Statistics with Aviation Applications Math 211 Mode of Delivery Lecture Blended Course Syllabus

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1 Statistics with Aviation Applications Math 211 Mode of Delivery Lecture Blended Course Syllabus Credit Hours: 3 Credits Academic Term: Term 4: 23 March May 2015 Meetings: Thurs 18:00-22:00 26 Mar; 2,9,16,23,30 Apr; 7, May. Location: Instructor: Office Hours: Rota, Spain. Dr. Antonio Ruiz Before and after class or by appointment Telephone: Phone: Course Description: This course is a study of basic descriptive and inferential statistics. Topics include types of data, sampling techniques, measures of central tendency and dispersion, elementary probability, discrete and continuous probability distributions, sampling distributions, hypothesis testing, confidence intervals, and simple linear regression. Lecture hours per week (4: 45). Prerequisite(s): MATH 111 or MATH 140 Course Goals: Enable students to select and apply appropriate descriptive and inferential statistical techniques to analyze varying types of data, to defend the rationale for selection of the techniques, and to effectively communicate results of their analyses. Learning Outcomes: Alignment with Worldwide College of Arts & Sciences general education program outcomes is indicated in parentheses. Upon completion of the course, students will be able to do the following: Ver. 12/11 1

2 1. Construct, compute, and use appropriate graphical displays and numerical measures to make accurate conclusions about data. (PO 2 & 7) 2. Identify various discrete and continuous probability distributions, identify skewness and symmetry in a distribution, and compute appropriate parameters and probabilities associated with probability distributions including sampling distributions. (PO 2 & 7) 3. Explain the importance of randomness in sampling, select and apply appropriate sampling techniques. (PO 2 & 7) 4. Select and apply appropriate procedures to estimate parameters and test claims about parameters. (PO 2 & 7) 5. Given a set of data, choose appropriate software, use the software to analyze the data, and accurately interpret the output from the software. (PO 2 & 7) 6. Communicate the results of statistical analyses in a clear and concise manner. (PO 2 & 7) 7. Be a critical consumer of statistics presented by the media and other sources. Accurately interpret the statistics presented, identify ways in which they might be subject to misinterpretation either intentional or unintentional, and apply ethics to the interpretation and presentation of statistics. (PO 2 & 7) 8. Apply the concepts addressed in the course to problem solving including problems related to aviation/aerospace. (PO 2 & 7) List of Program Outcomes for General Education of Arts and Sciences PO1 - Apply knowledge of college level mathematics to defining and solving problems; PO2 - Apply statistical methods in the analysis and interpretation of data for the purpose of drawing valid conclusions relating to the solutions of problems; PO3 - Communicate ideas in written form in both technical and non-technical areas; PO4 - Communicate ideas in non-written form, such as through oral presentations or visual media; PO5 - Recognize the importance of professional, ethical and social responsibility; PO6 - Understand the natural world, to include the impact of the environment on aerospace operations and aerospace operations on the environment, as well as everyday life and professional experiences; PO7 - Use digitally-enabled technology to organize and manipulate data, perform calculations, aid in solving problems, and communicate solutions, ideas, and concepts; PO8 - Use scientific information in critical thinking and decision-making processes; PO9 - Function on multi-cultural and/or multi-disciplinary teams; PO10 - Apply economic principles to identify, formulate, and solve problems within professional and personal environments; PO11 - Identify and participate in professional and personal development activities through organizations and self-directed learning; PO12 - Understand contemporary issues in society PO13 - Recognize the complexity and diversity of the human experience, including cultural, aesthetic, psychological, philosophical, and spiritual dimensions; PO14 - Conduct and report research in accordance with professional standards. Ver. 12/11 2

3 Required Course Materials: Text Gould, R. & Ryan, C. (2013). Introductory statistics: Exploring the world through data (1st ed.), Books a la Carte Edition Plus MyStatLab -- access Card Package. (ISBN-10: ISBN-13: or Custom Version: ISBN and ) ISBN: or (custom) -or Suggested Supplemental Materials: Good scientific calculator. Grading: MyStatLab Assignments (9) 15% StatCrunch Reports (3) 20% MyStatLab Quizzes (6) 12% Course t-test Project 24% Participation/Discussion Board 8% Final Exam Part I 8% Final Exam Part II 13% Total 100% UNDERGRADUATE: Score Grade A (Superior) B (Above Average) C (Average) D (Below Average) Below 60 F (Failure) *This course contains three StatCrunch Reports; two are weighted at 6% and the other at 8%. See StatCrunch activity description for a detailed explanation. MyStatLab (MSL) Homework Modules 1, 2, and 4 each contain two MSL homework assignments. Modules 5, 6, and 7 Ver. 12/11 3

4 each contain one MSL homework assignment. MSL is a virtual mathematics lab. Help is available within MSL for each problem in the assignment. Homework is where the material is learned. Tests are where this learning is demonstrated. The more effort you put into doing homework, the easier the tests will be. The nine MSL assignments are worth 15% of your final grade. StatCrunch Reports There are three StatCrunch Reports that require you to show that you have learned how to use the StatCrunch software by working problems and turning in the StatCrunch output with the problems. StatCrunch Reports in Modules 2 and 6 are worth 6% each and the StatCrunch Report in Module 3 is worth 8% for a total of 20% of your course grade. t-test Course Project A course project, started in Module 8 and submitted by the middle of Module 9, will require you to state a research question, collect and analyze data related to your question, and turn in a written report of your analysis. Detailed instructions and guidance for this activity are provided throughout the course. Your project will be screened by an anti-plagiarism Blackboard tool called SafeAssign (information about SafeAssign is located in the Resources section of the course). This is a required activity and must be completed before taking the final exam. The project is worth 24% of your course grade. Final Exam You will take the course final exam in Module 9 using MSL. It will cover all material from the course and will be in two parts with a time limit on each part. The first part of your final exam is worth 8% and the second part is worth 13% of your final grade. Together, they contribute 21% to your final grade. Library: The Jack R. Hunt Library, located on the Daytona Beach Campus, is the primary library for all Worldwide Campus students. Web: Phone: (800) (ext. 6947) or (386) (Voic is available after hours) Hours: Monday - Friday, 8:00 a.m. - 5:00 p.m. EST Assignments, Discussion Board Participation (If required for Blended Delivery), and/or special administrative: All assignments will be completed in a professional manner and on time, unless prior arrangements have been made with the professor. Blackboard assignments (if required) are graded with class participation. This course includes weekly activities, each of which may have grade points associated with them. Unless prior arrangements have been made with the instructor, students are expected to participate each week, according to the course schedule. This is especially important with regards to discussion activities. Weekly discussions typically include both an initial posting and one or more substantive replies. Note: Proper etiquette has to do with keeping it simple by using proper English and proper spelling spell check works well in Blackboard. Ver. 12/11 4

5 Course Policies: Embry-Riddle is committed to maintaining and upholding intellectual integrity. All students, faculty, and staff have obligations to prevent violations of academic integrity and take corrective action when they occur. The adjudication process will include the sanction imposed on students who commit the following academic violations, which may include a failing grade on the assignment, a failing grade for the course, suspension, or dismissal from the University: 1. Plagiarism: Presenting as one s own the ideas, words, or products of another. Plagiarism includes use of any source to complete academic assignments without proper acknowledgement of the source. All papers submitted for grading in this course may be submitted to safeassign.com - where the text of the paper is compared against information contained in the safeassign.com database. Papers submitted will be included in the safeassign.com database and become source documents for the purpose of detecting plagiarism. 2. Cheating: A broad term that includes the following: a. Giving or receiving help from unauthorized persons or materials during examinations. b. The unauthorized communication of examination questions prior to, during, or following administration of the examination. c. Collaboration on examinations or assignments expected to be individual work. d. Fraud and deceit, that include knowingly furnishing false or misleading information or failing to furnish appropriate information when requested, such as when applying for admission to the University. 3. APA 6 th edition format is the ERAU Worldwide standard for all research projects. Disability and Special Needs: ERAU is committed to the success of all students. It is a University policy to provide reasonable accommodations to students with disabilities who qualify for services. If you would like to request accommodations due to a physical, mental, or learning disability contact the Disability Support Service Office at (386) Course Schedule: Week Meeting Date Mar 26 Mar Topics Introduction and course Familiarization Introduction, Summary & Presentation of Data, Collecting Data, Organizing Categorical Data. Numerical Variation and Distribution, Categorical and Variables and Distributions, Graphs Learning Outcomes LO 1 LO 2 Activities Log in to Blackboard and review class assignments. Chap 1 Chap 2 MSL HW Ch 1 MSL Quiz Ch 1 MSL HW Ch 2 MSL Quiz Ch 2 Ver. 12/11 5

6 2 30 Mar 5 Apr 2 Apr Measures of Center, Variation, z-scores, Interquartile Range, Boxplots Regression Analysis and Correlation, Modeling Linear Trends LO 4 Chap 3, pp Chap 4, pp StatCrunch Assignm 1A and 1B MSL HW Ch 3 MSL Quiz Ch 3 MSL HW Ch 4 MSL Quiz Ch Apr 9 Apr Bootstrapping and Randomization, Central Limit Theorem Bootstrapping and Randomization LO 1, 2, 4 LO 5, 6 Blackboard Reading: Bootstrap Distributions Blackboard Reading: Randomization Test Turn in StatCrunch Assignm 1, StatCrunch Assignm Apr 16 Apr Probability, Addition Rule, Multiplication Rule, Conditional Probability, Simulations, Law of Large Numbers LO 4, 5, 6 Chap 5, pp HW Ch5 MSL Quiz Ch Apr 23 Apr The Normal and Binomial Probability Distributions LO 3 Chap 6, pp Turn in StatCrunch Assignm 2 HW Ch 6 MSL Quiz Ch Apr-3 May 25 Nov Survey Sampling and Inference Course Project: Research Question Prep LO 3, 4, 5, 6 Chap 7 pp HW Ch 7 MSL Quiz Ch May 7 May Hypothesis Testing for Population Proportions LO 4, 5, 6 LO 7, 8 Chap 8 pp Ver. 12/11 6

7 Course Project: t-test Project Instructions Hypothesis Testing for Population Proportions StatCrunch Assignm 3 HW Ch 8 MSL Quiz Ch May No meeting Inferring Population Means Course Project: Project Plan Document Inferring Population Means LO 7, 8 Chap 9, pp Turn in StatCrunch Assignm 3 HW Ch 9 MSL Quiz Ch May No meeting Course Project Plan and Course Project LO 4, 5, 6 LO 7, 8 Chapters 6-9 Final Part 1 and 2 Instructor Bio: I have a PhD in Marine Science along with Masters in Oceanography, Physics and Math and BS in Nautical Science. My graduate work was done at the Naval Postgraduate School, Monterey, California and Cadiz University, Spain. I am currently teaching overseas for Embry- Riddle Aeronautical University in Europe. I have been teaching with ERAU for 30 years. I also teach part-time for the University of Maryland. I have taught courses in Mathematics, Physics, Meteorology, Biology, Environmental Science and of course, Oceanography. I currently live in Cadiz, Spain. Ver. 12/11 7

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