INFORMATION AND REQUIREMENTS



Quantitative Methods 201 U (4), Spring 2005

MW 5.30 to 7:20 PM in BLM 209



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 company’s 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:

1. Homework 12% (turn in at the beginning of due class sessions)

2. Quiz: 8% (10 minutes, see the schedule)

3. Project - 1 10% (W, April 25)

4. Midterm 20% (W, April 27)

5. Project - 2 15% (W, June 1)

6. Final 35% (W, June 1 or M, June 6: 6:30-8:20 PM)

1. 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.

2. Quizzes: Closed book, except table pages, and closed-notes. Bring your calculator!

3. 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.

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4. 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.

5. 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

|Date |Part I Topics (subject to minor changes) |Readings |

|Week 1 | 3/28 |M |Orientation | |

| | | |Statistics for Management |Ch. 1, Ch. 18.1&2 |

| | | |TS1: Data structure and variable type |Ch. 2, |

| | | |(study unit; variable types: quantitative, qualitative, nominal, ordinal) | |

| | | |Case: Survey of exercise level | |

| | 3/30 |W |TS1: Descriptive Statistics-1 |Ch. 3, Ch. 4 |

| | | |(histogram, relative frequency, mode, mean, median, minimum, maximum, |Ch. 5: 5.1,5.2, 5.4 |

| | | |quartiles) | |

| | | |Case: Does the promotion work? | |

|Week 2 | 4/4 |M |TS1: Descriptive Statistics-2 |Ch 7: 7.3 |

| | | |(variance, standard deviation) | |

| | | |TS1: Normal distribution | |

| | | |(normal curve, standard normal table, z-score) | |

| | | |Case: Investment risk analysis | |

| | | |HW#1 Due: | |

| |4/6 |W |TS2: Probability |Ch. 6: 6.1-6.4 |

| | | |(random experiment, outcome, sample space, event, sources of probability) | |

| | | |Quiz 1: | |

|Week 3 |411 |M |TS2: Probability – (rules for computing probability) |Ch. 6: 6.5 |

| | | |(complimentary event, intersection, union, independent, mutually exclusive,| |

| | | |conditional probability; Venn diagram) | |

| | | |Case: System reliability | |

| | | |HW# 2 Due: | |

| |4/13 |W |TS2: 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: Let’s Make a Deal | |

| | | |Case: Sensitive interview | |

|Week 4 |4/18 |M |TS2: Random Variable |Ch 7: p.236-247 |

| | | |(probability distribution, expected value, standard deviation) | |

| | | |Case: Las Vegas roulette | |

| | | |HW# 3 Due: | |

| |4/20 |W |Random Variable (cont’d) |Ch.7: 7.4 |

| | | |(binomial distribution - definition, normal approximation) | |

| | | |Case: Misjudging the true popularity | |

| | | |Case: Does organic milk taste better? | |

| | | |Quiz 2: | |

|Week 5 |4/25 |M |Midterm Review | |

| | | |HW# 4 Due | |

| | | |Project – 1 Due | |

| |4/27 |W |MIDTERM (text tables, one page of notes, calculator) | |

|Date | | |Part II Topics |Readings |

|Week 6 |5/2 |M |TS4: Scatterplot and Least Squares Line |Ch. 11: to p.470 |

| | | |(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 | |

| |5/4 |W |TS3: Random Sampling |Ch 8: omit 8.5 |

| | | |(representative sample, biased sample, table of random digits.) | |

|Week 7 |5/9 |M |TS3: Sampling Distributions & Confidence Interval) |Ch 9 |

| | | |(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 Run | |

| | | |HW# 5 Due | |

| |5/11 |W |TS3: Hypothesis Testing – 1 Setting Up |Ch 10 |

| | | |(null and alternative (research) hypotheses, | |

| | | |type I & II errors, level of significance, significant vs. real | |

| | | |differences) | |

| | | |Case: CO2 content | |

| | | |Quiz 3 | |

| | | | | |

|Week 8 |5/16 |M |TS3: Hypothesis Testing – 2 Test Procedures | |

| | | |(confidence interval, t-stat, & p-value methods) | |

| | | |Cases: Awareness, Probability of Type II error | |

| | | |HW#6 Due | |

| |5/18 |W |TS4: Hypothesis Testing for Regression |Ch 11: p 470-481 |

| | | |(linear model as the population, standard error of the slope, test | |

| | | |of significance of slope) | |

| | | |Cases: Movie making - 2 | |

|Week 9 |5/23 |M |TS4: Regression (cont.) | |

| | | |(comprehensive review of regression) | |

| | | |HW#7 Due | |

| |5/25 |W |Final Exam Review Questions | |

| | | |Quiz 4 | |

|Week10 |5/30 |M |Memorial Day Holiday |r |

| |6/1 |W |Q and A. Course Evaluation | |

| | 6/6 |M |Project 2 Due | |

| | | |Final Exam: 6:30-8:20 PM | |

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