MATH-040 Probability and Statistics Summer 2017

Similar documents
Office Hours: Mon & Fri 10:00-12:00. Course Description

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

Spring 2014 SYLLABUS Michigan State University STT 430: Probability and Statistics for Engineering

STA 225: Introductory Statistics (CT)

Class Meeting Time and Place: Section 3: MTWF10:00-10:50 TILT 221

SYLLABUS. EC 322 Intermediate Macroeconomics Fall 2012

FINN FINANCIAL MANAGEMENT Spring 2014

S T A T 251 C o u r s e S y l l a b u s I n t r o d u c t i o n t o p r o b a b i l i t y

Sociology 521: Social Statistics and Quantitative Methods I Spring Wed. 2 5, Kap 305 Computer Lab. Course Website

Syllabus Foundations of Finance Summer 2014 FINC-UB

Probability and Statistics Curriculum Pacing Guide

Course Content Concepts

Course Syllabus for Math

San José State University Department of Marketing and Decision Sciences BUS 90-06/ Business Statistics Spring 2017 January 26 to May 16, 2017

MATH 1A: Calculus I Sec 01 Winter 2017 Room E31 MTWThF 8:30-9:20AM

Accounting 312: Fundamentals of Managerial Accounting Syllabus Spring Brown

Ryerson University Sociology SOC 483: Advanced Research and Statistics

Foothill College Summer 2016

Instructor: Matthew Wickes Kilgore Office: ES 310

Nutrition 10 Contemporary Nutrition WINTER 2016

Math 181, Calculus I

EDCI 699 Statistics: Content, Process, Application COURSE SYLLABUS: SPRING 2016

Foothill College Fall 2014 Math My Way Math 230/235 MTWThF 10:00-11:50 (click on Math My Way tab) Math My Way Instructors:

Syllabus for CHEM 4660 Introduction to Computational Chemistry Spring 2010

MAT 122 Intermediate Algebra Syllabus Summer 2016

Sociology 521: Social Statistics and Quantitative Methods I Spring 2013 Mondays 2 5pm Kap 305 Computer Lab. Course Website

Syllabus ENGR 190 Introductory Calculus (QR)

AGN 331 Soil Science Lecture & Laboratory Face to Face Version, Spring, 2012 Syllabus

Physics 270: Experimental Physics

Algebra 1, Quarter 3, Unit 3.1. Line of Best Fit. Overview

Spring 2016 Stony Brook University Instructor: Dr. Paul Fodor

MATH 205: Mathematics for K 8 Teachers: Number and Operations Western Kentucky University Spring 2017

STA2023 Introduction to Statistics (Hybrid) Spring 2013

CIS 121 INTRODUCTION TO COMPUTER INFORMATION SYSTEMS - SYLLABUS

Military Science 101, Sections 001, 002, 003, 004 Fall 2014

PHY2048 Syllabus - Physics with Calculus 1 Fall 2014

Math 96: Intermediate Algebra in Context


EECS 700: Computer Modeling, Simulation, and Visualization Fall 2014

CRITICAL THINKING AND WRITING: ENG 200H-D01 - Spring 2017 TR 10:45-12:15 p.m., HH 205

Math 22. Fall 2016 TROUT

Spring 2015 Natural Science I: Quarks to Cosmos CORE-UA 209. SYLLABUS and COURSE INFORMATION.

CS/SE 3341 Spring 2012

Instructor: Mario D. Garrett, Ph.D. Phone: Office: Hepner Hall (HH) 100

EGRHS Course Fair. Science & Math AP & IB Courses

THE GEORGE WASHINGTON UNIVERSITY Department of Economics. ECON 1012: PRINCIPLES OF MACROECONOMICS Prof. Irene R. Foster

Penn State University - University Park MATH 140 Instructor Syllabus, Calculus with Analytic Geometry I Fall 2010

University of Victoria School of Exercise Science, Physical and Health Education EPHE 245 MOTOR LEARNING. Calendar Description Units: 1.

Spring 2015 IET4451 Systems Simulation Course Syllabus for Traditional, Hybrid, and Online Classes

BIODIVERSITY: CAUSES, CONSEQUENCES, AND CONSERVATION

Theory of Probability

ENME 605 Advanced Control Systems, Fall 2015 Department of Mechanical Engineering

POLITICAL SCIENCE 315 INTERNATIONAL RELATIONS

Please read this entire syllabus, keep it as reference and is subject to change by the instructor.

CIS Introduction to Digital Forensics 12:30pm--1:50pm, Tuesday/Thursday, SERC 206, Fall 2015

ITSC 1301 Introduction to Computers Course Syllabus

OFFICE SUPPORT SPECIALIST Technical Diploma

Page 1 of 8 REQUIRED MATERIALS:

Pre-AP Geometry Course Syllabus Page 1

POLSC& 203 International Relations Spring 2012

MGMT 3362 Human Resource Management Course Syllabus Spring 2016 (Interactive Video) Business Administration 222D (Edinburg Campus)

THE UNIVERSITY OF SYDNEY Semester 2, Information Sheet for MATH2068/2988 Number Theory and Cryptography

AGN 331 Soil Science. Lecture & Laboratory. Face to Face Version, Spring, Syllabus

BUS Computer Concepts and Applications for Business Fall 2012

Strategic Management (MBA 800-AE) Fall 2010

ANT 3520 (Online) Skeleton Keys: Introduction to Forensic Anthropology Spring 2015

SOUTHERN MAINE COMMUNITY COLLEGE South Portland, Maine 04106

FINANCE 3320 Financial Management Syllabus May-Term 2016 *

MTH 215: Introduction to Linear Algebra

Required Materials: The Elements of Design, Third Edition; Poppy Evans & Mark A. Thomas; ISBN GB+ flash/jump drive

Name: Giovanni Liberatore NYUHome Address: Office Hours: by appointment Villa Ulivi Office Extension: 312

Intensive English Program Southwest College

Biology 1 General Biology, Lecture Sections: 47231, and Fall 2017

GIS 5049: GIS for Non Majors Department of Environmental Science, Policy and Geography University of South Florida St. Petersburg Spring 2011

ASTRONOMY 2801A: Stars, Galaxies & Cosmology : Fall term

Green Belt Curriculum (This workshop can also be conducted on-site, subject to price change and number of participants)

COMMUNICATION AND JOURNALISM Introduction to Communication Spring 2010

Economics 201 Principles of Microeconomics Fall 2010 MWF 10:00 10:50am 160 Bryan Building

MGT/MGP/MGB 261: Investment Analysis

Introduction to World Philosophy Syllabus Fall 2013 PHIL 2010 CRN: 89658

Syllabus - ESET 369 Embedded Systems Software, Fall 2016

ECO 2013: PRINCIPLES OF MACROECONOMICS Spring 2017

CALCULUS III MATH

METHODS OF INSTRUCTION IN THE MATHEMATICS CURRICULUM FOR MIDDLE SCHOOL Math 410, Fall 2005 DuSable Hall 306 (Mathematics Education Laboratory)

University of Pittsburgh Department of Slavic Languages and Literatures. Russian 0015: Russian for Heritage Learners 2 MoWe 3:00PM - 4:15PM G13 CL

UNDERGRADUATE SEMINAR

KOMAR UNIVERSITY OF SCIENCE AND TECHNOLOGY (KUST)

Instructor Dr. Kimberly D. Schurmeier

Business Computer Applications CGS 1100 Course Syllabus. Course Title: Course / Prefix Number CGS Business Computer Applications

Firms and Markets Saturdays Summer I 2014

Business Analytics and Information Tech COURSE NUMBER: 33:136:494 COURSE TITLE: Data Mining and Business Intelligence

Texas A&M University - Central Texas PSYK PRINCIPLES OF RESEARCH FOR THE BEHAVIORAL SCIENCES. Professor: Elizabeth K.

Psychology 102- Understanding Human Behavior Fall 2011 MWF am 105 Chambliss

General Physics I Class Syllabus

Mathematics. Mathematics

Quantitative analysis with statistics (and ponies) (Some slides, pony-based examples from Blase Ur)

CMST 2060 Public Speaking

Demography and Population Geography with GISc GEH 320/GEP 620 (H81) / PHE 718 / EES80500 Syllabus

Grading Policy/Evaluation: The grades will be counted in the following way: Quizzes 30% Tests 40% Final Exam: 30%

Introduction to Forensic Anthropology ASM 275, Section 1737, Glendale Community College, Fall 2008

Transcription:

MATH-040 Probability and Statistics Summer 2017 Instructor: Oded Meyer Office: STM 309 email: ogm@georgetown.edu Office hours: TBD SYLLABUS AND COURSE POLICIES Course Web Page: http://campus.georgetown.edu Lectures: Monday Thursday 10:45 AM 1:25 PM Reiss 282 Class time will consist of a combination of lecture, discussion, question and answer, problem solving and computer work using the statistical software Minitab. Attendance will contribute 10% to your overall course score Required Electronic Text The Probability and Statistics course from acrobatiq.com. Linked from the course Blackboard page. Good Reference (but definitely not required): Statistics: The Art and Science of Learning from Data, 2nd or 3rd edition, Agresti and Franklin. Prerequisite: Basic Algebra. 1

OVERVIEW Does eating fat cause cancer? Does vitamin C prevent colds? Can you predict someone s University grades from their SAT scores? Are the smoking habits of parents and their children related? Statistics can help us answer all these questions. Broadly speaking, Statistics is a set of methods that help us collect, organize and interpret data. We use these tools to uncover relationships between variables, to make predictions and to discover causal mechanisms. The way introductory statistics courses are taught has changed tremendously in the last 10 years. Instead of tedious arithmetic calculations, we will emphasize: graphical analysis of data, simple but powerful concepts that do not require difficult mathematical manipulations, and interpretation of computer output. The four main topics that we will learn in this class are: Exploratory Data Analysis: A data set consists of a collection of measurements. How can we organize them and describe them? How can we gain insight by exploring the data visually. Experimental Design: A newspaper article reports that according to a recent study, people who eat lots of oat bran have fewer heart attacks. How was this study designed? Was it designed in a way that we can conclude from it that eating oat bran actually prevents heart attacks? In general, when can we be sure that when the results of a study show that two phenomena are associated, that one actually causes the other? Statistical Inference: It is rarely feasible to measure everyone in the population. At best, we can draw random sample from the population. How can we make inferences about the population based on the sample? polls do this everyday. How do they do it? Probability: Probability is a mathematical description of randomness, and provides us with the formalisms that allow us to draw inferences from samples to populations. In addition, the study of probability theory provides new perspectives, methodologies, models and intuitions to aid in the analysis and solution of real world problems. COURSE OBJECTIVES A student who has successfully completed the course should be able to: 1. Articulate an appreciation for the diverse application of statistics and its relevance to his/her life and field of study. 2. Demonstrate conceptual understanding of fundamental statistical ideas such as variability, distribution, association, causation, sampling, experimentation, confidence, and significance. 3. Show introductory level practical ability to choose, generate and properly interpret appropriate descriptive and inferential methods. 4. Appropriately choose and correctly apply some elementary probability models. 5. Exhibit critical thinking about statistics (e.g., to demonstrate the ability to assess the validity of statistical arguments in the popular press and scholarly publications; to show the ability to assess the relative fit of statistical models to real-world studies). 6. Demonstrate the ability to effectively communicate statistical ideas (and thus be able to knowledgeably participate in modern social debates). 7. Demonstrate introductory level experience with using statistical software to perform data analysis. 2

CLASS HANDOUTS For every lecture there will be a handout that we will work through. Copies of the handouts will be posted on the course BB page. The completed handouts (handouts + class notes) will not be available. HOMEWORK Homework will be posted on the course Blackboard page every Tuesday and Thursday and will be due the following Thursday and Tuesday, respectively. The purpose of these assignments is to help you learn the material. Assignments are due at the beginning of class. Assignments turned in after 11:00 and before 1:25pm will be panelized 25 points. No assignment will be accepted after 1:25 PM. There will be absolutely no exceptions to this policy. You are allowed and even encouraged to discuss the assignments with each other,but the work that you hand in must be your own. This means that each student must perform all analyses on his/her own computer, and must independently write the analysis and interpretation. In order to avoid misunderstanding, you should let us know when you work with a classmate on a HW assignment. Simply write Worked with (name) under your name. You should always show all of your work. You will not receive credit for simply writing down a numerical answer, even if the calculations seem simple enough to do in your head. Showing the method of solution is as important as the correct answer. Your worst homework grade will be dropped before computing your final grade this is meant to cover cases in which you are too ill, too busy, or too tired to complete the homework. Solutions will be available posted on the course BB page. Read them as they provide you with examples of what a complete answer should look like. Final Comments about HW: 1. Warning: If you wait until the last minute to finish the assignment, you accept the risk that the computer or printer will fail or be unavailable. 2. No homework can be accepted in electronic form. EXAMS There will be two mid-term exam and a cumulative final exam. The exam dates are as follows: Exam1: Wednesday, June 14, 2017 (tentative). Exam2: Tuesday, June 27, 2017 (tentative). Final: Thursday, July 6, 2017. 3

Examinations will be closed-book and closed notes; however you may use one 8 1/2 by 11 sheet of paper (one-sided for the midterms and two-sided for the final exam) with whatever formulas, facts or explanations you find helpful. You will be required to bring your own calculator. No make-up examinations will be given. A student who misses an examination because of a medical reason must provide documented evidence of serious medical incapacitation to Oded Meyer. Other reasons for missing an examination must be discussed with Oded BEFORE the day of the examination. Each case will be considered on an individual basis. The overall course grade for a student who misses an examination with a valid reason will be based on that student s remaining course work. A student who misses an examination without a valid excuse will receive a zero grade for that examination. REGRADES Although I strive for consistency and accuracy in grading, mistakes can occur. I will gladly correct all errors in tabulation or overlooked material. All regrading requests (of HW and exams) must be accompanied by a written statement carefully highlighting and explaining the items you feel were misgraded. Regrades requests must be submitted within 2 lectures of when the assignment of exam is returned. No regrades will be considered after this time. COURSE GRADE Homework average (after dropping lowest score) 15% Attendance (one absence is allowed) 10% 2 midterm exams 20% each Final Exam 35% Once your course final score is calculated, letter grades will be assigned as follows: A: 95 100 A : 90 95 B+ : 87 90 B : 83 87 B : 80 83 C+ : 77 80 C: 73 77 C- : 70 73 D+ : 67 70 D: 60 67 F: below 60. ACADEMIC INTEGRITY Georgetown students are expected to follow the ethical guidelines and cheating and plagiarism policies (see http://honorcouncil.georgetown.edu/system) Cheating and/or plagiarism will not be tolerated. HOW CAN YOU GET MINITAB 17? Minitab has only a PC version which can be downloaded from the UIS Software Webstore : http://georgetown.onthehub.com/webstore/welcome.aspx Once you login, choose the Math & Stat tab and then Minitab 17. If you are a Mac user (and cannot run windows using VMware Fusion or Parallels Desktop), you ll be able to use Minitab using UIS s virtual lab. Detailed instructions on how to do so are posted on the course Blackboard page (Course Documents section). Otherwise, several UIS controlled computer labs across campus have Minitab installed on the computers. 4

TENTATIVE COURSE SCHEDULE Dates June 5-12 June 14 (Wednesday) June 13-22 June 27 (Tuesday) June 26 July 5 No lecture Tuesday July 4 July 6 (Thursday) Topics Understanding the Big Picture Examining Distributions (Graphs and numerical measures) Examining Relationships Analysis of two-way tables Scatterplots, linear relationships, correlation and least squares regression Association vs. Causation Gathering Good Data (sampling) Design of Experiments First Midterm (TENTATIVE) Basic Probability Principles Conditional Probability, Independence, Bayes Rule, and Probability Trees Discrete Random Variables Binomial Random Variable Continuous Random Variables The Normal Distribution Sampling Distributions and the Central Limit Theorem Second Midterm (TENTATIVE) Point Estimation and Confidence Intervals The Logic of Hypothesis Testing Hypotheses Testing the Population Proportion Hypothesis for the Population Mean (Introducing the t distribution) Comparing Two Means (independent samples) Matched Pairs One-Way ANOVA + Multiple comparisons Inference for Two-Way Tables (Chi-Square Test for Independence) Inference for Regression Final Exam 5