University of Colorado Denver College of Liberal Arts and Sciences MATH 4830/ Applied Statistics Spring 2014

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1 University of Colorado Denver College of Liberal Arts and Sciences MATH 4830/ Applied Statistics Spring 2014 I. Course Overview and Information Professor: Audrey E. Hendricks Office: CU-627 (CU-Building, th Street Across Speer Blvd.) Phone: audrey.hendricks@ucdenver.edu Course website: Class Meeting Times: Monday/Wednesday 5:00-6:15pm in North Office Hours: Monday/Wednesday 3:30-4:15pm (other times available by appointment) Welcome! This course is about applying statistics in real life. For a particular situation or study, you will learn how to choose the appropriate test, check assumptions, perform the calculations, and, most importantly, correctly and coherently interpret the results. This course will likely help you to analyze and understand studies and data from other classes as well as statistics in the news and real life situations. Please note that this is a senior level/master s level course. As such, the material will be at a high level and the workload will be relatively heavy. The more you put into the course, the more you will get out! Course Announcements: Course announcements will often be made via . s will be sent to your ucdenver.edu address in accordance with university policy. You are responsible for the information contained in any messages I send you, regardless of whether the information is repeated in class. It is your responsibility to maintain this address. Canvas: Course homework and resources (e.g. course syllabus, web resources, etc.) will be provided on the Canvas course site. It is your responsibility to know how to access this site. Contact me or Canvas help for any questions.

2 II. Course Description, Learning Outcomes, and Prerequisites Course Credits: 3 Hours Course Description: Review of estimation; confidence intervals and hypothesis testing; ANOVA; categorical data analysis; non-parametric tests; linear and logistic regression. Learning Objectives: By the end of this course, students should have a basic understanding of How to select and apply an appropriate statistical technique for a given set of data Clearly interpret and communicate the results of a statistical analysis (both written and orally) Learning Outcomes: This course will help build on several learning outcomes including the following: Critical Thinking Students will enhance their critical thinking by learning when and how to apply the appropriate statistical method given a particular study. Students will further practice questioning existing analyses in the public (i.e. news stories) and in science (i.e. journal articles). Although all of the assignments and exams will require critical thinking, the statistics in the news assignment and the final project will best measure each student s ability to use critical thinking skills to complete the appropriate statistical analysis and to critic others statistical analysis. Problem Solving Students will develop their problem solving skills by working through many statistical analyses. Each student s problem solving skills will be measured by their performance on the homework quizzes and exams. Written and Oral Communication An essential aspect of statistics is the ability to communicate the thought behind and results of a statistical analysis both written and orally. Students will develop and be assed on their written communication through their homework, exams, and final project. They will develop their oral communication through statistics in the news, class participation, and their final project presentation. Students will be assed on their oral communication through their final project presentation. Prerequisites: An introductory statistics course such as MATH 2830 or permission of instructor. Further, it is assumed that you: Understand o Basic sampling methods (e.g. a simple random sample) o Different types of variables (continuous versus categorical, etc.) o Confidence level and p-value o Normal distribution and sampling distributions Can calculate/produce o Basic summary statistics such as the mean, median, mode, variance, standard deviation, range, and interquartile range o Confidence intervals and hypothesis tests for a population mean, proportion, a difference of population means, and a difference in population proportions o Simple visualizations of the data (e.g. histograms, boxplots, bar charts, etc.)

3 III. Required Text and Materials Required Textbook: Discovering Statistics Using SPSS, 4 th edition by Andy Field Additional Materials Required: Access to a computer with SPSS Statistics installed. SPSS is a statistical software package commonly used in academia and industry. SPSS can be installed on Windows and Apple computers. SPSS is installed on the MERC demonstration room computers (NC-4009) and can also be rented by students (for six months or more) at a discounted rate. An inexpensive place to rent the program is (though there may be cheaper retailers). There are many different versions of SPSS you can purchase. The version recommended for this course is SPSS Statistics Standard Grad Pack for $ download fee. Access to a computer with a word processing program such as Microsoft Word or Open Office to complete homeworks, exams, and projects. IV. Evaluation/Grades Final Grade Components: Your final grade will be determined as follows: Homework Quizzes (lowest two scores dropped) 25% Final Project 25% 2 Exams (25% each) 50% Grading Scale: Final letter grades will be determined by the following scale: Percentage Letter Grade 94 or higher A A B B B C+ Percentage Letter Grade C C D D D F Homework Quizzes: There will be weekly homework assignments from which one question will be chosen for a quiz. Unless otherwise stated, no notes or resources may be used on the quiz. All homework questions will be assigned at least one-week prior and will also be available on Canvas. The two lowest homework quizzes will be dropped. One of the quiz grades will be determined from the statistics in the news assignment (see below).

4 Statistics in the News: Once during the semester, students will be required to give a 5-10 minute presentation/discussion on a news story or a simple journal article. The presentation will require briefly summarizing the statistics in the story or article and moderating a brief discussion about the correct (or incorrect) ways the statistics might be interpreted. Students will sign up for their date on January 27 th. This assignment will count as a homework quiz. Exams: There will be two exams. One exam on Wednesday March 5 th and one exam on Wednesday April 30 th. Final Project: The Final Project will be distributed on Wednesday April, 2 nd. A written report for the final project will be due on the last day of class (finals week May 12 th or 14 th ). A minute presentation of the final project will be given during one of the last two days of class (May 7 th, & finals week May 12 th or 14 th ). Students who complete the statistics in the news assignment first will have first choice on signing up for their final project presentation date and time slot. 5830: Students enrolled in the master s level of this course will be required to understand the course material at a higher level and as such will have additional or different homework, quiz, and exam questions in order to assess the students additional level of understanding. Additionally, 5830 students will be required to complete an independent (rather than a group) final project. Late Assignments or Missed Exams: Without prior approval from me or a documented health, disability, or emergency reason, missed homework quizzes, exams, or the final project will be scored as a zero.

5 V. Tentative Course Outline Date Topic Reading from Discovering Statistics Jan 22 Jan 27 Syllabus & Review Chapter 1 Review Chapters 1 & 2 Jan 29 Review Chapters 1 & 2 Feb 3 Introduction to SPSS Chapters 3 & 4 Feb 5 Introduction to SPSS (Homework 1 Due / Quiz 1) Chapters 3 & 4 Feb 10 Model Assumptions & Outliers Chapter 5 Feb 12 Model Assumptions & Outliers (Homework 2 Due / Quiz 2) Chapter 5 Feb 17 Comparing Two Means Chapter 9 Feb 19 Comparing Two Means (Homework 3 Due / Quiz 3) Chapter 9 Feb 24 Feb 26 March 3 March 5 March 10 Correlation Chapter 7 Correlation (Homework 4 Due / Quiz 4) Chapter 7 Regression Chapter 8 Exam 1 Regression Chapter 8 March 12 Regression (Homework 5 Due / Quiz 5) Chapter 8 March 17 Regression Chapter 8 March 19 Regression (Homework 6 Due / Quiz 6) Chapter 8

6 March 24 March 30 March 31 Spring Break! Regression Chapter 8 April 2 Logistic Regression (Homework 7 Due / Quiz 7) Chapter 19 April 7 Logistic Regression Chapter 19 April 9 ANOVA (Homework 8 Due / Quiz 8) Chapter 11 April 14 ANOVA Chapter 11 April 16 ANCOVA (Homework 9 Due / Quiz 9) Chapter 12 April 21 ANCOVA Chapter 12 April 23 Non-parametric (Homework 10 Due / Quiz 10) Chapter 6 April 28 April 30 May 5 May 7 May 12/May 14 (Monday/Wednesday) Non-parametric Chapter 6 Exam 2 TBD Project Presentations Project Presentations (Finals Week)

7 VI. Other Resources The Learning Resources Center The Learning Resource Center is where students go to get help or insight with class assignments, course-loads, and study skills. The Center also helps with arranging tutoring sessions, which take place in the days or evenings. North Classroom Building (NC) Room 2006 (303) Monday - Thursday 9am-7pm Friday 9am-5pm Program Access for Persons with Disabilities The University of Colorado Denver is committed to providing reasonable accommodations and access to programs and services to persons with disabilities. Students should contact the Disabilities Resources Offices. North Classroom building 2514; Phone # , TTY Monday Friday: 8am 5pm

8 Academic Success and Advising Center This office serves as the first point of contact for students who are pre-business, preengineering, or who have not declared a major in CLAS or CAM. In addition, the center provides general information and resource referral to all students. North Classroom Building (NC) Room 2024 Phone # ASAC@ucdenver.edu Monday, Tuesday, Thursday, Friday: 8am 1pm, 2pm 5pm Wednesday: 8am 1pm, 2pm 6pm Career Center The Career Center offers a full array of services that prepare students for career success, such as resume help, internship and career counseling and they have a large career library. Tivoli Student Union Room 267 Phone # Monday Friday: 8am 5pm The University of Colorado Denver, provides many other services and resources. See

9 Spring 2014 CLAS Academic Policies The following policies pertain to all degree-seeking students in the College of Liberal Arts and Sciences. Schedule verification: It is each student s responsibility to verify online that his/her official registration is correct: verify before classes begin and prior to the drop/add deadline. Failure to verify schedule accuracy is not sufficient reason to justify a late add or drop. Students must activate and regularly check their official student account for CU Denver business: Those who forward must check CU Denver regularly for messages not automatically forwarded. Waitlists: Students are not automatically notified if they are added to a class from a waitlist. Students are not automatically dropped from a class if they never attended, stopped attending, or do not make tuition payments. Waitlists are purged after the 1st week of classes, after which a paper Schedule Adjustment Form (SAF or drop/add form) is required. It is the student's responsibility to get the form (online or at the Advising Office, NC 4002), have it signed, deliver it to the Registrar (Annex 100) or the Student Services Center (NC 1003), and verify her/his schedule online. Late adds (after 5 February) will be approved only when circumstances surrounding the late add are beyond the student s control. This will require a written petition and verifiable documentation. Petition forms are available in NC The signature of a faculty member on a SAF does not guarantee that a late add petition will be approved. Late drops/withdrawals (after 7 April) will be approved only when circumstances surrounding the late drop have arisen after the published drop deadline and are beyond the student s control. This will require a written petition and verifiable documentation. The signature of a faculty member does not guarantee that a late drop/withdrawal petition will be approved. Tuition: Students are responsible for completing arrangements with financial aid, family, scholarships, etc. to pay their tuition prior to Census Date (5 February). Students who drop after that date are (1) financially responsible for tuition and fees, (2) academically responsible and will receive a "W" grade, and (3) are ineligible for a refund of COF hours or tuition. Graduation: Undergraduate students wishing to graduate in Spring 2014 must complete the online Graduation Application form, in the UCD Access Portal, and meet with their academic advisor to obtain a graduation application. This application must be submitted by Census Date (5 February). You can obtain an application only after meeting with your advisor. There are no exceptions to this policy. Graduate students wishing to graduate in Spring semester 2014 must complete the online Graduation Application form, in the UCD Access Portal, and have a Request for Admissions to Candidacy on file with the CU Denver Graduate School (LSC 1251) no later than 5 PM, February 5, Important Dates and Deadlines January 20, 2014: Martin Luther King Holiday. Last day to withdraw from all classes via UCDAccess and receive a refund of the $200 advance payment and all tuition. January 21, 2014: First day of classes. January 26, 2014: Last day to add or waitlist classes using UCDAccess. After this date, a Schedule Adjustment Form (SAF) is required to change, add, or drop. January 27, 2014: Last day to drop without a $100 drop charge. No adds permitted on this day. January 28 February 5, 2014: UCDAccess registration is closed; registration now requires a SAF with faculty signature. Verify your registration via UCDAccess. You are not registered for a course unless your name appears on the official roster; conversely, your name may have been added automatically from the

10 waitlist without notification, which means that you will be held responsible. February 5, 2014: Census date. 2/5/14, 5 PM: Last day to add structured courses without a written petition for a late add. This is an absolute deadline and is treated as such. This does not apply to independent studies, internships, project hours, thesis hours, dissertation hours, and modular courses. 2/5/14, 5 PM: Last day to drop a course or completely withdraw from Spring 2014 using a SAF and still receive tuition refund, minus the drop fee. After this date, tuition is forfeited and a "W" will appear on the transcript. This includes section changes. This is an absolute deadline. 2/5/14, 5 PM: Last day to request Pass/Fail or No-Credit option for a course. 2/5/14, 5 PM: Last day for a graduate student to register for a Candidate for Degree and last day for a Ph.D. student to petition for a reduction in hours. 2/5/14, 5 PM: Last day to apply for Spring 2014 graduation. If an undergraduate, you must make an appointment and see your academic advisor to apply. If a graduate student, you must complete the Intent to Graduate and Candidate for Degree forms. February 17-26, 2014: Faculty can use the Early Alert system. March 24-30, 2014: Spring Break-(no classes; campus open). April 7, 2014, 5 PM: Last day for non-clas students to drop or withdraw without a petition and special approval from the academic dean. After this date, a dean s signature is required. April 22, 2014, 5 PM: Last day for CLAS students to drop or withdraw with signatures from the faculty and dean but without a full petition. After this date, all schedule changes require a full petition. Petitions are available in NC 4002 for undergraduates and in the CU Denver Graduate School offices for graduate students. May 12-17, 2014: Finals Week. No schedule changes will be granted once finals week has started-- there are no exceptions to this policy. Commencement is May 17. May 22, 2014: Due date for faculty submission of grades (tentative). May 26, 2014: Spring final grades available on UCD Access (tentative).

11 Academic Dishonesty Student Code of Conduct: Students are expected to know, understand, and comply with the ethical standards of the university, including rules against plagiarism, cheating, fabrication and falsification, multiple submissions, misuse of academic materials, and complicity in academic dishonesty. For suggestions on ways to avoid academic dishonesty, please see the Academic Honesty Handbook at Plagiarism is the use of another person s ideas or words without acknowledgement. The incorporation of another person s work into yours requires appropriate identification and acknowledgement. Examples of plagiarism when the source is not noted include: word-for-word copying of another person s ideas or words; the mosaic (interspersing your own words here and there while, in essence, copying another s work); the paraphrase (the rewriting of another s work, while still using their basic ideas or theories); fabrication (inventing or counterfeiting sources); submission of another s work as your own; and neglecting quotation marks when including direct quotes, even on material that is otherwise acknowledge. Cheating involves the possession, communication, or use of information, materials, notes, study aids, or other devices and rubrics not specifically authorized by the course instructor in any academic exercise, or unauthorized communication with any other person during an academic exercise. Examples of cheating include: copying from another s work or receiving unauthorized assistance from another; using a calculator, computer, or the internet when its use has been precluded; collaborating with another or others without the consent of the instructor; submitting another s work as one s own. Fabrication involves inventing or counterfeiting information creating results not properly obtained through study or laboratory experiment. Falsification involves deliberate alteration or changing of results to suit one s needs in an experiment or academic exercise. Multiple Submissions involves submitting academic work in a current course when academic credit for the work was previously earned in another course, when such submission is made without the current course instructor s authorization. Misuse of Academic Materials: The misuse of academic materials includes, but is not limited to, the following: 1. Stealing or destroying library or reference materials or computer programs. 2. Stealing or destroying another student s notes or materials, or having such materials in one s possession without the owner s permission. 3. Receiving assistance in locating or using sources of information in an assignment when such assistance has been forbidden by the instructor. 4. Illegitimate possession, disposition, or use of examinations or answer keys to examinations. 5. Unauthorized alteration, forgery, or falsification. 6. Unauthorized sale or purchase of examinations, papers, or assignments. Complicity in Academic Dishonesty involves knowingly contributing to or cooperating with another s act(s) of academic dishonesty.

12 University Wide Policies Student Code of Conduct Accommodations Academic Freedom Family Educational Rights and Privacy Act (FERPA) Attendance pdf Discrimination and Harassment Policy and Procedures itylife/sexualmisconduct/denverpolices/pages/denverwelcome.aspx Grade Appeal Policy

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