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UW MadisonStat 310 Spring 2024 University of Wisconsin Madison STAT 310 Introduction to Probability and Mathematical Statistics I Instructor Nimal Wickremasinghe Office 1217A Medical Sciences Center MSC Ph 608 263 7329 Email wickremasing wisc edu Office Hours Wed 12 00 1 45 pm and by appt 1217A Teaching Assistant Hao Yan Email hyan84 wisc edu Office Hours 2 30 4 30 pm Mon 1217C Discussion Hours T 3 30 4 20p 1156 Mechanical Engineering Building T 4 35 5 25p 106 School of Social Work Building W 8 50 9 40a m 304 Educational Sciences Class Meeting Time and Location T R 9 30 10 45 a m Van Hise 594 Course Description Understanding of likelihood principle s central role to statistical inference using the language of mathematical statistics to analyze statistical procedures use of computer as a tool for understanding statistics Specifically samples and populations estimation hypothesis testing and theoretical properties of statistical inference such as unbiasedness efficiency minimum variance Learning Outcomes Upon completion of this course successful students will be able to comprehend and apply fundamental statistical inference methods of science and engineering Specifically students will Use statistical theory to understand and apply fundamental tools of statistical inference confidence intervals and hypothesis tests Understand and apply statistical inference procedures based on approximate normality of the target population s in the following statistical contexts inference based on a single random sample comparing two independent random samples comparing two paired random samples Understand and apply statistical inference procedures for nonparametric target population s in the following statistical contexts inferences based on a single random sample comparing two independent random samples comparing two paired random samples and large sample methods Requisites MATH STAT 309 STAT 311 MATH STAT 431 or MATH 531 1 UW MadisonStat 310 Spring 2024 Designations Breadth Natural Science Level Advanced L S credit type Counts as Liberal Arts and Science credit in L S Credit Information The course is 3 credits The class meets for two 75 minute in person lectures each week and carries the expectation that students will work on course learning activities readings homework studying etc for about 3 hours out of the classroom for every lecture period Instructional Mode All lectures are in person located in 594 Van Hise Office hours are available in person and by appointment Please see the Office Hours schedule posted to Canvas Regular and Substantive Student Instructor Interaction The regular and substantive student instructor interaction requirement is met through in person lectures providing feedback on student work and regular weekly office hours Course Schedule Calendar Week 1 Jan 23 25 1 1 1 2 introduction to samples and populations use of R for summarizing data Week 2 Jan 30 Feb 1 1 3 measures of location 1 4 measures of variability R based demos Week 3 Feb 6 8 5 3 statistics their distributions 5 4 distribution of the sample mean Week 4 Feb13 15 6 1 point estimation 6 2 methods of estimation method of moments Week 5 Feb 20 22 6 2 maximum likelihood estimation and properties 7 1 confidence intervals introduction Week 6 Feb 27 29 7 2 large sample intervals for a population mean and proportion 7 3 intervals based on normal distribution Week 7 Mar 5 7 7 3 prediction intervals and tolerance intervals 7 4 confidence intervals for the variance and the SD for normal distributions Week 8 Mar 12 14 Tue Midterm Review Thu Midterm Test see details under exams Week 9 Mar 19 21 Tue Going over the midterm solutions Thu 8 1 hypotheses and test procedures 8 2 z tests for population mean Week 10 Mar 25 29 SPRING RECESS Week 11 Apr 2 4 8 3 one sample t test and distribution free counterpart 8 4 tests for population proportion Week 12 Apr 9 11 8 5 further aspects of hypothesis testing 9 1 inference based on 2 samples 2 UW MadisonStat 310 Spring 2024 Week 13 Apr 16 18 9 2 two sample t test 9 3 paired t test Week 14 Apr 23 25 9 4 inference for the difference in population proportions Week 15 Apr 30 May2 Tu 9 5 inference for two population variances Th Final exam review Week 16 May 5 10 Final Exams Week details to be announced Attendance Very important Students are expected to attend all the lecture sessions Online Materials Canvas will be used to post all necessary materials including lecture notes slides handouts and homework assignments Canvas will also serve as a gradebook and discussion forum for asking questions It is recommended that you check Canvas regularly The course website is https canvas wisc edu courses 288952 Communication Both Canvas announcements and the university supplied email class list will be used to share all critical information It is imperative that your wisc edu email is active and working and that you check it regularly or have it forwarded to the account that you use most regularly We ask that questions for which the answer would be relevant to all students in the class be directed to the Piazza forum on Canvas not to instructor or TA email This way we can answer questions once instead of many times When you do contact the instructor or TA via email please use your wisc edu email account Textbook Probability and Statistics for Engineers and the Sciences by Jay L Devore 9th Edition 2016 Cengage Learning make sure you have the correct edition since question numbers may be different for different editions Computing Access to a calculator will be necessary to complete homework quizzes and exams It is recommended that you use a calculator which allows you to enter complex algebraic equations and includes a large display such as Texas Instruments TI 84 Plus The instructor may use R Studio for certain demonstrations R and R studio are free open source software It is not a requirement for students to write R codes in coursework or in exams But the instructor may give R outputs in exams and ask the students to interpret them Homework Homework will be assigned nearly every week With very few exceptions all homework problems will be assigned from the textbook The homework problems are intended to afford an opportunity for students to practice applying the specific course concepts learned in each week Details about homework guidelines expectations and submission procedures are below Homework will generally be assigned in Canvas on Tuesdays and will be due on the following Monday at 11 59pm Madison

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