代写PM 510: Principles of Biostatistics Fall 2024代写C/C++程序

日期：2024-09-27 12:31

Department of Population and Public Health Sciences

PM 510: Principles of Biostatistics

Syllabus:  Fall 2024

Course Description:  This course provides an in-depth introduction to biostatistical methods and their applications in the field of biology and health sciences. Students will develop a comprehensive understanding of statistical concepts and techniques, while also gaining hands-on experience using the Statistical Package for the Social Sciences (SPSS) software for data analysis. Students will be equipped with the skills necessary to effectively design experiments, analyze biological data, and draw meaningful conclusions by the end of the course.

Course Objectives:

1.   Knowledge and Comprehension:

•     Define and explain fundamental statistical terms and concepts used in biostatistics.

•     Describe different types of data and their appropriate graphical and numerical summaries.

•     Explain the principles of probability and their role in biostatistical analysis.

•     Understand the basics of experimental design in biological research.

2.   Application and Analysis:

•     Apply descriptive statistics to summarize and visualize biological data.

•     Perform. inferential statistical tests (t-tests, ANOVA, chi-square) to analyze differences and associations in biological datasets.

•     Conduct correlation and regression analyses to assess relationships between variables in biological studies.

•     Interpret the results of statistical analyses and draw biologically meaningful conclusions.

3.   Synthesis and Evaluation:

•     Design sound experiments and sampling strategies to address research questions in biology.

•     Evaluate the assumptions and limitations of different statistical tests in the context of biological data.

•     Critically assess published research studies that use statistical methods in the field of biostatistics.

•     Synthesize information from multiple sources to develop a comprehensive statistical analysis plan for a biological research project.

4.   Application of SPSS:

•     Navigate and utilize SPSS software for data entry, management, and basic manipulation.

•     Import and export data between different file formats within the SPSS environment.

•     Perform. data transformations, recoding, and computation of derived variables using SPSS syntax.

•     Generate graphical representations and interpret output from SPSS analyses.

5.   Problem Solving and Project Design:

•     Identify appropriate statistical methods to address specific research questions in biostatistics.

•     Develop comprehensive analysis plans for various types of biological data.

•     Formulate hypotheses, choose appropriate tests, and outline the steps for conducting statistical analyses in research projects.

6.   Ethical and Professional Considerations:

•     Recognize ethical issues related to data collection, analysis, and reporting in biostatistics.

•     Demonstrate awareness of responsible data handling and privacy considerations when using biological datasets.

•     Communicate statistical results accurately and effectively to both technical and non- technical audiences.

7.   Integration and Application to Research:

•     Apply acquired knowledge and skills to analyze real-world biological datasets and research questions.

•     Collaborate effectively with multidisciplinary teams to contribute statistically sound insights to biological research projects.

By the end of this course, students will be proficient in applying statistical concepts and techniques to address challenges and opportunities in biostatistics within the context  of biological and health sciences.

Recommended Textbooks: Principles of Biostatistics, 2nd Edition

Marcello Pagano and Kimberlee Gauvreau Duxbury, 2000

Biostatistical Analysis, 5th Edition Jerrold H. Zar

Prentice Hall, Inc. (may be listed as Pearson Prentice Hall or Pearson Education)

OpenIntro Statistics, 4th Edition

Diez DM, Barr CD, Cetinkaya-Rundel M. https://www.openintro.org/book/os/ (2019)

The electronic version of this text is free at the link

above.  You can purchase a hard copy on the above

website or through Amazon for ~$20.  There are many

supplemental materials with this text including videos and labs you may find useful.

Software: IBM SPSS Statistics V29.  Some homework will require the use of SPSS, which is a statistical analysis software package.  This software is offered for free through USC ITS.  The

TA will reach out to you with a license form. you must complete and return in order to receive an activation code.  The license key is personalized, so please to not share with other individuals.

However, if you did not receive an e-mail from the TA, to get SPSS you can go to https://software.usc.edu/spss/spss-orderstudent/and do TWO things:

1.   Request your subscription by following the instructions at the bottom of the order page

2.   Download the software using the link provided by ITS.

SPSS is also freely available on the USC Virtual Desktop Interface (VDI;

https://itservices.usc.edu/vdi/).  However, if you have poor internet connectivity, we highly

recommend you install a local copy of SPSS on your computer.  Also, you cannot store any files  on the VDI and, depending on user load, the VDI may not be available due to the limited number of available licenses.  Therefore, again, we highly recommend you install a local version on your personal laptop or desktop computer.

You are expected to learn the basics of using SPSS on your own.  We provide a screencast that reviews some of the basics and provide a link to a tutorial below.  There are many online

resources that will help you learn SPSS basics.

Other Materials:    Recorded lectures and slides (posted onhttps://brightspace.usc.edu/)

Course reader (posted on Brightspace)

Homework assignments (posted on Brightspace) Supplemental articles (posted on Brightspace)

On-line SPSS tutorial (LinkedIn Learning; there are many other tutorials available online)

Policy on Generative Artificial Intelligence (AI) tools: In this course, you can choose to use AI-powered programs to help you with homework assignments.  You should be aware that AI text  generation  tools  may  present  incorrect  information,  biased  responses,  and  incomplete analyses.  Thus, they are not yet prepared to produce text that meets the standards of this course. To adhere to our university values, you must cite any AI-generated material, e.g., text, images, etc, included or referenced in your work and provide the prompts used to generate the content. Using an AI tool to generate content without proper attribution will be treated as plagiarism and reported to the Office of Academic Integrity.

Course Information: This course will employ a flipped classroom design to encourage active student participation and engagement with the course material.   In  order to  facilitate optimal flipped classroom conditions that allow the most active student participation in discussion and learning in  synchronous  class  sessions,  students  will be required to view videos  and  course materials posted  in  Brightspace  or  shared  by  your  instructor  in  advance  of  class  meetings. Students should come to class prepared to discuss course readings and any required viewing or supplementary materials. Please expect the following weekly time commitment for this course:

•   Contact time (lectures/labs/discussion sections; pre-recorded or live):  3 hrs 55 min

•   Out-of-class time (homework, readings):  9 hrs 15 min

Participation: Discussion will comprise a significant component of class participation.  You are expected to respectfully and actively listen to your peers and to thoughtfully contribute your own ideas to our discussions.

What you will NOT need during synchronous sessions: Please  turn  off your  cell phones  or any other device that would disrupt the class.

Grading: Weekly Quizzes (15%)

Midterm Exam (35%)

Final Exam (40%)

Homework Completion (10%)

The course grading rubric is shown in the table on the right. If you find yourself falling below the 55% level, please reach out to the instructor or TA. Students have generally performed well in this class and falling below 55% early in the course has been a strong predictor of a poor final grade.

Grading Scale
A      95-100%  A- 90-94.99%  B+ 85-89.99%  B 80-84.99%  B- 75-79.99%  C+ 70-74.99%	C     60-69.99%  C- 55-59.99%  D+ 50-54.99%  D 45-49.99%  D- 40-44.99%  F <40%

Quizzes: There will be a weekly quiz given online before each synchronous session that covers that week’s materials. The quizzes will be administered via Brightspace and you will have 15 min to take the quiz during the 36 hour period before the start of the synchronous session. That means you must take the quiz on your own during that 36 hour period prior to the start of each week’s synchronous session.  You will not be allowed to use any reference materials (your lecture notes, textbooks, internet-based resources) for the quizzes. The quiz is timed for 15 min, but you will be given three attempts at the quiz and your highest score will be your final score. Because of the possibility of internet connectivity issues, we have set things up to be as flexible  as possible.

We have not activated the automated submission, so Brightspace will allow you to exceed 15 min for the quiz.  However, please note Brightspace keeps track of your time and will indicate if a question is answered after your 15 min time limit.  Questions answered after the time limit will not count towards your score, so please keep track of your time.  The quizzes are designed to help you determine if you are keeping up with the class materials and providing you feedback on where you might need to spend more time reviewing specific materials.  The questions on the quizzes do not reflect the types of questions that will be asked on the midterm or final exams.

Exams: There will be a midterm and a final.  Both exams will be held during the synchronous class hours and will be in-person, but will be administered via Brightspace.  The exams are designed for 2-hours, but you will given 3-hours to complete it, assuming nobody is using the classroom after our scheduled time.  You will only be allowed to use your lecture notes, the course reader, and the online p-value calculator for the exams.

The exams are designed to test your ability to choose an appropriate statistical test to answer a specific research question, test your knowledge of statistical concepts, and test your ability to use a statistical test to obtain a correct conclusion to the research question.  A reminder to fully charge your laptops or other digital devices prior to coming in for your exams.  Depending on the classroom assigned to us, outlets may be scarce.  You are more than welcome to bring extension   cords and power strips to use during the exams.

Please turn off or silence your cell phones or other devices during the exam.  You will not be  allowed to touch your cell phones during the exam period.  Also, you are on the honor system that you will not access additional materials online or on your computer during the exam.

Anyone found to have violated the honor system or reaching for their cellphones will receive an automatic grade of “F”for the exam.

Homework: Homework will be assigned after each topic is covered and will be due according to the schedule shown at the end of the syllabus.  Homework will be assigned and turned in using Brightspace.

Late homework will not be accepted without an adequate excuse, e.g., documented illness.

Make arrangements with the instructor or TA well in advance of the deadline, if you know you will be late turning in a homework.  Plan to complete all assignments early, in case unforeseen  circumstances arise, particularly with respect to Brightspace access.

Rules for homework:

Show all your work.  All steps that led up to your answer must be shown.

Write clearly. Sloppy/illegible work will receive no credit. It is highly recommended you use Word to write up your homework and cut-and-paste your SPSS output when   necessary.

For questions requiring an interpretation or conclusion, phrase these in your own words. If students are suspected of plagiarizing, i.e., having the exact same wording of a free response answer, they will receive no credit for that problem and will be subject to academic discipline.

Scan or take a picture of your written work, consolidate all your work into a single file for uploading to Brightspace.  File format can be PDF or Word document.  Please make sure the scan/picture is clear!

Again, late homework will not be accepted.

There will be a section labeled “Beyond the Basics” for some of the homework

assignments.  These are extra problems for students who might be interested in a bit more theoretical detail underlying some of the topics we are covering in this course. These are not required as part of the assignment and are voluntary only.

o It is highly recommended you attempt the “Beyond the Basics” problems, if you are considering biostatistics as a future career.

Although the individual homework assignments are only worth one point, please remember  the overall homework is worth 10% of your final grade.  So, skipping homework can have an adverse effect on your final grade.