Stat 215 Syllabus Spring 2016

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1 Stat 215 Syllabus Spring 2016 Instructor: Prof. Robert Mnatsakanov Lecture Time: 10:00 11:00 am T R Class Location: 259 Hodges Hall Lab Location: G33 Eisland Hall Office Location: 126 Stansbury Hall Office Hours: Monday, 3pm-5pm Office Phone: Dept. Phone: Prerequisite: C or better in Math 156 (Calculus II) Lab Assistant: Lab M 12:30-11:30 am; W 9:30-11:30 am felmagbr@mix.wvu.edu G 29 EIE Lab Grader: Your lab TA is the grader for your section of Stat 215. Course Description: This course uses a broad brush to introduce the fascinating science of statistics to students from many diverse fields. Examples and applications from biology, environmental science, education, political science, public policy, behavioral sciences, public health and medicine will be used to enhance the relevancy of the basic methods of descriptive and inferential statistics that form the core learning in this course: descriptive measures; random variables; sampling distributions; estimation; tests of hypothesis; chi-square tests; regression; and, correlation. This course is offered in the General Education Curriculum under Objective 2: Basic Mathematical Skills and Scientific Inquiry; and Objective 4: Contemporary Society. The course material encourages critical thinking and challenges students to employ the scientific method to examine contemporary issues, ideas, and conventional wisdom. Course Objectives: In this course students will: 1. Acquire experience in applying mathematics, and specifically statistics, to solve real-life problems. 2. Learn to approach and analyze problems logically and mathematically. 3. Learn to communicate mathematically by being provided opportunities to read, write, and discuss ideas and concepts in statistics. 4. Learn to value mathematics and specifically statistics, as a universal scientific language. 5. Learn to value the role of mathematical and specifically statistical concepts and methodologies in addressing research that arise in the natural and social sciences and in humanities. This course provides the student with the foundations of statistical theory and the opportunity to practice using several statistical methods to organize, analyze, and present data, to design experiments appropriate to the information desired, to test hypotheses, to make judgments about data and to predict future behavior based on available data. Descriptive statistics, simple and

2 conditional probability, probability distributions, and topics in inferential statistics such as hypothesis testing and estimation are emphasized. Student Learning Outcomes: Upon successful completion of this course, all students are expected to demonstrate the ability to: 1. Understand the difference between descriptive and inferential statistics; 2. Understand the concepts of population and sample; 3. Understand how to obtain a random sample; 4. Understand other sampling methods such as with and without replacements from a finite population; 5. Understand the concept of a random variable; 6. Identify the experimental unit and the variable type and to specify the variable values; 7. Organize data for statistical analysis, construct, interpret, and understand graphical displays of a set of observed data; 8. Calculate, interpret, understand, and identify when to use the sample mean, quartiles, IQR, median, mode, and standard deviation and identify outliers; 9. Measure and assess the association between two quantitative variables, and understand what the Pearson correlation coefficient measures; 10. Understand the idea of least squares estimation, interpret the intercept and slope of a least squares regression line, understand the connection between correlation and regression analysis; 11. Compute, understand and interpret the theoretical probability of an event, construct and interpret probability distributions, know how the laws of probability are used to compute probabilities of compound and conditional events; 12. Understand and interpret the probability mass function of a discrete random variable; 13. Understand and interpret the probability density function of a continuous random variable; 14. Understand and construct the cumulative distribution function of a numeric random variable; 15. Understand and work with linear functions of random variables; 16. Understand and work with various probability distributions, including the Bernoulli distribution, Binomial distribution, Poisson distribution, Geometric distribution, Uniform distribution, Normal distribution, Multinomial distribution, t-distribution, and Chi-square distribution; 17. Understand, examine the sampling distribution of a statistic; 18. Calculate the expected value and variance of a numeric random variable; 19. Identify and understand binomial, poisson, and normal random variables, compute their probabilities, means and variances; 20. Compute z scores and understand the z-score as a measure of relative position; 21. Use Normal approximation to compute binomial probabilities; 22. Understand and compute the mean and standard deviation of the sampling distribution of sample means and use the Central Limit Theorem to answer probability questions involving the sample mean; 23. Compute and interpret confidence intervals on population means, population proportions, and mean differences between two populations using sample data; 24. Construct the null and alternative hypotheses; 25. Understand and describe the Type I and Type II errors in the context of a hypothesis test; 26. Relate the steps in hypothesis testing to the scientific method; 27. Perform large-sample and small-sample hypothesis tests on population parameters, use p- values and the classical methods for making decisions, interpret the results and state the conclusion of a hypothesis test; 28. Perform chi-square goodness of fit tests for multinomial distributions;

3 29. Perform chi-square tests of independence and the chi-square test of homogeneity, through the use of contingency tables; 30. Make inferences concerning the theoretical slope of a linear regression line and determine the accuracy of regression predictions. Textbook: (Required) Probability and Statistics for Engineers by Miller, Freund, Johnson (8 th ed.) ISBN: Class Notes: Additional lecture notes will be posted later; Student Requirements During Lecture and Lab Sessions: 1. Students MUST turn off cell phones (all functions) prior to the start of class. Students will not use cell phones during lectures. 2. Students will not interfere with the learning processes of any other students. 3. Students will attend all lectures and lab sessions. 4. Students will arrive for lectures and lab sessions BEFORE the lectures and lab sessions begin. 5. Students will NOT DEPART EARLY from lectures and lab sessions. 6. Students may ask the instructors questions at any time. 7. Students will pay attention to the material being presented, explained and discussed. 8. Students will not converse with each other during lectures and lab sessions. 9. Students will participate in discussions during lectures and lab sessions. 10. Students will not surf the web during lectures and lab sessions. 11. Students will take and submit ALL lab quizzes. 12. Students will not work on homework. Performance Measures: Type Points Exam Exam Exam Lab Quizzes 100 Course Grade: The course grade will be based on a total of 400 points, using a 90%, 80%, 70%, 60% criteria for assigning the course grades A, B, C, D respectively. Any total less than 60% of 400 points will result in the course grade F. Grade Minimum Points A 360(90%) B 320 (80%) C 280 (70%) D 240 (60%) F < 240 (<60%)

4 Textbook Exercises: Textbook exercises are assigned by section on the class schedule. Textbook exercises may be collected and graded. Finish each set of exercises before the next class meeting. You must work the exercises in order to succeed in this course, since they provide practice problems to the students and are often representative of exam questions. Attendance Policy: Class attendance is required. Absences, tardiness, and leaving early from lecture adversely affect student performance. The student is responsible for all material missed as a result of an absence. For further guidelines please refer to Exams and quizzes: Each student must bring his/her WVU student identification card to exams and quizzes. Students are not permitted to use the textbook during quizzes and exams. Students are not permitted to use notes during quizzes. Calculators are required and cannot be shared. Students are not allowed to use cell phone during quizzes and exams, and students must remove baseball caps. Students must not leave the room during a quiz or exam without the instructor s permission. The date for each exam is indicated in the class schedule, but the final determination of material covered on each exam will be announced in class prior to the exam. The quizzes and exams are timed. Each student must present his/her WVU Student Identification card when exams and quizzes are submitted. Failure to present his/her WVU Student Identification card on the day of the exam/quiz will result in the grade 0 (zero) for the quiz/exam. Lab Exercises: During the semester, at least 15 exercises will be assigned but not graded. The lab instructors will work practice examples similar to the assigned exercises in G31/33 Eiesland Hall during your assigned lab period. You can work the exercises during the free periods at the lab or you can work them at any computer supporting Java. Graduate Teaching Assistants will teach the labs sections as outlined above and will also be available during free lab/office hours. You are expected to attend the lab sessions for the quizzes/examples and complete the exercises on your own. Lab Quizzes During the semester, at least 10 quizzes will be given and the best 10 will be used to compute the quiz grade. Each exercise will be graded using a 10 point scale, but will be worth a maximum of 5 points toward your course grade. You will find it helpful to bring a pencil and calculator when completing the quizzes. The quizzes are timed and are to be completed in G31/33 Eiesland Hall during your scheduled lab period. Make-Up Exams, Quizzes, and Exercises Makeups for quizzes/exam/exercises will be scheduled ONLY in the case of an emergency situation. I must be notified within two days of the date of the quiz/exam. The makeup quiz/exam must be completed within one week of the missed exam date. A reasonable excuse is required for a missed quiz/exam; otherwise the grade zero will be recorded for the quiz/exam. Your instructor will determine: 1) whether the excuse is reasonable, and, if so, 2) the manner in which the missed quiz/exam is made up. Academic Integrity: The integrity of the classes offered by any academic institution solidifies the foundation of its mission and cannot be sacrificed to expediency, ignorance, or blatant fraud. Therefore, I will

5 enforce rigorous standards of academic integrity in all aspects and assignments of this course. For the detailed policy of West Virginia University regarding the definitions of acts considered to fall under academic dishonesty and possible ensuing sanctions, please see the Student Conduct Code at Should you have any questions about possibly improper research citations or references, or any other activity that may be interpreted as an attempt at academic dishonesty, please see me before the assignment is due to discuss the matter. Social Justice: West Virginia University is committed to social justice. I concur with that commitment and expect to maintain a positive learning environment based upon open communication, mutual respect, and non-discrimination. Our University does not discriminate on the basis of race, sex, age, disability, veteran s status, religion, sexual orientation, color or national origin. Any suggestions as to how to further such a positive and open environment in this class will be appreciated and given serious consideration. Disability Services: If you are a person with a disability and anticipate needing any type of accommodation in order to participate in this class, please advise me and make appropriate arrangements with the Office of Disability Services ( ). Course Syllabus Modification: The instructor reserves the right to make modifications to the policies stated in the course syllabus. Students will be notified of any changes. (created )

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