enhance student-to-student and instructor-to-student interaction, Online Web Conferences utilizing Blackboard Collaborate have been scheduled an overview meeting for Tuesday 7-8pm Central Standard Time for questions and answer sessions (i.e. also Office Hours) Participation is required in the discussion threads by posting your own assignment and then posting engaging comments or questions (three or more) with other peers. Discussion posting: Discussions are an essential part of this online class. There will be TWO major discussions. To be awarded all point you will need to do the following: 1. Read the discussion topic carefully. Research on the topic, think critically and analyze the topic and then prepare a written answer to the topic. Use MS word to prepare the answer and upload your answer on the discussion board. 2. After posting your response follow the dynamics of the discussion closely. Reading other students’ postings and comment on their points. 3. Be online on the day and time scheduled for discussion. 4. Don’t use inappropriate language or grammar such as “what’s up”, slang words or abbreviations. Just post your responses written in proper English. I will be assessing your communication style. 5. I will be following your postings to determine your ability to express knowledge on the topic, using proper terminology, and analytical skills. 6. YOU MUST PARTICIPATE IN ALL DISCUSSION POSTINGS. To receive an “A” score (i.e. between 90-100), your posting must be thorough and analytical but also you MUST post more than 3 comments on other students’ postings. I WILL PROVIDE QUESTIONS AHEAD OF TIME. There will be NO make-up work provided if you missed points from discussions.

Knowledge of mathematics: 1. The course does not emphasize on mathematics. Many of the calculations require nothing more than elementary high-school algebra. The emphasis, instead, is on understanding the LOGIC of the statistical methods. 2. The most important part of the assignments will be to either focus on (a) a problem in which you use a statistical procedure to analyze the results of a study and then write an essay explaining what you have done to someone who has no knowledge of statistics or (b) a problem in which you are presented with the results of a study and must explain what they mean to a person who has never had a course in statistics. 3. NOTE: Students who are concerned about their placement in this class should discuss it with me in the first week of classes. Send me an Email via Blackboard. Syllabus summary (read the whole syllabus carefully) 1. Students are responsible for knowing the entire syllabus (and any updates given out in the Bb), not just this summary. 2. There will be no extra credit, special arrangements, or adjustments to scores 3. There will be 6 exams. No make-up, early, or late exams. Grade for missed exam will be = 0. (ONE exam can be dropped with written, confirmed medical excuse.) 4. All assignments will be due on Bb at 11:59 pm each time (see course outline)

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TECHNOLOGY PREREQUISITES Students are required to have computer skills in order to be successful in the class. Additionally, students should feel confident about their ability to navigate through typical online websites and their ability to use common word processing software in order to submit written assignments.

The minimum technical skills and the system requirements for this course:

BLACKBOARD Students will utilize the Lamar University’s Learning Management System (LMS), Blackboard, for online courses. For Blackboard support go to (https://blackboardsupport.lamar.edu) for more information.

SYSTEM REQUIREMENTS Computer/Technology Requirements: 1. Students will need regular access to Windows, MAC with a broadband Internet connection. Note: mobile devices (if you have mobile devices there are limitations) The minimum computer requirements are:  Most current version of Firefox is recommended o Please note that Blackboard may not support Internet Explorer, Safari, or Chrome.  8 GB or more preferred  Broadband connection (cable modem, DSL, or other high speed) required – some courses are video intensive  1024 x 768 or higher resolution  Strongly recommended that you have a headset with microphone. You may also use webcam, and speakers o Example: Plantronics Audio 628 USB headset  Current anti-virus software must be installed and kept up to date.  Students will need some additional free software for enhanced web browsing. Be certain to download the free versions of the software. o Firefox (http://www.mozilla.org) o Adobe Reader (https://get.adobe.com/reader/) o Adobe Flash Player (http://get.adobe.com/flashplayer) o Java (http://www.java.com) o QuickTime (https://www.apple.com/quicktime/download/) o Silverlight (https://www.microsoft.com/silverlight/)  Most home computers purchased within the last 3-4 years meet or surpass these requirements. 2. At a minimum, students must have Microsoft Office 365 (https://my.wip.lamar.edu) click on MS Office 365). Microsoft Office 365 is available for all students.

Required Skills:  Navigate websites, including downloading and reading files from them.  Use e-mail, including attaching and downloading documents/files.  Save files in commonly used word processing formats (.doc, .docx).  Copy and paste text and other items in computer documents.  Save and retrieve documents and files on your computer.  Locate information on the Internet using search engines.

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 Locate information in the library using the online catalog.

COURSE SPECIFIC TECHNOLOGY SKILLS REQUIREMENTS No additional technology skills needed beyond the ones listed above

SOFTWARE USED IN THIS CLASS a. You will need access to the IBM SPSS software package to perform Descriptive and Inferential Statistics. Other statistical software such as EXCEL, JMP, , , SAS, , , BMDP, LISREL, Statgraphics, StatsDirect, , -free, etc. are permitted as long as you know how to use them. b. Microsoft Office (with at least Word, PowerPoint, and Excel) is required.

RESPONSE TIMES Use the Blackboard email to communicate privately with the instructor or any member of the class. I will also be communicating with you via email; either with one student -privately or to the whole class. Sometimes I will use the announcement tool to post announcements. I will be responding to your email or providing you feedback as quick as I can. However, expect responses within 24-48 hours and up to one week for assignments.

PARTICIPATION REQUIREMENTS Students must be actively participating in their online course at least 3 out of 7 days a week. Students should log into the course each day and check for any announcement or communication from the instructor. Remember that participation is required in the discussion threads by posting your own response and then posting engaging comments or questions with other peers on a scheduled discussion date. MAKE-UP WORK In case of missed tests students are fully responsible for communicating with instructor in order to schedule time for make-up test. There will absolutely be no extra credit work provided in this course. The grade you obtain in your exams, homework, and discussions is final.

Course Expectations & Policies:  You are required to complete all assignments/projects for the course.  Your written work should exemplify that of a pre-professional. Follow APA guidelines for written papers and projects  Regular Blackboard log-in and assignment posting are required except in case of emergency or sickness.  Students are responsible to know time & date of exams/tests. If you miss taking an exam due to sickness or other pressing matters, you are responsible to inquire for a make-up exam. Make-up exam should be complete before the next exam.  If you fail to complete or submit assignments, complete work late; realize that you do so at your own academic risk.  It is the student's responsibility to notify the instructor in case of any problem that arises.  Assignment NOT submitted or completed will receive a "0" and 5 points will be deducted for any late work.  Students should use proper spelling, grammar, APA, and punctuations on any written work

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submitted to me.  For APA Writing Style Go to: http://owl.english.purdue.edu/owl/section/2/10/ Or go to: http://owl.english.purdue.edu Click on non-Purdue users and then left menu bar for 2009 APA format [Compliments of: Purdue University Online Writing Lab (OWL)].

DROP DATES This course adheres to the add/drop standards for each term as stated by Lamar University. For more details, refer to the http://www.lamar.edu and search “Academic Calendar.”

COURSE EVALUATION Instruction as well as student performance is subject to evaluation. Procedures for evaluation will be provided near the end of this course via email from the university. Please respond to each evaluation link provided.

LU CONNECT PORTAL Students are asked to obtain a Lamar Electronic Account username and password so they can log onto the LU CONNECT website. Students may get information on how to get into the LU CONNECT website from the University’s homepage (http://www.lamar.edu)by clicking on the LU CONNECT link on the left top corner of the screen. Follow the steps to secure your LU CONNECT username and password.

STUDENT HANDBOOK Students may access the Student Handbook online at http://students.lamar.edu/student-handbook.html.

UNIVERSITY POLICIES AND SERVICES

STUDENTS WITH DISABILITIES For students with disabilities, this course will comply with all accommodations prescribed by the Lamar University Disability Resource Center (DRC). It is the responsibility of the student to ensure that the instructor has been informed of all prescribed accommodations. Lamar University’s Disability Resource Center offers a variety of services designed to provide for students with disabilities and can be contacted at (409) 880-8347 or emailed at [email protected].

The Disability Resource Center offers a variety of services designed to assure students with disabilities equal access to the university’s activities, programs and services. Some of the services provided include academic accommodations, assistive equipment, communication access service providers, note-takers, physical access and priority registration. Documentation of a disability from a professional in the field is required to receive services.

Students with disabilities should notify the director of DRC prior to registration in any university program. The director will arrange a meeting with the student to determine reasonable academic adjustments/accommodations. The Disability Resource Center is located in room 105 of the Communication Building. Students may write to P.O. Box 10087, Beaumont, Texas 77710, call 409.880.8347, fax 409.880.2225 or e-mail [email protected]. Additional information is available at the DRC website, http://www.lamar.edu/disability-resource-center/.

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TECHNICAL SUPPORT Technical Support can be located at http://students.lamar.edu/it-services-and-support/index.html.

For Blackboard technical support go to (https://blackboardsupport.lamar.edu).

ACADEMIC SUPPORT Academic Support can be located at http://students.lamar.edu/academic-support/index.html.

STUDENT SERVICES Information on Student services can be located at http://students.lamar.edu/student-services/index.html.

ACADEMIC HONESTY POLICY Lamar University expects all students to engage in academic pursuits in a manner that is above reproach. Students are expected to maintain complete honesty and integrity in their academic experiences both in and out of the classroom. Any student found guilty of dishonesty in any phase of academic work will be subject to disciplinary action. Disciplinary proceedings may be initiated against a student accused of any form of academic dishonesty including, but not limited to, cheating on an examination or other academic work which is to be submitted, plagiarism, collusion, and the abuse of resource materials. Plagiarism shall mean the appropriation of another’s work or idea and the unacknowledged incorporation of that work or idea into one’s own work offered for credit. Collusion shall mean the unauthorized collaboration with another person in preparing work offered for credit. Abuse of resource materials shall mean the mutilation, destruction, concealment, theft or alteration of materials provided to assist students in the mastery of course materials. Academic work shall mean the preparation of an essay, report, problem, assignment, creative work or other project that the student submits as a course requirement or for a grade.

Students are specifically warned against all forms of plagiarism, which include “purchasing, or otherwise acquiring and submitting as one’s own work any research paper or other writing assignment prepared by an individual or firm.” Plagiarism is defined as, “the appropriation and the unacknowledged incorporation of another’s work or ideas into one’s own offered for credit” (82). Students seeking to avoid plagiarism should consult either the course instructor or the most recent addition of the MLA Handbook for Writers of Research Papers or the most recent addition of the APA Style Guide, depending on your College requirements for writing research papers. The course instructor will complete a thorough and impartial investigation of any instance of academic dishonesty. A student found guilty of academic dishonesty will be notified in writing by the instructor of the violation, the penalty, and the student’s right to appeal the determination of dishonesty and/or the sanction imposed. Penalties for academic dishonesty in this course will result in either a lowered letter grade or failure of the course as determined by the instructor. The penalty may vary by instructor. For complete policy: go to https://students.lamar.edu/academic-support/academic-policies.html.

COPYRIGHT POLICY STATEMENT Copyright is defined as the ownership and control of the intellectual property in original works of authorship which are subject to copyright law. As an institution of higher learning that values intellectual

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integrity, Lamar University prohibits the distribution of published materials (print or electronic) in violation of copyright law.

NETIQUETTE (ONLINE ETIQUETTE) STATEMENT Please adhere to the same standards of behavior and professional respect online that you would follow in face-to-face communication with others, but most particularly when writing email and when taking part in collaborative and discussion board activities. Lamar provides access to network resources, including the Internet, in order to support learning and to prepare students for the 21st century world. Students, however, are expected to adhere to the Lamar University Acceptable Use Policies when Using Networks. More comprehensive student code of conduct can be found at https://students.lamar.edu/academic- support/code-of-conduct.html.

ACCEPTABLE USE Students must respect the integrity and security of Lamar University computer systems and network, and the privacy and preferences of other users. Responsibility for learning about and complying with Lamar University Acceptable Use Policy ultimately rests with the individual. The network may be used to download, copy, or store any software, shareware, digital media files or , as long as the use complies with copyright law licensing agreements, and campus policies, such as storage space limitations and network bandwidth restrictions. The network may not be used for any activity, or to transmit any material, that violates United States or local laws.

UNACCEPTABLE USE The network may not be used for commercial purposes. Advertising and sponsorships on Lamar University websites is restricted. In addition, students may not permit other persons to use their usernames, passwords, accounts or disk space, or disclose their usernames, passwords or account information to any third party. Students may not log on to someone else's account, internet address, or other network codes, or attempt to access another user's files. Students may not create false or dummy accounts to impersonate someone else. Students may not try to gain unauthorized access ("hacking") to the files or computer systems of any other person or organization. Students may not impersonate another person by forging e-mail, web pages or other electronic media. Students who maliciously access, alter, delete, damage or destroy any computer system, computer network, computer program, or data will be subject to disciplinary action by Lamar University, and criminal prosecution as well. Students may not disrupt or attempt to disrupt network traffic, and they may not attempt to monitor or capture network traffic in any way. Finally, students may not intentionally create, store, display, print or transmit information that violates the university’s Sexual Harassment Policy.

GENERAL GUIDELINES TO RESPECT ALL PARTICIPANTS  Respect the right of each person to disagree with others.  Treat people the same as you would face-to-face.  Respect the time of others.

GUIDELINES WHEN COMMUNICATING WITH OTHERS (EMAIL, DISCUSSIONS, BLOGGING, AND ETC.)  Always sign your names to any contribution you choose to make.  Be constructive in your responses to others in the class.

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 Do not use all caps (Doing so may be interpreted as shouting).  Re-read your postings before sending them.  Always think before you write.  Respond respectably.  Use appropriate grammar and structure.  Spell-check your postings.  Use short paragraphs focused on one idea.  Use appropriate business language at all times.

DISTANCE EDUCATION LIBRARIAN Distance education students and faculty have access to a dedicated distance education librarian. Access this link, http://library.lamar.edu/services/distance-learning.html, for more information.

LAMAR UNIVERSITY PRIVACY POLICY STATEMENT Student records maintained by Lamar University comply with the Family Education Rights and Privacy Act of 1974 as amended (PL93-380). Detailed information should be accessed through this link: https://sacs.lamar.edu/catalog/PrefMaterial/V.GenAcademicPol.htm#edurights.

ACADEMIC CONTINUITY STATEMENT In the event of an announced campus closure in excess of four days due to a hurricane or other disaster, students are expected to login to Lamar University’s website’s homepage (http://www.lamar.edu) for instructions about continuing courses remotely.

EMERGENCY PROCEDURES *Be sure to update your MyLamar Account with the most current information.* Many types of emergencies can occur on campus instructions for specific emergencies such as severe weather, active shooter, or fire can be found at http://www.lamar.edu/about-lu/administration/risk-management/index.html.

These procedures may or may not apply to you: Severe Weather: • Follow the directions of the instructor or emergency personnel • Seek shelter in an interior room or hallway on the lowest floor, putting as many walls as possible between you and the outside • If you are in a multi-story building, and you cannot get to the lowest floor, pick a hallway in the center of the building • Stay in the center of the room, away from exterior walls, windows, and doors Violence / Active Shooter (CADD): • CALL- 9-1-1 • AVOID- If possible, self-evacuate to a safe area outside the building. Follow directions of police officers. • DENY- Barricade the door with desk, chairs, bookcases or any items. Move to a place inside the room where you are not visible. Turn off the lights and remain quiet. Remain there until told by police it is safe. • DEFEND- Use chairs, desks, cell phones or whatever is immediately available to distract and/or defend yourself and others from attack.

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Tentative Course Content Outline

HLTH 5303- 48F: BIOSTATISTICS Doing Research & Intro to Linear Models MODULE-1 Week 1: Jan 16-21 A: Welcome and Course Introduction  Students will introduce themselves via a discussion board (due Jan. 19th )  Listen to a video clip on “Course Introduction” by Dr. Msengi MODULE-1: LEARNING OBJECTIVES 1. Getting to know each other through introduction 2. Explain concepts and terminology of Statistics, kinds of variables, measurements and scales 3. Distinguish between quantitative and qualitative research process and data type 4. Distinguish models for samples and populations 5. Analyze Public Health data using computer and the SPSS Software for statistical analysis 6. Explain the IBM SPSS software and its environment 7. Explain the statistical models and the reasons they are utilized 8. Explain clear data presentation approach 9. Explain appropriate data organization, display, charts histograms and graphs building 10. Evaluate bias and ways to reduce bias in research and statistics 11. Explore the assumptions of non-parametric tests and when to use these tests 12. Analyze the general procedures of non-parametric tests in SPSS 13. Compare two independent conditions-Wilcoxon rank-sum test and Man-Whitney test 14. Distinguish between several independent (the Kruskal-Willis test) and related (Friedman’s ANOVA) groups

Readings:  Welcome and Introduction  Course Syllabus  Andy Field (2018). Why do we need statistics? Chapter-1  Andy Field (2018). The Spine of Statistics. Chapter-2  Andy Field (2018), The Phoenix of Statistics. Chapter-3  Andy Field (2018), The IBM SPSS Statistics Environments. Chapter- 4 Lecture:  PowerPoints- Chapter 1-4 To do List  Read book chapter- 1 -4 (SLO: 1-7)  Read lecture notes- PPT (SLO: 1-3)  Complete Assignment-1 (SLO: 1-7)

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Web Conferencing:  Course overview meeting via Blackboard Collaborate on January 23, from 7:00pm to 8:00pm. Session will be recorded. SPSS Assignment -1: Descriptive Statistics  Use provided data to generate appropriate descriptive statistics  Interpret your statistical findings  Due January 22nd

Week 2: Jan 22-28 Readings:  Andy Field (2018). Exploring Data with Graphs. Chapter-5  Andy Field (2018), The Beast of Bias. Chapter-6  Andy Field (2018), Non-Parametric Models. Chapter-7 Lecture:  Lecture: PowerPoints chapters 5-7 To do List  Read Book Chapter-5-7 (SLO:6-7)  Read Lecture notes-PPT (SLO:6-7)  Complete Assignment-2  Take EXAM-1 (SLO: 1-7) SPSS Assignment-2: Exploring Data with Graphs  Use provided data to generate appropriate graphs  Due January 25th

Exams: (Chapters 1-7)  Exam-1: Due January 26th

MODULE-2 Linear Models with Continuous or Categorical Predictors

Week 3: Jan 29-Feb 4 MODULE-2: LEARNING OBJECTIVES 1. Explain modelling relationships of covariance, correlation coefficient, confidence intervals for r, interpretation of causality. 2. Explain Bivariate and partial correlation and the procedure for analyzing correlations in SPSS 3. Analyze correlations using SPSS; Pearson’s & Spearman’s Correlation Coefficient, Kendall’s tau and biserial & poin- biserial correlations. 4. Compare correlations, calculate effect size and report correlations coefficients

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5. Explain linear and multiple regression 6. Evaluate bias in regression models, generalizing the models and determining the sample size. 7. Analyze regression using SPSS and interpret results. 8. Evaluate t-test, dependent, independent, and paired samples t-test, and its applications. 9. Explain the rationale for the t-test and its assumptions. 10. Analyze public health data in IBM SPSS using t-test, interpret and report results 11. Assess moderation interactions in regression, interpreting and reporting the analysis outcome 12. Evaluate principles of ANOVA (GLM-1) and the theory of one-way independent ANOVA. 13. Analyze public health data using ANOVA test in the IBM SPSS

Readings:  Andy Field (2018). Correlation. Chapter-8  Andy Field (2018), The Linear Model (Regression). Chapter-9 Lecture:  Lecture PowerPoints Chapters 8-9 To do List  Read chapter 8-9 (SLO:1-7)  Read lecture notes-PPTs (SLO: 1-7)  Complete Assignment-3 (SLO: 1-2) SPSS Assignment-3: Correlation and Regression  Use provided data to generate appropriate statistics  Interpret your statistical findings  Due February 2nd

Week 4: Feb 5-11 Readings:  Andy Field (2018); Comparing Two Means. Chapter 10  Andy Field (2018); Comparing Several Means. Chapter 12 Lecture:  PowerPoints Chapter 10 and 12 To do List  Read week’s chapter 10 & 126 (SLOs: 3-7)  Read lecture notes-PowerPoints (SLOs: 3-7)  Complete SPSS Assignment-3 (SLOs: 1-2)  Take Exam-2

SPSS Assignment -4: Comparing two or more means: T-test &

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ANOVA  Use provided data to generate appropriate t-tests  Interpret your statistical findings  Due February 9

Exams (Chapters-8, 9, 10, & 12)

Exam-2: Due February 12  None

MODULE-3 Linear Models with Categorical Predictors and Multiple Outcomes MODULE-3: LEARNING OBJECTIVES Week 5: Feb 12-18 1. Explain planned contrasts and Post hoc procedures in ANCOVA (GLM-2), analyze and interpret results. 2. Explain appropriate way to use ANCOVA, analyze and interpreting outputs from ANCOVA and reporting results 3. Evaluate factorial ANOVA (GLM-3) and its rationale, and assumptions 4. Analyze data using factorial ANOVA, mixed design ANOVA, interpret output, and report the results of factorial and mixed design ANOVA (GLM-5) 5. Explain the rationale, theory, effect size, and assumptions of repeated measure and mixed design ANOVA (GLM-4) 6. Analyze data using IBM SPSS , interpret outputs and report results of repeated measures and mixed design ANOVA 7. Assess appropriate use of Multivariate Analysis of Variance (MANOVA). 8. Compare and contrast MANOVA from ANOVA 9. Explain the theory of MANOVA and the principle of the MANOVA test statistics 10. Evaluate practical issues when conducting MANOVA. 11. Analyze health data using IBM SPSS with MANOVA test generate MANOVA output, interpret and report results from MANOVA.

Readings:  Andy Field (2018); GLM-2: Comparing means adjusted for other Predictors ANCOVA. Chapter 13  Andy Field (2018); GLM-3: Factorial Designs. Chapter 14  Andy Field (2018); GLM-4: Repeated Measures Designs. Chapter- 15  Lecture:  PowerPoints, Chapters 14-15 To do List  Read chapters 14-157 (SLO:1-7)  Read lecture notes-PPT (SLO:1-7)  Complete homework (SLO:1-2)

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Discussion-1  Due February 15

Week 6: Feb 19- 25 Readings:  Andy Field (2018); GLM-5: Mixed Designs. Chapter-16.  Andy Field (2018) Multivariate Analysis of Variance (MANOVA). Chapter-17 Lecture:  PowerPoints chapters 16 & 17. To do List  Read chapters 16 &17 (SLO: 5-7)  Read the accompanying lecture notes-PPT (SLO: 5-7)  Complete Assignment-5 ((SLO: 5-7)  Take Exam-3 (SLO: 1-7) EXAM-3: (Chapters 13-17)

Due February 26th MODULE- 4 Linear Models with Categorical Outcomes or Hierarchical Data Structures Week 7: Feb 26-March 4 MODULE-4: LEARNING OBJECTIVES

1. Analyzing categorical data and the use of Chi-Square and Odd-ratio 2. Explain the theory of analyzing categorical data and the assumptions when analyzing categorical data 3. Explain Loglinear models and its theory and assumptions 4. Conduct an analysis of Chi-square, Loglinear and its effect size using IBM SPSS, read the outputs, interpret and report results 5. Explain the principles behind logistic regression and the sources of bias 6. Explain Binary Logistic, Multinomial Logistic regression, entering data in SPSS and testing assumptions 7. Analyze data using logistic regression, interpret results and report logistic regression results

Readings:  Andy Field (2018); Exploratory Factor Analysis. Chapter 18  Andy Field (2018); Categorical Outcomes: Chi-Square and Loglinear Analysis. Chapter 19 Lecture:  Lecture notes/PowerPoints- Chapter 18- 19 To do List  Read chapter 18-19 (SLO, 1-5)

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 Read lecture notes-PPT (SLO, 1-5)  Participate in Discussion-2  Complete assignment 6 SPSS Assignment -5: Chi-Square (Non-Parametric)  Use provided data to generate appropriate Chi-Square tests  Interpret your statistical findings  Due March 1st

Discussion-2  Due March 2nd

Week 8: March 5-7 Readings:  Andy Field (2018); Categorical Outcomes: Logistic Regression. Chapter 20. Lecture: 1. Lecture notes/PowerPoints- Ch. 20 To do List  Read chapter 20 (SLO, 6-13)  Read lecture notes-PPT (SLO, 6-3)  Complete the SPSS assignment-7 (SLO, 1-5)  Take EXAM-4 (SLO, 1-7) SPSS Assignment-6: Logistic Regression  Use provided data to generate appropriate Logistic Regression tests  Interpret your statistical findings  Due March 6th

EXAM-4 (Chapters 19-20)  Due March 7th March 12-18  No School- SPRING BREAK

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COURSE SCHEDULE (January 16- March 7, 2018) WEEK TOPIC READING ACTIVITY MODULE-1 Why do we need statistics Chapter- 1 Student intro- Due: Jan. 19th

1 The Spine of Statistics Chapter- 2 Chapter Reading The Phoenix of Statistics Chapter- 3 SPSS Assignment-1: Due Jan. 22nd

The IBM SPSS Environment Chapter- 4 Course Overview Meeting- Jan 23-(7-8:00pm)

Exploring Data with Graphs Chapter -5 Chapter Reading

th 2 The Beast of Bias Chapter- 6 SPSS Assignment-2: Due Jan. 25 Non-Parametric Models Chapter- 7 Exam-1: Due Jan. 26th

MODULE-2 Correlation Chapter- 8 Chapter reading

nd 3 The Linear Model (Regression) Chapter- 9 SPSS Assignment-3: Due Feb. 2

Comparing two Means (t-test) Chapter- 10 Chapter reading

th 4 GLM-1: Comparing Several Means Chapter- 12 SPSS Assignment-4: Due Feb. 9 (ANOVA) Exam-2: Due Feb. 12th

MODULE-3 GLM-2: ANCOVA Chapter-13 Chapter reading

th 5 GLM-3: Factorial Design Chapter-14 Discussion-1: Due Feb. 15 GLM-4: Repeated Measures Design Chapter -15

GLM-5: Mixed Designs Chapter- 16 Chapter reading

th 6 Multivariate Analysis of Variance Chapter- 17 Exam-3: Due Feb. 26 (MANOVA)

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MODULE-4 Exploratory Factor Analysis Chapter-18 Chapter reading

st 7 Chi-Square and Loglinear Chapter- 19 SPSS Assignment-5: Due March 1 Discussion-2: Due March 2nd

Logistic Regression Chapter- 20 Chapter reading

th 8 SPSS Assignment-6: Due March 6 EXAM-4: Due March 6th

The instructor reserves the right to adjust the syllabus as needed. While information and assurances are provided in this course syllabus, it should be understood that content may change in keeping with new research and literature and that events beyond the control of the instructor could occur. Students will be informed of any substantive occurrences that will produce syllabus changes. Students are responsible for staying current on the lessons listed and should prepare for changes and new information during the semester. Academic Calendar Spring 2018  Jan 01 New Year's Holiday - January 1  Jan 03 Winter Mini - Last day to drop/withdraw with academic penalty (by 5 pm)  Jan 09 Winter Mini Session ends / Final Exams  Jan 11 16 weeks - Spring 2018 non-payment purge after 5 p.m.  Jan 11 8 weeks/Spring II - Non-payment purge after 5 pm  Jan 12 Grades for Winter Mini due by 1 pm  Jan 12 16 weeks - Last day to register for Spring 2018 without late fee  Jan 15 Martin Luther King, Jr. Holiday  Jan 16 16 weeks - Late registration with fee begins for Spring 2018  Jan 16 16 weeks - Spring 2018 semester begins  Jan 16 8 weeks/Spring II - Classes begin  Jan 18 16 weeks - Last day to register for Spring 2018 with late fee  Jan 18 8 weeks/Spring II - Last day to add  Jan 19 Application for May 2018 graduation begins  Jan 23 8 weeks/Spring II - Census Day  Jan 23 8 weeks/Spring II - Last day for full refund on dropped (not withdrawn) courses  Jan 31 16 weeks - Census Day  Jan 31 16 weeks - Last day for full refund on dropped (not withdrawn) courses  Jan 31 8 weeks/Spring II - Last day to drop or withdraw without academic penalty  Feb 05 8 weeks/Spring II - Final non-payment purge after 5 pm  Feb 12 16 weeks - 20th Class Day  Feb 12 16 weeks - Final Spring 2018 non-payment purge after 5 pm  Feb 16 8 weeks/Spring II - Last day to drop or withdraw with academic penalty  Feb 19 16 weeks - Last day to drop or withdraw without academic penalty  Mar 06 Last day for graduate students to apply/pay for May 2018 graduation  Mar 07 8 weeks/Spring II - Last class day  Mar 09 8 weeks/Spring II - Final grades are due by 1:00 pm  Mar 12 Spring Break: March 12-16  Mar 16 Energy Conservation Day  Mar 19 8 weeks/Spring III - Classes begin  Mar 20 8 weeks/Spring III - Last day to add  Mar 26 8 weeks/Spring III - Census Day  Mar 26 8 weeks/Spring III - Last day for full refund on dropped (not withdrawn) courses

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 Mar 30 Good Friday - No Classes  Apr 02 Course schedules available for May Mini/Summer/Fall 2018  Apr 03 Last day for undergraduates to apply/pay for May 2018 graduation  Apr 04 Advisement begins for May Mini/Summer/Fall 2018  Apr 04 16 weeks - Last day to drop or withdraw with academic penalty  Apr 04 8 weeks/Spring III - Last day to drop or withdraw without academic penalty  Apr 09 Registration begins at 7 am for special populations - Mini/Summer/Fall 2018  Apr 09 8 weeks/Spring III - Final non-payment purge after 5 pm  Apr 16 Open registration begins at 7 am for May Mini/Summer/Fall 2018  Apr 20 8 weeks/Spring III - Last day to drop or withdraw with academic penalty  Apr 26 16 weeks - Last TTH class day for Spring 2018 (no exams or graded assignments)  Apr 30 16 weeks - Last MWF class day for Spring 2018 (no exams or graded assignments)  May 01 16 weeks - Final exam preparation day (no classes)  May 01 16 weeks - Final exams begin at 5 pm  May 02 16 weeks - Final Examinations: May 2-8  May 08 8 weeks/Spring III - Last class day  May 10 16 weeks - All grades are due by 1:00 pm  May 10 8 weeks/Spring III - Final grades are due by 1:00 pm

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