ࡱ> ] X9bjbj _dx-\x-\0h\\8 TU/"">"" .......14.";"^""".}/((("j.(".((**-a#R*.%/0U/*15#>15**15+ ""("""""..%&"""U/""""15"""""""""\> : GEOG 306 Introduction to Quantitative Methods for Geographic and Environmental Sciences Summer Session II 2014 July 14th August 24th  Time: Monday and Wednesday 6:00 9:45 PM Location: Canvas Adobe Live Connect (Online) and ELMS Website:  HYPERLINK "http://elms.umd.edu" http://elms.umd.edu Instructor: Amanda Hoffman-Hall ( HYPERLINK "mailto:ahall2@umd.edu" ahall2@umd.edu) Office hours by appointment TA: Patrick McDonough ( HYPERLINK "mailto:pmcd@terpmail.umd.edu" pmcd@terpmail.umd.edu) Office hours by appointment  Course Information Overview: This course is an introduction to quantitative methods for geographic and environmental sciences. Geographers and other environmental and social scientists use quantitative methods, such as statistics, to measure, describe, and make estimates about variables across the landscape for a variety of reasons, such as developing and testing hypotheses or to support decision making. Increasingly large amounts of spatial data are being generated and used by all levels of government as well as by other private and public institutions. Thus, developing solid skills in quantitative analysis should be a priority for any student in these fields. The class covers the fundamentals of statistical analysis including data display, data description and summary, statistical inference and significance tests, analysis of variance, correlation and regression. Concepts will be presented and developed through the use of real world data sets that cover both the natural environment as well as the social environment. Online Course Considerations: Lectures will be live online utilizing Canvas (available at  HYPERLINK "http://elms.umd.edu/" http://elms.umd.edu) and Adobe Live Connect. Make sure that you have access to decent internet connection. Computer lab assignments are completed individually online and the course TA will be available to assist through Adobe Live Connect or using the conference feature on Canvas. The Department of Geography computer labs are fully equipped with all of the necessary software in case if anyone wants to make use of it. A headset with microphone is required. A webcam is optional. Attendance is mandatory for all sessions and will be recorded. Objectives: The main goal of this class is to provide a foundation in the quantitative analysis of spatial and other data, with a particular emphasis on statistics. In particular students will: (1) Develop an understanding of important theoretical concepts in statistical analysis; (2) Gain experience in the application of statistics to spatial and other data using specific statistical software; (3) As part of problem sets, students will learn concepts and skills in using R (statistical software). Who Should Take This Class? This class is appropriate for anyone majoring in the geographic (both physical and human) and environmental sciences. Students whose focus is on other aspects of spatial data handling and analysis, such as those in GIS and remote sensing will find it useful. There are no prerequisites for the class. Course Materials Required Text: J. Chapman McGrew, Jr., Arthur J. Lembo, Jr., Charles B. Monroe. 2014. An Introduction to Statistical Problem Solving in Geography, 3rd edition, Waveland Press, Inc. ISBN 10: 1-4786-1119-7 ISBN 13: 978-1-4786-1119-6 A hard copy of the book will be available at the university bookstore, or can be purchased for $49.95 from the Waveland Press website ( HYPERLINK "http://www.waveland.com" www.waveland.com). An e-book is also available for rent for $24.98 ( HYPERLINK "http://www.coursesmart.com/9781478611196" http://www.coursesmart.com/9781478611196). If you can find an earlier edition for cheaper that will suffice. Optional Text: An Introduction to R, available free as a pdf from http://www.r-project.org/ There are a number of introductory statistics web sites that are very good and may help you considerably in your understanding by providing a different perspective. Three that are recommended are below. Statistics at Square 1: http://bmj.bmjjournals.com/statsbk/index.shtml Electronic Statistics Textbook: http://www.statsoft.com/textbook/stathome.html Simple R: Using R for Introductory Statistics http://www.math.csi.cuny.edu/Statistics/R/simpleR/index.html Further readings, if any, will be announced in class or by e-mail. Software: The required software for this class is R. R is the open source, freeware version of Splus, one of the most powerful and versatile statistical packages, and is available for free download for use on PC, Mac, UNIX and Linux environments. The software is available in the Geography Open Lab on the PC machines, though the availability of these labs is limited for summer courses. If you have a laptop or home computer you can download R for free from here:  HYPERLINK "http://www.r-project.org/" http://www.r-project.org/. This class will be using R-Studio as an interface to R. You should install R-Studio after installing R. R-studio is available for Windows, Mac and Linux at  HYPERLINK "http://www.rstudio.com/ide/download/desktop" http://www.rstudio.com/ide/download/desktop . All students are REQUIRED to have a UMD GLUE account, and they must have a UMD email address. We will frequently use email for communication in this class, as well as to distribute materials, and we will only use UMD email addresses. Also, make sure that you put the prefix Geog306_ in the subject line of any e-mail sent to the instructor or TA. This will make sure that your email doesnt get lost or sent to a spam folder. Finally, all students should have a scientific calculator for use during exams and assignments. Most computers come with a calculator built in (for example, on a PC when Calculator is opened click View -> Scientific to change to a very basic scientific calculator). Hardware: A webcam with a microphone is encouraged but optional. Grading GradesPercentage RequiredAssignmentPercentage of Total GradeA>90 to 100Homework/Labs40%B>80 to <90Midterms (2)30%C>70 to <80Final20%D>60 to <70Participation10%F<60Total100% Homework/Labs (40%): After each lecture there will be an online laboratory exercise. A TA will be available through Canvas to guide you should you encounter any difficulty. After completing the lab you will have a homework assignment which is due before the next lecture. Homework assignments must be submitted online through Canvas, they can be typed or handwritten and scanned. Only .docx, .doc, or .pdf files will be accepted. Homework is due before the start of the next class (6 PM). There will be 9 Lab/Homeworks which will count for 40% of your final grade. Midterms (15% each 30% total): There will be two exams throughout the course. They will be a mix of multiple choice, fill in the blank, short answer, and calculations. They will be administered online. All exams (including the final) are open note. You may NOT work in groups or with a partner. You will be given 2 hours to complete each exam. Each exam is worth 15% of your final grade, for a total of 30%. Final (20%): The final will be the same format as the midterms but will cover all material learned during the course. It is worth 20% of your final grade. Participation (10%): Online lectures will be given live but will be recorded so that you may view them again as a study guide. Attendance at the lectures is not required HOWEVER each lecture will contain at least 3 miniature quizzes which will count towards your participation grade, worth 10% of your final grade. Make-up and Late Assignment Policies: Assignment due dates are explicitly stated. Assignments will be accepted up to 72 hours (or 3 days) after the due date. Each day late for the assignment will result in a 20-point (20%) deduction for the assignment. This penalty begins 1 minute after the due date! Technical excuses including "computer system error", "didn't print", etc. will not be accepted as reasons for late work. You are expected to start the work early. Never underestimate the time you will spend on the assignments. If you are ill or physically indisposed and cannot submit your assignment on time, you must notify the instructor before class and provide a written doctors note when you return for you to have a chance to make up the assignment. Make-up exams will be given only for University approved excused absences. This policy may seem strict, but this class will move rapidly and it is in your best interest to turn in everything on time to avoid falling irrecoverably behind. Please contact the instructors if you are struggling and we will aid you as best we can. Also, if you cannot complete the assignment on time, it is better to turn in partially completed work than nothing at all! Administrative Details Academic Misconduct: The University of Maryland, College Park has a nationally recognized Code of Academic Integrity, administered by the Student Honor Council. This Code sets standards for academic integrity for all undergraduate and graduate students. All students are responsible for upholding these standards for this course. It is very important for you to be aware of the consequences of cheating, fabrication, facilitation, and plagiarism. For more information on the Code of Academic Integrity or the Student Honor Council, please visit http://www.shc.umd.edu. All work turned in must be the students own. Students may work together on problem sets, however, each student absolutely must turn in their own work, from their own computer, and any discussion must be theirs alone, and not attributable to another person or group. Students must list everyone they collaborated with on each homework problem. Students may not use any textual discussion, calculations or programs from any other student or group of students. Disability Statement: Any student who feels he or she may need an accommodation based on the impact of a disability should contact the instructor in the beginning of the semester to discuss his or her specific needs. Please contact the Office of Disability Support Services (http://www.counseling.umd.edu/DSS/) at 301.314.7682 in Counseling Center, 0126 Shoemaker Building to coordinate reasonable accommodations in case of documented disabilities. You will need to furnish a disability certificate from the counseling center on the first day of class. In order to keep from falling behind, I would HIGHLY suggest completing the readings a few hours (or the day) before lecture, watching the lecture from 6 8 PM, lab from 8 9 PM, and completing your homework immediately following lab. Each homework is an extension of the lab so it is best to do it while it is fresh in your memory. If you maintain this schedule you will have no problem turning in your homework on time, while also giving yourself more free time/study time on days we do not have class. There will never be a lab after an exam, however, you will be expected to turn in the previous lectures homework before each exam. GEOG 306 Course Schedule DateReadingsHW DueLecture Lab07/14/2014Chapter 1Lecture 0: Course Overview, Introduction to StatisticsHW 0: Course Set Up07/16/2014Chapter 2HW 0 @ 6 Lecture 1: Geographic Data and Data BasicsLab 1: Introduction to R07/21/2014Chapters 3, 4HW 1 @ 6Lecture 2: Descriptive Statistics Lab 2 : Descriptive Statistics07/23/2014Chapters 5, 6HW 2 @ 6Lecture 3: ProbabilityLab 3: Probability07/28/2014 Chapters 7, 8HW 3 @ 6Lecture 4: Data Sampling, Sampling Design, and Estimation in Sampling Lab 4: Sampling07/30/2014Midterm 1 [Online] Open Book: 6:00 PM 8:00 PM Covers Lectures 1 408/04/2014Chapter 9HW 4 @ 6Lecture 5: Elements of Inferential Statistics and Hypothesis Testing Lab 5: Inference08/06/2014Chapter 10HW 5 @ 6Lecture 6: Analysis of Variance: Two Sample Tests Lab 6: 2 sample tests08/11/2014Chapters 11, 16HW 6 @ 6Lecture 7: Analysis of Variance: Multiple Sample Test, Correlation Lab 7: ANOVA/ Correlation08/13/2014Midterm 2 [Online] Open Book: 6:00 PM 8:00 PM Covers Lectures 5 708/18/2014Chapters 17, 12HW 7 @ 6Lecture 8: Regression/Goodness-of-FitLab 8: Regression/Chi-Square08/20/2014HW 8 @ 6 Final Exam [Online] Open book: 6:00 PM 8:00 PM CumulativeNote: The GEOG 306 course schedule is tentative and is subject to revision by the instructor     GEOG306: Introduction to Quantitative Methods Summer II 2014 PAGE  -PAGE 6-    "23:;XY_jopƲyoeo[eMeMehhH*PJnH tH h<PJnH tH hPJnH tH hnPJnH tH  hhjjCJPJaJnH tH &hh<5CJPJ\aJnH tH &hh;tc5CJPJ\aJnH tH &hhjj5CJPJ\aJnH tH  h5CJ(PJ\aJ(nH tH &hh5CJ(PJ\aJ(nH tH (jhhCJ(UaJ(mHnHu Yp8 9 $ & ' : ; 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