Lecture Time: Monday & Wednesday: 3.00PM 4.15PM. Class Room: Office Hours: Tuesday s & Thursday s 10.30AM to 12.00Noon, or by appointment.

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1 ST Experimental Statistics for Engineers II Course syllabus Fall credits Instructor: Name: Dr. Paul Savariappan Office: SAS 5232 Phone: Lecture Time: Monday & Wednesday: 3.00PM 4.15PM Class Room: 214 Cox Hall Office Hours: Tuesday s & Thursday s 10.30AM to 12.00Noon, or by appointment. Teaching Assistants: Name: Haoyu Chen Office: hchen36@ncsu.edu Office hours: Monday s and Wednesday s 5PM 6PM Prerequisites: The prerequisite is ST 515 Textbook: Probability and Statistics for Engineering and the Sciences by Jay L. Devore, 9th Edition, ISBN , Cengage Learning. Course Description: ST 516 is a second course in statistical inference and is further examination of statistics and data analysis to supplement the probability covered in ST 515. Course content includes inference for comparing multiple samples, experimental design, analysis of variance and post-hoc tests. Also included are inference for simple regression, multiple regression, and curvilinear regression. Multiple regression-related topics such as multicollinearity, variable selection, and comparison of subsets of multiple regression models are included. Modern statistics is computer intensive and involves a great deal of graphing and calculating. You will use computer software to automate most calculations and the creation of data-descriptive graphics. This will enable us to analyze sizeable, interesting, and realistic data sets and move quickly to an understanding of the big ideas and the beginning of good judgment in working with data that emphasizes understanding, analysis and interpretation. 1

2 Learning Outcomes Calculate the least squares line for fitting a straight line to bivariate data and clearly explain the meaning of the slope in the context of the data. Perform hypothesis tests for the slope of a simple linear model; construct prediction and confidence intervals for the response variable. Given a study explain what is meant by the true regression line and describe the sampling distribution of the sample slope. State the assumptions of inference about the regression model. Explain the practical reason for testing that the slope is zero. Given a study objective, significance level (α ) and summary statistics, conduct a formal test of significance on a slope based on the t-distribution by conducting the appropriate steps. (This includes choosing and stating hypotheses, calculating a test statistic, calculating and interpreting the p-value and interpreting the conclusion of the test in context.) Given standard regression output, interpret the results of the test of hypothesis about the slope. Perform statistics inference for multiple regression models. Given a study, determine whether it is an observational study or an experiment. Given a study, identify subjects and treatments. Given a study, determine whether a completely randomized design was used. Given a study objective, describe how to implement a completely randomized design. Given a study, explain why randomization should be used. Given a study, determine whether a blocking design was used and describe the blocks. Given a study objective, explain the advantage of using a blocking design. Given a study objective, describe an appropriate comparative experiment appropriately using the principles of randomization, replication, control, blocking, double-blinding, placebo, and control group. Perform chi-square goodness-of-fit tests, tests of homogeneity, and tests of independence for count data; state assumptions that must be satisfied for tests to be valid. Explain test results in the context of the data. Note Outlines: Moodle will be used to post all necessary course materials, including handouts and homework assignments. Students are expected to print a course material and it will be available at least 24 hours prior to each lecture. Moodle will also serve as a gradebook and discussion forum for asking questions. Students are expected to check Moodle or their NCSU regularly to receive course announcements. Computing: We will be using R for most analyses. R is a free, open-source, and extremely flexible package, and is available for download online at: No prior experience will be expected. Discussion during the first week of class will be a tutorial on how to download and install R, as well as some simple commands. 2

3 Homework: HW problems will be assigned on weekly basis. There will be 7-9 homework assignments throughout the semester. Generally, assignments will be posted to Moodle. No unexcused late work will be accepted for credit. You must do your own work. Students missing a HW and quiz will be assigned a score of zero for that HW and quiz. Exams: There will be 2 midterm exams and a cumulative final exam. All exams are closed book. For each midterm exam, students may use one 8 ½ X 11 inch page of notes (front and back, any content). For the final exam, students may use three 8 ½ X 11 inch pages of notes (front and back, any content). Basic calculators (such as TI-83) may be used on all exams. Requests for exam re-grades must be made in writing and within two weeks of the date on which the exam is returned in class. Making-up exams: Students who are unable to attend an exam for a legitimate unavoidable reason may take a make-up exam only if the student provides suitable documentation (such as a note from a physician) of the absence. Students who have a personal emergency (extreme family illness or death, etc) should contact the Absence Verification Officer (absence-verification@ncsu.edu) to obtain documentation; see dasa.ncsu.edu/students/absence-verification-process/ for more information. According to university policy, a student must notify the instructor in advance if s/he will miss an exam. If it is not possible to notify the instructor in advance, the instructor must be given notice as soon as possible after the exam. Grading: There are no extra-credits or negotiations based on individual circumstances. Your final grade will be determined by the following criteria. Midterm 1: 25% (Oct 03) Midterm 2: 25% (Nov 14) Final: 25% (Dec 17) Homework: 25% s will be determined by calculating the student's total out of the available points and comparing with the standard NCSU letter grading scale: Numeric Numeric Numeric A+ 97 B [83, 87) C- [70, 73) A [93, 97) B- [80, 83) D+ [67, 70) A- [90, 93) C+ [77, 80) D [63, 67) B+ [87, 90) C [73, 77) D- [60, 63) F < 60 3

4 Incomplete (IN) grades are given only as specified in university regulations. Students who wish to audit the course with satisfactory status must register officially for the course and will be required to complete all online quizzes. Students with disabilities: Reasonable accommodations will be made for students with verifiable disabilities. In order to take advantage of available accommodations, students must register with the Disability Services Office at Suite 2221, Student Health Center, Campus Box 7509, For more information on NC State s policy on working with students with disabilities, please see: Academic Accommodations for Students with Disabilities Regulation (REG ). Academic Misconduct: Cheating, plagiarism and other forms of academic dishonesty will not be tolerated. To create a fair and equitable environment, the instructor aggressively enforces the universities policies on academic misconduct. All exams are to be completed individually. Although working together on written assignments to overcome obstacles is encouraged, each student must submit their own work. All cases of academic misconduct will be handled as set out in university policies. For additional information see: Code of Student Conduct policy (NCSU POL ). Additional regulations: Students are responsible for reviewing the NC State University PRR s which pertains to their course rights and responsibilities, including o Equal Opportunity and Non-Discrimination Policy Statement with additional references at o Code of Student Conduct o s and Point Average o Credit-Only Courses o Audits Important Dates: o September 03: No class or office hours for Labor Day o October 03: Midterm Exam 1, during regular class time o October : No class or office hours for Fall Break o October 19: Drop/Revision Deadline (Last day to switch to credit only or drop without a W grade) o November 14: Midterm Exam 2, during regular class time o December 17, 1-4pm: Cumulative Final Exam 4

5 Tentative Syllabus (with approximate book sections): The distribution of Sample Mean: 5.4 Statistical Intervals (Single Sample): ; Properties of Confidence intervals, Large sample Confidence Intervals for the Population Mean and Proportions, Intervals based on a Normal Population Distribution. Tests of Hypothesis (Single Sample): ; Hypothesis and Test procedures, Tests about a Population Mean and Proportions, P- Values. Inferences based on Two samples: ; Z Tests and Confidence Intervals for a difference between two Population means and proportions, Two Sample t-test and Confidence Intervals, Analysis of paired data Analysis of variance: , ; Single factor ANOVA, Multiple Comparisons in ANOVA, Two Factor ANOVA, Three factor ANOVA, Factorial experiments Linear Regression and Correlation: Nonlinear and Multiple Regression: HOW TO SUCCEED IN A MATH CLASS: Come to every class meeting. Arrive early, get yourself settled, spend a few minutes looking at your notes from the previous class meeting, and have your materials ready when class starts. Read each section before it is discussed in class. Do some math every day. Start preparing for the tests at least a week in advance. Spend about half of your study time working with your classmates. Take advantage of tutors and office hours, extra help can make a big difference. 5

State University of New York at Buffalo INTRODUCTION TO STATISTICS PSC 408 Fall 2015 M,W,F 1-1:50 NSC 210

1 State University of New York at Buffalo INTRODUCTION TO STATISTICS PSC 408 Fall 2015 M,W,F 1-1:50 NSC 210 Dr. Michelle Benson mbenson2@buffalo.edu Office: 513 Park Hall Office Hours: Mon & Fri 10:30-12:30