- Download this PATH 3610 study guide to get exam ready in less time! Study guide uploaded on Apr 17, 2017. PATH 3610 Midterm: midterm 2 key information.
- PATH.3610 DE Principles of Disease (restricted elective) BIOM.3010 Comparative Mammalian Anatomy (restricted elective) ANSC.3120 Animal Nutrition ANSC.3080 Agricultural Animal Physiology Winter Semester 6 PATH.3040 Principles of Parasitology (restricted elective) MBG.3060 Quantitative Genetics (used for vet school - Genetics).
View MIDTERM 1 Path.docx from PATH 3610 at University of Guelph. MIDTERM 1 Question 1 1/1 points The primary change in hemolytic jaundice is: inadequate bilirubin excretion increased production of. PATH. 3610 – Principles of Disease W (3-0) 0.50 A course designed for students with particular interests in nutrition and biology. The course presents basic concepts of disease in the cells, tissues, organs and fluids of the body.
Path 3610 Midterm 1 Quizlet
|COURSE WEB SITE||http://mnstats.morris.umn.edu//introstat/|
|# OF CREDITS :||4|
|PREREQUISITE:||MATH. 1202 OR 1302 OR #|
|DAYS & TIME:||10:00-10:50|
|BUILDING & ROOM:||SS. 136|
|INSTRUCTOR:||Dr. Engin A. Sungur|
|OFFICE HOURS:||MTWThF, 1-2|
COURSE DESCRIPTION: The course will concentrate on ProbabilityTheory and Statistical Methods. Probability theory; set theory,axiomatic foundations, conditional probability and independence,Bayes's Rule, random variables. Transformations and expectations;expected values, moments and moment generating functions. Commonfamilies of distribution; discrete and continuous distributions.Multiple random variables; joint and marginal distributions, conditionaldistributions and independence, covariance and correlation, multivariatedistributions. Properties of a random sample and central limittheorem. Markov chains, Poison processes.
COURSE MATERIALS: (i) Sheldon, M. R., Introduction to ProbabilityModels (sixth edition), Academic Press, 1993
(ii) Study Guide
EXAMINATION POLICY: Two midterm examinations and a finalexam will be given. Time table for the examinations is given below:
|MIDTERM 1||JANUARY, 26 (Tuesday)||SS. 136||10:00-10:50|
|MIDTERM 2||FEBRUARY, 25 (Thursday)||SS. 136||10:00-10:50|
|FINAL||MARCH, 16 (Tuesday)||SS. 136||9:30-11:30|
EACH EXAMINATION (INCLUDINGTHE FINAL) WILL BE CLOSED-BOOKS AND CLOSED-NOTES.
HOMEWORKS: Eight homeworks will be assigned. No late homeworkswill be accepted without a valid excuse. Solutions will be availableat the following class.
PLEASE FEEL WELCOME TO SEE ME OUTSIDE OF THE CLASS, ANYTIME, IF YOU HAVE QUESTIONS, PROBLEMS, OR COMMENTSPERTAINING THE COURSE WORK.
The detailed syllabus of the course is given in the followingtable.
|TOPIC||TEXT BY ROSS||STUDY GUIDE|
|Introduction & Sample Space and Events||§ 1.1-1.2||§ I.1-I.2|
|Probabilities||§ 1.3||§ I.4-I.5|
|Conditional Probabilities||§ 1.4||§ I.5|
|Independent Events||§ 1.5||§ I.5|
|Bayes' Formula||§ 1.6||§ I.5|
|Random Variables||§ 2.1||§ II.2-II.3|
|Discrete Random Variables||§ 2.2||§ II.1 Discrete Mathematics,|
|Continuous Random Variables||§ 2.3||§ II.1 The Derivative of a Function, Derivatives of the Composite Functions, The Definite Integral, Antidifferentiation, Evaluation of the Integrals, Methods of Integration, Some Special Functions|
|Expectation of a Random Variable||§ 2.4||§ II.1 Evaluation of the Definite Integrals by Using Antiderivatives, Methods of Integration|
|Jointly Distributed Random Variables||§ 2.5||§ II.1 Some Results Involving Multivariate Calculus|
|Moment Generating Functions||§ 2.6||§ II.1 Methods of Integration, Some Results Involving Limits|
|Limit Theorems||§ 2.7||§ II.1 Some Results Involving Limits|
|Conditional Probability &|
|Chapter 3||§ II.1|
|Markov Chains||Chapter 4||§ I.6 & II.1|
|The Exponential Distribution & the Poisson Process||Chapter 5||§ II.1|
The organization of the in-class activities are summarized inthe following flowchart. The main components of the organizationstructure are:
(i) Summaries and Outline: These two components, hopefully,will provide a smooth transition between the topics and lectures.These will answer three basic questions: Where have we been?,Where are we going?, and What have we learned?
(ii) Student Evaluators: Class participation and discussionare very important on the learning process. Students are encouragedto ask questions in the class. Questions, comments could helpthe instructor to set up his/her pace. The input from the studentsshould be constant. If you point out the weaknesses of the instructor,and the problems with the course in general as soon as possibleyour learning process will be enhanced. To formalize and promoteactive learning, each in-class activity will be evaluated by thetwo students. These students will be responsible to point outall the problems that might affect the learning of the rest ofthe class. For example, the topics that are not clearly covered,pace of the lecture, use of the blackboard, problems with takingnotes, etc.Time to timestudent evaluators will be askedto make a summary of the previous class.
Kyle Gee Barina
Paul Thaddeus Brown
Gina M. Garding
Malcolm C. Gold
James D. Harman
James R. Johnson
Kristin L. Kaster
Debra S. Kielhold
Thomas P. Kluis
Joel H. Leet
Dave A. Logan
Terra L. Miller
Amy E. Mounts
Paul E. Olson
Naomi C. Pollestad
David E. Rausch
Rufino R. Rodriguez
Jared Christopher Schmillen
Michael J. Schwerin
Christopher J. Sieling
Daniel Thomas Wolters
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(iii) Minute paper: Time to time you will be asked to answerthe following three questions:
1. What was the most important thing you learned today?
Path 3610 Midterm 1 Quizlet
2. What was the most important thing you learned yesterday?
3. What questions are uppermost in your mind as we conclude thisclass session?
Answers to these questions will help the instructor on settingup her/his pace, pin-point the topics that the students are havingproblems on understanding, to correct misunderstanding etc. Thequestions are related with effectiveness of the lecture, retentionof the information delivered, and effectiveness of the teachingin general.
The topics that will be covered are mostly in the text book. Ifa topic is not in your textbook, then it will be pointed out inthe lecture and/or handouts will be provided.
Exams will cover the material discussed in the class andthe readings in the text. Before the exam, an information sheetwill be provided. This information sheet (worksheet) willinclude (a) place and date of the examination, (b) the detailedtopics that will be covered in the examination, (c) the toolsthat students must bring to the examination (such as statisticaltables, calculators etc.). One day before the exam, the topicsthat will be included in the exam will be reviewed, andimportant points that should be remembered will be pointed out.Right after the examination, the students will get the solutions.The anticipated grading time of the exams is 1 day.
The students should plan on taking the exam on the scheduled date.Illness (Health Service Excuse) or a Chancellor's excuse willbe honored as a reason for taking the exam at other than the scheduleddate. (Make-ups creates a data which is not independent and identicallydistributed. As you will learn in this course, lack of these propertiescreates a big problem on the inference based on such data).
No late homeworks will be accepted without a valid excuse.
The difficulty of the exams will be so arranged that there willbe no need for the 'normalization' of the scores basedon the Gaussian Distribution (known as making a curve). Trendson the scores, attendance to the lectures, class participationetc. will be considered on the determination of the final grades.