eco362

This course deals with the use of statistical techniques for business and economic decision making. An examination of representative techniques is intended to develop an acquaintance with such an approach to decision making.

Course Data --
Instructor	Dr. Ray Guydosh
Email	ray.guydosh@plattsburgh.edu
Office	Redcay-114
Telephone	518.564.4189 (email is better)
Office Hours	To Be Announced
Website	http://faculty.plattsburgh.edu/ray.guydosh
Materials	The student will receive some assignments by email.
Materials	Additional handouts will be provided.
Recommended	Statistics for Management and Economics, Fifth Edition, Gerald Keller and Brian Warrack, Duxbury, 1999

Course Objectives -- Objectives which are common to all sections of the course and all instructors of the course appear in bold.

S -- To develop an acquaintance with the use of statistical techniques in decision making.

C -- To develop an acquaintance with the use of computer techniques for statistical analysis.

P -- To understand how statistics can facilitate problem solving and decision making in organizations.

Evaluation --

There will be about twenty problem assignments, most centered around a statistical test. These problems will be distributed to you by email and you will submit your answers using a form on the course website. These assignment will count approximately 80% of the course grade.

The instructor understands that not only does technology not always work as expected, but also that other personal problems sometimes arise during a semester. And, sometimes a person just messes something up. The you may therefore select one assignment to omit during the semester without penalty.

HOWEVER, the instructor expects you to allow time for things to go wrong. He expects that you will not submit assignments late. He understands that sometimes doing an assignment late will still teach you something, but he also understands that following the order and timing of course material teaches you more. Besides, doing an assignment late can keep you from spending your full energy on a current assignment. Sometimes doing an assignment late can also inconvenience your classmates and your instructor and keep them from giving their full energy to their own activities. Other than described above, doing an assignment late will benefit your learning, but late assignments will not be graded.

There will be a semester-long project that will involve the collection and analysis of data gathered by the class. You will be working on this project in steps throughout the semester. This project will count about 20% of your grade.

There may be several additional assignments, not described above. There may be an examination during the course. If so, the percentages described above will be appropriately adjusted.

Tentative Course Schedule -- Subject To Frequent Updates and Changes
Class Days		Assn#	Due	Topic	Objectives
				Assignment
Jan 24		0	Jan 29	Introduction	SP
				Read Course Syllabus
Jan 29		1	Jan 31	Excel Spreadsheet Statistical Functions	SCP
				Calculating Location and Spread
Jan 31	Example	2	Feb 5	Ways of Defining Location and Spread	SCP
				Writing a Statistics Problem
Feb 5	Example Example	3	Feb 7	Distribution of Sample Measurements	SCP
				Estimating Location Knowing Spread
Feb 7	Example	4	Feb 13	Is A Sample From A Particular Population? A Touch of Quality Control	SCP
				Confidence Interval For Population Means
Feb 19	Example	5	Feb 21	Estimating Population Mean Not Knowing Spread	SCP
				Estimating Population Mean Not Knowing Spread
Feb 21	Example	7	Feb 26	Estimating Population Proportion From A Sample	SCP
				Estimating Population Proportion From A Sample
Feb 26	Example Example	6	Feb 28	Estimating Population Spread From A Sample	SCP
				Estimating Population Spread From A Sample
Feb 28	Example Example	9	Mar 5	Differences in Two Means-Matched Samples	SCP
				Differences in Two Means-Matched Samples
Mar 12	Example	10	Mar 14	Differences in Two Means-Unrelated Samples	SCP
				Differences in Two Means-Unrelated Samples
Mar 26	Example	8	Mar 28	Differences in Two Proportions	SCP
				Differences in Two Proportions
Mar 28	Example	11	Apr 2	Differences Two Variances	SCP
				Differences in Two Variances
Apr 2	Example Example	12	Apr 9	Differences in Two Populations (NP/NN)	SCP
				Wilcoxon Rank Sum Test
Apr 9	Example Example	13	Apr 11	Differences in Two Matched Populations (NP/NN)	SCP
				Sign Test
Apr 11	Example Example	17	Apr 16	Differences in Several Populations (NP)	SCP
				Chi Squared in One Dimension
Apr 16	Example Example	18	Apr 18	Relations Between Two Populations (NP)	SCP
				Chi Squared in Two Dimensions
Apr 18	Example Example	14	Apr 23	Differences in Several Populations	SCP
				Analysis of Variance One Factor
Apr 23	Example Example	14	Apr 25	Differences in Several Populations	SCP
				Analysis of Variance One Factor
Apr 25	Example Example	15	Apr 30	Relations Between Two Populations	SCP
				Analysis of Variance Two Factors
Apr 30 May 2	Example Example	19	May 7	Relations Between Two Variables	SCP
				Simple Regression
May 7	Example Example	20	May 9	Relations Among Several Variables	SCP
				Multiple Regression
May 9	Example Example	21	May	Selecting and Applying the Proper Test	SCP
				Data Analysis
May 9	Example Example	21	May	Selecting and Applying the Proper Test	SCP
				Data Analysis
May ??	Course Evaluation	Exam	May	Exam Week	SCP
				Exam Week & Course Evaluation Due
May		TBA	May	TBA	SCP
				TBA
May		TBA	May	TBA	SCP
				TBA
May		TBA	May 18	TBA	SCP
				TBA
May		TBA	May	TBA	SCP
				TBA
May		TBA	May	TBA	SCP
				TBA
May		TBA	May	TBA	SCP
				TBA
May		TBA	May	TBA	SCP
				TBA
May		TBA	May	TBA	SCP
				TBA
May		TBA	May	TBA	SCP
				TBA

Course Perspectives -- Information contained in the following tables is expected to be part of every core course outline in the School of Business and Economics at Plattsburgh State University.
There exist "perspectives" that form the context for business activities and study. Knowledge relating to such perspectives receive, to a greater or lesser extent, emphasis in all business and economics courses. To the extent specified on the matrix below, faculty in the department teaching this course cover these perspectives through examples, case studies, assignments or reading material. Similarly, a particular course may provide, in one way or another, opportunities for students to enhance their performance or understanding with respect to specified skills. For this particular course, the emphasis given to enhancing knowledge of selected perspectives and developing particular skills, ranging from none to high is as follows:
Skills Enhancement	None	Low	Mod	High	Knowledge Enhancement	None	Low	Mod	High
Written Communication		x			Ethical		x
Oral Communication		x			Global	x
Mathematical Analysis				x	Political, Social and Legal		x
Statistical Analysis				x	Regulatory	x
Computer Literacy			x		Environmental	x
Team Building	x				Technological			x
Research Methods			x		Demographic Diversity	x
Analytical & Integrative Processes			x

Note --

This course outline is not necessarily a complete description of the course and does not constitute a contract between the student and the instructor or the College. Changes may be made to the policies and information on this outline.

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ECO362

Business And Economics Data Modeling