Brown, Richard D.

English

University of Montana

University of MontanaScholarWorks at University of MontanaSyllabi Course SyllabiSpring 2-1-2018STAT 216.14: Introduction to StatisticsRichard D. BrownUniversity of Montana, MissoulaLet us know how access to this document benefits you.Follow this and additional works at: https://scholarworks.umt.edu/syllabiThis Syllabus is brought to you for free and open access by the Course Syllabi at ScholarWorks at University of Montana. It has been accepted forinclusion in Syllabi by an authorized administrator of ScholarWorks at University of Montana. For more information, please contactscholarworks@mso.umt.edu.Recommended CitationBrown, Richard D., "STAT 216.14: Introduction to Statistics" (2018). Syllabi. 7769.https://scholarworks.umt.edu/syllabi/7769                                                                                                                                                                                                                                                                                                    STAT 216 - Introduction to Statistics – Syllabus Spring 2018Course Coordinator• Cindy Leary (cindy.leary@mso.umt.edu)Office: Math 214STAT 216 on Moodle: All information for this course will be posted on Moodle. Hereyou will find all handouts given in class and all notes covered during lecture. Thisincludes all lab worksheets, “hand-in” homework assignments, and the solutions to allassignments. The lecture notes have significant amounts of material intentionallyomitted so that we may cover this material during class. If you miss a class, checkMoodle for any announcements made that day, and copy the notes from a classmate. Iwill not provide you with copies of notes you missed. A course pack containing theblank notes is available in the bookstore.Course Format: 3 lectures/week: MWF 9:00-9:50 or 10:00-10:50am, NorthUnderground Lecture Hall (NULH 101). 1 discussion/lab section per week: Thursday atthe times listed below. Attendance at discussion sections is mandatory.Prerequisites: M 115 (Probability and Linear Mathematics, previously labeled MATH117), or 3 or more credit math course numbered 121 or above.Stat 216 Discussion Sections:9:00am LectureSection Time Room Instructor1 9:00 MA 312 Jared Halvorson2 10:00 MA 312 Jared Halvorson3 11:00 MA 312 Benjamin Stark4 12:00 MA 312 Benjamin Stark5 1:00 MA 312 Daniel Barthelmeh10:00am Lecture Section Time Room Instructor11 8:00 MA 103 Ted Owen12 9:00 MA 103 Ted Owen13 10:00 MA 103 Daniel Barthelmeh14 11:00 MA 103 Rick Brown18 11:00 LA 235 Quy Cao15 12:00 MA 103 Rick Brown16 1:00 MA 103 Dominika Dec17 2:00 MA 103 Dominika Dec1                                                                                                                                                                                                                                                                                                                                                                                                                               Stat 216 Instructors: You may go to ANY of these instructors for help during theiroffice hours, which will be posted on Moodle.Name Office EmailCindy Leary Math 214 cindy.leary@mso.umt.eduRick Brown Corbin 355 rick.brown@umontana.eduDaniel Barthelmeh Corbin 359 daniel.barthelmeh@umontana.eduQuy Cao Corbin 367 quy.cao@umontana.eduDominika Dec Corbin 357 dominika.dec@umontana.eduJared Halvorson LA 409 jarod.halvorson@umontana.eduTed Owen Corbin 367 theodore.owen@umontana.eduBenjamin Stark Corbin 358 benjamin.stark@umontana.eduLearning Outcomes: Upon successful completion of STAT 216, a student will:1.	 be able to describe and explore sets of data both numerically and graphically.2.	 know how to use the normal model for the distribution of a single variable and thelinear regression model for the relationship between two variables.3.	 know the basic principles of good experimental design and good sampling design. 4.	 know the fundamental ideas of statistical inference for means and proportionsincluding both hypothesis testing and confidence intervals.5.	 be able to interpret confidence intervals and P-values in the context of real problems. 6.	 be a critical consumer of statistical studies reported in the media.Computing Information: StatCrunch statistical software will be used by theinstructors during class and will also be required for some homework problemsthroughout the course. This software can be accessed within MyStatLab.Learning Catalytics: is a cloud-based learning and assessment system that we willuse during the lecture portion of this course. It is available through a link in Moodle, butin order to access it, you will need to have a device that can connect to the wirelessinternet in the lecture hall. A device such as a smartphone, tablet, or laptop would workwell. This technology allows me to assess your understanding of the material, make thecourse more engaging, and collect data for our class to analyze. Your responses willalso constitute a portion of your grade (5%). Your Learning Catalytics grade will beprimarily be based attendance. While these responses are worth 5% of your grade, youalso have the option of using your overall exam average as your Learning Catalyticsgrade.Note: If you are ever unable to connect to the Learning Catalytics page during class,you may email me your responses during class. Emails received after the end of classwill not be included in your Learning Catalytics grade. Note also that we drop your fivelowest Learning Catalytics grades.2                                                                                                                                                                                                                                                                                                                                                                                                                                                                    Textbook: Intro Stats (4th ed. Custom), by DeVeaux, Velleman, & Bock. Youautomatically have access to the online textbook and resources through Moodle (unlessyou choose to ``opt out" of the tuition billing system). If you would additionally like topurchase a printed copy of the book (for $20), please go to:http://www.mypearsonstore.com/stores/STAT216\\ You will also need the username:pearson and password: welcomeCalculators: Since Math 115 is a pre-requisite for this course, it is expected that youalready own a calculator suitable for this class and that you also know how to use it.Your calculator should, among other things, be able to calculate probabilities from theBinomial, Normal, and t-distributions. If you are thinking about purchasing a calculatorfor this course, students tend to be the most comfortable with the TI-83 or TI-83 Plus. Alist of other calculators is provided on the Moodle course page. Please note thatcalculators with a QWERTY keyboard, smart watches, and cell phones are not allowedfor use during exams.Incomplete (I) Grades: Incompletes (I's) are given at the discretion of the coursecoordinator (Cindy Leary) only. See the 2017-2018 UM catalog for the conditions underwhich an "I" may be given.Credit/No-Credit Grades: A D- grade is required to receive credit under the Credit/No-Credit option. You will be allowed to change your grading option from Credit/No Creditto Traditional or vice versa up until May 4th. Note: A course taken to meet a generaleducation requirement (such as Stat 216) CANNOT be taken as Credit/No Credit. Seethe 2017-2018 UM course catalog for more information.Grading: Your overall percentage for the course will be computed using the weightsbelow. We will also drop some of your lowest scores as indicated in the table. The +/­grading system will be used to assign final grades. There is no strict grading scale forthis course; however, the table below indicates the worst-case scenario for the lettergrade breakdown. For example, if you earn an 80% in the course, you are guaranteedno worse than a B-, and it could be higher. No extra credit will be available.Grade Category Weight # DroppedMyStatLab Homework 10% 2Hand-in Homework 8% 1Learning Catalytics (or Exam Avg) 5% 5 DaysWorksheet/Lab Grade 8% 1Exam #1 23% 0Exam #2 23% 0Exam #3/Final Exam 23% 0Grade A- to A+ B- to B+ C- to C+ D- to D+ F CR (Credit)% 90-100 80-89 68-79 57-67Less than57%57-1003                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         “Hand-in” Homework: Weekly assignments will be posted on Moodle as a Worddocument. It is expected that you type the answers into this document or neatly write inyour work when appropriate. This course largely focuses on teaching you how tointerpret and analyze data. We expect you to use correct grammar and spelling whileproviding clear and concise explanations. These assignments will be handed in at thebeginning of your lab on Thursdays. NO LATE HOMEWORK WILL BE ACCEPTEDFOR ANY REASON. We will not regularly accept homework assignments via e-mail,but you may e-mail an assignment if you are sick and cannot make it to campus, withthe approval of Cindy Leary. Homework is not only a fairly substantial portion of yourgrade, but it is vital to your success in this class. Working with other students onhomework is allowed and encouraged, as long as you hand in your own work, and donot simply copy someone else's work. Solutions to all problems from each assignmentwill be posted on Moodle.OnlineHomework: You will access your online homework problems and other textbookresources through Moodle (MyStatLab). To initially gain access to this system, use theinformational document posted at the top of our Moodle page. Once you go throughthis initial login procedure, you will automatically have access to MyStatLab resourcesfor the rest of the semester. Any online assignments completed after the due date willonly receive 50% of the total points earned.Recommended Problems: Additional recommended problems will be assigned butnot collected from each chapter, with answers provided in the back of the textbook. Youare encouraged to work all of these problems.Labs/Worksheets: During the discussion sections, you will have the opportunity to askquestions about course material and work on problems with other students in smallgroups. You will complete a worksheet most weeks during the discussion section. Theintent of the worksheets is to have you practice using statistical methods and to promotecooperative learning. Completing the worksheets in groups will allow you to discussideas and problems with other students. Your worksheet grade will reflect both your ownwork and the work of your group. *** Make-up worksheets will usually not be given,but notify Cindy if you are unable to attend your lab due to a UM-sponsoredactivity.Tests:There will be 2 evening tests during the semester given in NULH and Urey lecturehalls.• Test #1, Thursday, March 1st, 6:00-7:30pm• Test #2, Thursday, April 5th, 6:00-7:30pmYou must take the test in your assigned location and time. More will be said about theexams at a later date. If you cannot make it to an exam, you must let me know BEFOREthe exam is given. No make-up exams will be given without a documentable reason formissing the exam.4                                                                                                                                                                                                                                                                                                                                                                                                                                            Final exam: The final exam will emphasize later material but will also cover some ofthe key elements from earlier chapters. The final exam will take place on Tuesday,May 8th for the 9am lecture and Wednesday, May 9th for the 10am lecture. Bothexams will be given from 10:10am to 12:10pm. Makeup exams will not be given due totravel plans.Study Advice: COME TO CLASS! STUDY THE NOTES! BE AN ACTIVE LEARNER!Read through the notes to be covered before coming to class and review them afterclass. Either print the notes from Moodle or purchase a course pack from the bookstore.This will reduce the volume of notes you will need to take in class and you will get moreout of the lecture. Read the textbook to solidify your understanding of the topicsintroduced during lecture. Doing your homework as well as the additional recommendedproblems conscientiously will greatly increase your chance of success in this class.There will be STUDY JAM sessions held most Monday and Wednesday evenings in theU.C. commons (6:30pm-9:00pm). **Plan to spend 2 hours outside of class for eachhour of class – Seriously!**Adding/Dropping the Course: January 30th is the deadline for students to drop orchange a grading option via CyberBear. February 9th is the deadline for students todrop/add a course or change the grading option using a course add/course changeform. After this date, a student is allowed to make changes by petition. The finaldeadline for any and all changes is May 4th. These policies are listed in the UM catalogat http://www.umt.edu/catalog.Students with disabilities: Students with disabilities may request reasonablemodifications by contacting Cindy Leary. The University of Montana assures equalaccess to instruction through collaboration between students with disabilities,instructors, and Disability Services for Students (DSS). ``Reasonable" means theUniversity permits no fundamental alterations of academic standards or retroactivemodifications. For more information, please consult http:www.umt.edu/disability.Academic Misconduct: All students must practice academic honesty. Academicmisconduct is subject to an academic penalty by the course instructor and/ordisciplinary sanction by the University. This includes, but is not limited to, copyinganswers on homework assignments, cheating on exams, and any type of dishonesty inyour work. All students need to be familiar with the Student Conduct Code. The Codeis available for review online at http://www.umt.edu/vpsa/policies/student_conduct.php5                                                                                                                                                                                                                                                                                                                                                                               Tentative (Optimistic) Schedule Date Day Chapter Topics Covered (Tentative!!)1/221/241/26MondayWednesdayFriday122Course Introduction, DataCategorical Data, StatCrunch demoCategorical Data Displays & Distributions1/291/312/2MondayWednesdayFriday333Displaying & Describing Quantitative VariablesDisplaying & Describing Quantitative VariablesMean and Standard Deviation2/52/72/9MondayWednesdayFriday455Comparing Distributions, Boxplotsz-scoresNormal Model and the Empirical Rule2/122/142/16MondayWednesdayFriday5,666,7More on Normal Models, ScatterplotsScatterplots, CorrelationCorrelation vs Causation, Linear Regression2/192/212/23MondayWednesdayFriday77,8President’s Day – No classLinear RegressionLinear Regression, Residual Analysis, & R22/262/283/1MondayWednesdayThursday88Regression Wisdom, Outliers, Influential PointsTransformations in RegressionEXAM 1 from 6:00pm to 7:30pm3/53/73/9MondayWednesdayFriday91010Randomness, SimulationSample Surveys, Simple Random SamplesMore Sampling Designs3/123/143/16MondayWednesdayFriday111112Observational Studies, Experimental DesignMore on Experimental DesignRandomness & Probability, Law of Large Numbers3/193/213/23MondayWednesdayFriday15(Skip13,14)1515,16Sampling Distribution of p̂ Central Limit Theorem (CLT) for p̂ CLT, Confidence interval for p3/26 to 3/30 SPRING BREAK4/24/44/5MondayWednesdayThursday1616Confidence Intervals for pConfidence intervals for pEXAM 2 from 6:00pm to 7:30pm4/94/114/13MondayWednesdayFriday171717Hypothesis Testing for p, P-valuesHypothesis Testing for p, P-valuesHypothesis Testing examples4/164/184/20MondayWednesdayFriday1515,1818CLT for meansInferences about means, t-proceduresInferences about means, t-procedures4/234/254/27MondayWednesdayFriday181920Inferences about means, t-proceduresMore about tests, P-values, Type I & Type II errorsComparing two proportions4/305/25/4MondayWednesdayFriday202020Comparing two proportionsComparing two meansPutting all Inference Procedures Together5/85/9TuesdayWednesdayFINAL EXAM FOR 9am LECTURE (10:10am)FINAL EXAM FOR 10am LECTURE (10:10am)6 

STAT 216.14: Introduction to Statistics

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STAT 216.14: Introduction to Statistics

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