ࡱ>  bjbj "tjjl  %%%8%<6&  sN'N'(v'v'v'(>(( o"o"o"oTvoxqzs$u  xs (((((s;,v'v's;,;,;,(pv' v' o;,( o;, ;, 7QcW 4jv'B' ЮT _ %W)`gn4js0shx*x4j;,  Quantitative Methods 201 U (4), Spring 2005 MW 5.30 to 7:20 PM in BLM 209 http://faculty.washington.edu/htamura/qmeth201U OBJECTIVES: This course introduces basic statistical methods with applications for management. Management of business involves working with target populations. An example of a target population is a companys customers. Another example is all outputs from an internal process, say, a workstation. Yet another example is the economic system or the market within which the company operates. A population is a collection of units that vary from one unit to the next, and is therefore difficult to understand. To make them intelligible, a manager must collect data on the target population and interpret them. Also, a manager needs to measure the degree of uncertainty about what result one achieves when acting on the population. Statistical methods are tools for these purposes. Statistical tools you will learn in this course: TS1. descriptive statistics for classifying, summarizing, and displaying data. TS2. probability for measuring the uncertainty. TS3. inference for a few key characteristics of the population. TS4. models for the relationship between two variables. TS5. using Excel for implementing these skills INFORMATION AND REQUIREMENTS: The course web site up-dates the course syllabus (downloadable MS Word file) and additional materials. Course Instructor: Professor Hiro Tamura Office: Mackenzie 362 Tel & Fax: Tel 206-543-4399; Fax 206-543-3968 E-mail address: htamura@ Office hours: MW 4:00 - 5:20 PM Teaching Associate: Elisa Kao eskao@ Message phone number: (206) 543 1043; ask for Shawna Required Course Materials: Text: Siegel, A. F. (2003) Practical Business Statistics, Fifth Edition, available at the University Bookstore. Calculator: Academic Accommodations due to a Disability: Please contact Disabled Student Services (uwdss@u.washington.edu), 448 Schmitz, 206-543-8924 (voice/TTY), and request a letter indicating that you have a disability which requires academic accommodations, and present it to the course instructor. Grading: There are six components to the course grade: Homework 12% (turn in at the beginning of due class sessions) Quiz: 8% (10 minutes, see the schedule) Project - 1 10% (W, April 25) Midterm 20% (W, April 27) Project - 2 15% (W, June 1) Final 35% (W, June 1 or M, June 6: 6:30-8:20 PM) Homework: No late homework will be accepted. You must show some work for each problem for credit. The lowest homework score will be dropped for course grading. Quizzes: Closed book, except table pages, and closed-notes. Bring your calculator! The project: Up to 3 students in a project group. See the next page for description. IMPORTANT: It is the responsibility of the team to divide up the work equally and to ensure that all team members are making progress. Each team member is requested to fill out the evaluation form. . Midterm and Final Exams will be closed-book, except table pages, but you may bring 1 sheet of notes for the midterm and 2 sheets for the final. Bring your calculator. The final exam will cover the entire course, but the materials since the midterm will be emphasized. Course grades are based on a curve for all sections combined. (applies for QMETH201 A only) Sequel electives in statistical methods QMETH 490 A (4, Winter, 05): Managerial Applications of Regression Analysis QMETH 490 A (4, Spring 05): Analysis and Forecasting of Financial Data DatePart I Topics (subject to minor changes)ReadingsWeek 1 3/28MOrientation Statistics for Management TS1: Data structure and variable type (study unit; variable types: quantitative, qualitative, nominal, ordinal) Case: Survey of exercise level  Ch. 1, Ch. 18.1&2 Ch. 2, 3/30WTS1: Descriptive Statistics-1 (histogram, relative frequency, mode, mean, median, minimum, maximum, quartiles) Case: Does the promotion work? Ch. 3, Ch. 4 Ch. 5: 5.1,5.2, 5.4 Week 2  4/4MTS1: Descriptive Statistics-2 (variance, standard deviation) TS1: Normal distribution (normal curve, standard normal table, z-score) Case: Investment risk analysis HW#1 Due: Ch 7: 7.34/6 WTS2: Probability (random experiment, outcome, sample space, event, sources of probability) Quiz 1: Ch. 6: 6.1-6.4Week 3411 MTS2: Probability (rules for computing probability) (complimentary event, intersection, union, independent, mutually exclusive, conditional probability; Venn diagram) Case: System reliability HW# 2 Due: Ch. 6: 6.54/13 WTS2: Probability (applications of conditional probability) (multiplication rule; 2 x 2 table, probability trees) Case: Survey of exercise level Case: Appliance purchase Case: Marketing new recipes Case: Lets Make a Deal Case: Sensitive interview  Week 44/18 MTS2: Random Variable (probability distribution, expected value, standard deviation) Case: Las Vegas roulette HW# 3 Due: Ch 7: p.236-2474/20WRandom Variable (contd) (binomial distribution - definition, normal approximation) Case: Misjudging the true popularity Case: Does organic milk taste better? Quiz 2:Ch.7: 7.4Week 54/25M Midterm Review HW# 4 Due Project 1 Due 4/27WMIDTERM (text tables, one page of notes, calculator) Date Part II TopicsReadingsWeek 65/2MTS4: Scatterplot and Least Squares Line (scatterplot, correlation coefficient, least squares line, standard error of estimate, R-squared, adjusted R-squared) Case: Salary level vs. Experiences Case: MLB factors for winning Case: Movie making-1 Ch. 11: to p.4705/4WTS3: Random Sampling (representative sample, biased sample, table of random digits.) Ch 8: omit 8.5Week 75/9 MTS3: Sampling Distributions & Confidence Interval) (sampling distribution, central limit theorem, standard error, z-interval, t-table, t-interval,) Cases: Planning for Auditing, Political Poll Cases: Buy Product, Deli Expenditure Survey Cases: Samll Test RunCh 9 HW# 5 Due5/11WTS3: Hypothesis Testing 1 Setting Up (null and alternative (research) hypotheses, type I & II errors, level of significance, significant vs. real differences) Case: CO2 content Quiz 3Ch 10Week 85/16MTS3: Hypothesis Testing 2 Test Procedures (confidence interval, t-stat, & p-value methods) Cases: Awareness, Probability of Type II error HW#6 Due 5/18 WTS4: Hypothesis Testing for Regression (linear model as the population, standard error of the slope, test of significance of slope) Cases: Movie making - 2 Ch 11: p 470-481 Week 95/23MTS4: Regression (cont.) (comprehensive review of regression) HW#7 Due  5/25 WFinal Exam Review Questions Quiz 4 Week105/30MMemorial Day Holiday r6/1WQ and A. 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_Hlt103583547 _Hlt103583548@@?Dx~;@ FO QVv|){jt :;333333333333333333333333333$ m{FOBMN`BRVZ?Eaf "6;$:>B'University of Washington Buisness SchooPC:\Documents and Settings\htamura\My Documents\2-QMETH\1A-QMETH201U\syllabus.doc'University of Washington Buisness SchoocC:\Documents and Settings\htamura\Application Data\Microsoft\Word\AutoRecovery save of syllabus.asd'University of Washington Buisness SchoocC:\Documents and Settings\htamura\Application Data\Microsoft\Word\AutoRecovery save of syllabus.asd'University of Washington Buisness SchoocC:\Documents and Settings\htamura\Application Data\Microsoft\Word\AutoRecovery save of syllabus.asd'University of Washington Buisness SchoocC:\Documents and Settings\htamura\Application Data\Microsoft\Word\AutoRecovery save of syllabus.asd'University of Washington Buisness SchoocC:\Documents and Settings\htamura\Application Data\Microsoft\Word\AutoRecovery save of syllabus.asd'University of Washington Buisness SchoocC:\Documents and Settings\htamura\Application Data\Microsoft\Word\AutoRecovery save of syllabus.asd'University of Washington Buisness SchoocC:\Documents and Settings\htamura\Application Data\Microsoft\Word\AutoRecovery save of syllabus.asd'University of Washington Buisness SchoocC:\Documents and Settings\htamura\Application Data\Microsoft\Word\AutoRecovery save of syllabus.asd'University of Washington Buisness SchoocC:\Documents and Settings\htamura\Application Data\Microsoft\Word\AutoRecovery save of syllabus.asd4r(k2Du`Ztx$.QB:X0H|m^ 2D&w~`nxEځZ+G8Y3E(>"]2D,.,$Pt vRPV f\Yl!*=\P:C"4{=1#2D|n&DΩ6O)hc*:|)*B6iG+ҨwY+2D&3,3F.Xv% 52Dy62D15!7TV7FḞu=$R?2pDҨwi}JTOj^JR2D U@Fc9.[#\]^2DD_¸#a ych\Ui 1YiF Tl 9@V)*o( hh^h`OJQJo(^`o(.88^8`o(.^`.  ^ `o(()  ^ `.xx^x`.HLH^H`L.^`.^`.L^`L.hhh^h`.h88^8`.hL^`L.h  ^ `.h  ^ `.hxLx^x`L.hHH^H`.h^`.hL^`L.^`o(.^`o(. ^`B*o(ph.4i`{MD_u`15!7TV7:C"ycTO6O) UYl!Tl3Eu=PV c9.[Er,.R?&3,{=1#G8|mQx$1Yi,z|)*\Ui#a$Pt% 5]Y+JRy6X:y #\]^k&w~2pDG+)BD`abcik@EPSON Stylus Photo 820 Series (Copy 1)Ne00:winspoolEPSON Stylus Photo 820 SeriesEPSON Stylus Photo 820 Series `f odhhRL*** xhhDLLName32=E_DU13EE.DLL d 2EPSON Stylus Photo 820 Series  EPSON Stylus Photo 820 Series `f odhhRL*** xhhDLLName32=E_DU13EE.DLL d 2EPSON Stylus Photo 820 Series  (C`@UnknownGz Times New Roman5Symbol3& z ArialC PMingLiUe0}fԚG  MS Mincho-3 fg?5 z Courier New5& zaTahoma;Wingdings"Aha唆y&&  .=2k!20d ; 3QHINFORMATION AND REQUIREMENTSTSAI'University of Washington Buisness SchooOh+'0  <H d p | INFORMATION AND REQUIREMENTSMiNFOTSAIMATSAISAINormalT(University of Washington Buisness Schoo32vMicrosoft Word 9.0n@ @@ y@_Z@tL@_՜.+,D՜.+,H hp|   .  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