Bus 201-Data Collection and Analysis Fall 2004
Mari Yetimyan
Office: BT 756 Office Phone: (408) 924-3444 Fax: (408) 924-3445
E-mail: yetimyan_m@cob.sjsu.edu Web Page: www.cob.sjsu.edu/yetimy_m
Office Hours:
Tuesday
Course Description: Provides the knowledge and ability to gather and analyze data for applied uses, including sampling and collection of data, presentation of data, statistical inference and hypothesis testing, correlation and regression, and forecasting. An applied project is required; Excel is the basic analytical tool.
Textbook:
9th ed.,
Excel to be purchased at the bookstore.
Evaluation: Evaluation will be based on the following:
Two Exams 25% each
Comprehensive Final Exam 35%
Homework 5% (2 points for each problem in each homework, 8 points for each case)
Project 10%
Roughly, the breakdown of grades will be
90-100 A 80-89.9 B 70-79.9 C 60-69.9 D Below 60 F
Plus (+) and minus (-) designations for grades will be indicated in class.
Exams are closed-book and closed-notes with one 8.5 x 11 sheet (both sides) of notes allowed for each exam.
A list of homework problems will be distributed in class.
An approximately four-page project is due on the day of final exam. You are expected to apply the concepts learned in class to your real-life, preferably work-related problems. Please use whatever format you wish to use. Sample projects from previous semesters can be made available with prior notification.
Important dates
November 6 Second Saturday class (
Course Outline
Chapter 1 Data and Statistics and Chapter 7-7.2 Simple Random Sampling and 7.8
Other Sampling Methods
Chapter 2 Descriptive Statistics: Tabular and Graphical Presentations
Chapter 3 Descriptive Statistics: Numerical Methods
Chapter 4 Introduction to Probability
Chapter 5 Discrete Probability Distributions-5.1, 5.2, 5.3, and 5.4
Chapter 6 Continuous Probability Distributions-6.2 and 6.3
Chapter 7 Sampling and Sampling Distributions
Chapter 8 Interval Estimation
Chapter 9 Hypothesis Testing
Chapter 14 Simple Linear Regression
Chapter 15 Multiple Regression
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