R7103 (Chicago Campus)

Fall - I, 2007

Dr. Bharat S. Thakkar

ArgosyUniversity

COURSE SYLLABUS

R7103

Solutions Oriented Business Research Methods

Fall I, 2007

INSTRUCTOR:

Bharat S. Thakkar, Ph.D.

PHONE:

630-267-7890

EMAIL:


REQUIRED TEXTS:

Title / Statistics for Business and Economics
Author(s) / McClave, Benson & Sincich
Copyright / 2005
Publisher / Pearson-Prentice Hall
ISBN / 0-13-046641-7
Edition / 9th
This Course Requires the Purchase of a Course Packet:NO

Short Faculty Bio:

Thakkar received his MS and PhD degrees both in mechanical engineering from Illinois Institute of Technology at Chicago in 1967 and 1976, respectively. He has been engaged in the practice of electronic systems packaging, design, development, compliance, and reliability engineering over last thirty years of which last twenty-six years were spent with Lucent Technologies (formerly AT&T Bell Laboratories). He has addressed the problems of system reliability, electronic packaging, shock and vibration, thermal management and physical design. Prior to joining Bell Labs, Thakkar was engaged in research and development of materials forming. He has been active in teaching at the Illinois Institute of Technology as Adjunct Associate Professor in Mechanical, Mechanics, and Aerospace Eng Dept. He also taught at the MidwestCollege of Engineering, where he was Chairman of Mechanical Engineering Department. Bharat published and presented over twenty technical papers and holds twoU. S. patents. He also has received several awards for community service and affirmative action activities at Bell Labs.
In fall of 1997, IIT conferred Alva C. Todd Professorship upon Dr. Thakkar. This honor is granted to a part-time faculty member who has a minimum of 15 years of peer-recognized experience in the field of engineering with significant responsibility for engineering projects, design and research. Dr. Thakkar was also appointed as a member of the Education Task Force of the Electrical and Electronic Packaging Division (EEPD) in the American Society of Mechanical Engineers (ASME).
Adjunct Faculty @ IIT, NIU, MCE, NWU, Loyola, COD, GovernorsStateUniversity, National-LouisUniversity, and ArgosyUniversity. Currently, Consultant and CEO, PREM Group, Inc., Wheaton, Illinois, offers workshops and seminars to domestic and international clients.

Course description:

This foundation course in business research provides an overview of business research methods and concepts of probability theory, regression analysis and assumptions of multivariate analysis. Computer software and the ethics of research in business settings are also components of the course.

Course Pre-requisites: None

Course length: 7.5 Weeks

Contact Hours: 45 Hours

Credit Value: 3.0

Program Outcomes:

  1. Research
  2. Performing – Design, conduct, and justify applied research in a business context using appropriate methodology
  3. Understanding – Evaluate and apply existing theory and research to current business practice
  4. Communication
  5. Oral – Present orally, complex business information that is concise, clear, organized, and well supported in a professional manner appropriate to the business context
  6. Written – Present in writing, complex business information that is concise, clear, organized, and well supported in a professional manner appropriate to the business context using required format
  7. Critical Thinking/Problem Solving
  8. Critical thinking – Evaluate relevance of established theory to current business practice and identify gaps in current literature
  9. Problem Solving/Decision Making – Given a business situation, diagnose the underlying causes of the situation, evaluate possible solutions, in relation to underlying business theory and determine and defend appropriate course of action
  10. Information Literacy - Conduct an exhaustive literature search from a variety of sources, evaluate the credibility of the sources, and apply that information to create new knowledge
  11. Team
  12. Leadership - Conduct an exhaustive literature search from a variety of sources, evaluate the credibility of the sources, and apply that information to create new knowledge
  13. Collaboration - Given a case study or business situation collect, assimilate, and disseminate the views of stakeholders
  14. Ethics
  15. Ethics - Given a case study or business situations, evaluate the ethical dimensions of decision situations and personal, social, and corporate responsibility not absolved by market forces
  16. Diversity
  17. Diversity - Given a case study or business situation evaluate the multicultural dimensions of decision situations and multicultural solutions to business situations

Course Objectives:

1. Structure problems to prepare for decision analysis.

1.1 Given a business situation, identify qualitative and quantitative variables. (Program Outcomes: 3.2)

1.2 Given statements about the frequency of two or more events, calculate conditional and joint probabilities. (Program Outcomes: 3.1, 3.2 )

1.3 Calculate z scores, convert them to probabilities and vice versa. (Program Outcomes: 3.2 )

1.4 Use Excel with PHStat2 to enter data and calculate test statistics and probabilities. (Program Outcomes: 3.2)

1.5 Construct confidence intervals. (Program Outcomes: 3.2)

1.6 Describe the hypothesis testing procedure. (Program Outcomes: 2.2, 3.3)

1.7 Determine whether the necessary conditions have been met to apply a specific statistical technique. (Program Outcomes: 3.2)

1.8 Identify whether a one-tailed or a two-tailed test is appropriate. (Program Outcomes:1.2, 3.3 )

2. Develop and refine data gathering skills and techniques

2.1 Organize data into frequency distributions. (Program Outcomes: 3.1)
2.2 Explain the relationship between populations and samples. (Program Outcomes: 1.1, 1.2, 2.2)

3.Analyze a business problem by (a) identifying the issues, (b) gathering, compiling and organizing data, (c) recommending solutions, and (d) determining success measures and objectives

3.1 Select the appropriate functions in PHStat2 to solve basic statistical problems. (Program Outcomes:1.1, 3.1, 3.2)

3.2Apply appropriate hypothesis testing procedures to one, two and multiple sets of data. (Program Outcomes: 3.2, 5.1)

3.3Apply appropriate hypothesis testing procedures to categorical data. (Program Outcomes: 1.1, 1.2, 3.1, 3.2, 6.1)

3.4Find the appropriate balance between Type I and Type II errors. (Program Outcomes: 1.1, 1.2, 2.2, 3.1)

3.5Distinguish between statistical and causal relationships. (Program Outcomes: 1.1, 1.2, 2.2, 3.1)

3.6Calculate the least squares regression line. (Program Outcomes: 3.2)

3.7Calculate coefficients of correlation and determination. (Program Outcomes: 3.2)

3.8Select the appropriate functions in PHStat2 to construct multiple regression models. (Program Outcomes: 1.2, 3.3)

3.9Given a business situation, assess the strengths and weaknesses of statistical analysis. (Program Outcomes: 1.1, 1.2, 2.2, 3.1)

4. Recognize problem resolution skills through the application of systems thinking and creative/innovative methodologies

4.1Find the relevance of descriptive and inferential statistics to business decision-making. (Program Outcomes: 1.1, 1.2, 2.2, 3.1, 5.1)

4.2Given different measures of central tendency and variability, determine which are consistent with one another. (Program Outcomes: 3.2, 3.3)

4.3Make inferences about populations from sample data, and vice versa. (Program Outcomes: 3.1, 5.1)

4.4Construct a sampling distribution of the sample mean. (Program Outcomes: 3.2)

4.5Use the Central Limit Theorem to make estimates. (Program Outcomes: 3.1, 3.2)

4.6Identify the weakness of point estimates. (Program Outcomes: 2,2 3.1)

4.7Use confidence intervals to augment point estimates. (Program Outcomes: 3.2)

4.8Determine appropriate sample sizes. (Program Outcomes: 3.2)

4.9Identify dependent and independent variables. (Program Outcomes: 1.1, 1.2, 3.1)

4.10Given historical data, use simple linear and multiple regression to make predictions, and assess the likely accuracy of predictions. (Program Outcomes: 2.2, 3.1, 3.2, 5.1)

Assignment Table

Module / Module Topics / Readings / Assignments
1 / Statistics & Business Decisions
Central Tendency
Variability
Standard Deviation
Probability
Events
Union & Intersection of Events
Mutual Exclusivity
Conditional Probability
(On-line) / Chapters 1, 2, and 3. / 1. Write a business case study illustrating concepts discussed in Ch 1. (Course objectives: 1.1, 1.3, 4.2)
2. Illustrate briefly a case where business decisions were made based upon probability of financial success (Course objectives: 1.2)
3. Choose three term paper topics illustrating solution oriented business research methods.
4. One Problem, each from Ch 1, 2, and 3.
2 / Binomial Distribution
Normal Distribution
Tests for Normality
Relationship between Binomial & Normal Distributions
(On-line) / Chapters 4 and 5 / (Course objectives: 1.2)
  1. Why would a machine component fail? Explain by normally distributed load / strength interference. (300 words)
  2. How does it help you to perform statistical analyses and make business decisions if a variable is normally distributed?
  3. Describe three tests that can be used to determine if a variable is normally distributed, including the criteria for deciding whether each test has been met or not.
(Course objectives: 1.7, 2.2, 3.9, 4.1)
4. One Problem, each from Ch 4 and 5
3 / Sampling Distribution
Central Limit Theorem
Confidence Intervals for Means
Confidence Intervals for Proportions, Sample Size
(On-line) / Chapters 6 and 7 / 1. Examine the effect of sample size on the standard error of the mean. Give your work-related example.
(Course objectives: 4.3, 4.4, 4.5)
2. One Problem, each from Ch 6 and 7.
4 / Hypothesis Testing
Elements of Hypothesis Testing
Test for Population Mean / Chapters 8 and 9 / 1. One Problem, each from Ch 8 and 9.
(Course objectives: 1.3, 1.6, 1.8, )
2. In your own words, explain in ten steps how two new treatments for a medical disease could be compared using the statistical method of hypothesis testing.
(Course objectives: 3.2, 3.4, 3.5)
5 / Analysis of Variance (ANOVA)
Elements of ANOVA
Single Factor
Comparing Multiple Means
(On Intralearn) / Chapter 10 / 1. One Problem from Ch 10.
(Course objectives: 3.2)
6 / Chi-Square Tests
Categorical Data / Chapter 11 / 1. Two Problems from Ch 11.
(Course objectives: 3.3, 3.9)
7 / Simple Linear Regression
Estimating and Predicting
Multiple Regression / Chapter 12 and 13 /
  1. Two Problems from Ch 12.
(Course objectives: 3.6, 3.7, 4.9, 4.10)
2. One Problem from Ch 13
(Course objectives: 3.8, 4.9, 4.10)
8 / Approved Term Paper Topic Individual Presentations / _ / 10-minute per presentation including Q & A.

Grading Criteria

Grading ScaleGrading requirements

A / 100 – 93
A- / 92 – 90
B+ / 89 – 88
B / 87 – 83
B- / 82 – 80
C+ / 79 – 78
C / 77 – 73
C- / 72 – 70
F / 69 and below
Attendance/participation / 30%
Weekly Assignments / 30%
Final paper/ Presentation / 40%

Library:

All resources in ArgosyUniversity’s online collection are available through the Internet. The campus librarian will provide students with links, user IDs, and passwords.

Library Resources: Argosy University’s core online collection features nearly 21,000 full-text journals and 23,000 electronic books and other content covering all academic subject areas including Business & Economics, Career & General Education, Computers, Engineering & Applied Science, Humanities, Science, Medicine & Allied Health, and Social & Behavior Sciences. Many titles are directly accessible through the Online Public Access Catalog at . Detailed descriptions of online resources are located at .

In addition to online resources, ArgosyUniversity’s onsite collections contain a wealth of subject-specific research materials searchable in the Online Public Access Catalog. Catalog searching is easily limited to individual campus collections. Alternatively, students can search combined collections of all ArgosyUniversity Libraries. Students are encouraged to seek research and reference assistance from campus librarians.

Information Literacy: ArgosyUniversity’s Information Literacy Tutorial was developed to teach students fundamental and transferable research skills. The tutorial consists of five modules where students learn to select sources appropriate for academic-level research, search periodical indexes and search engines, and evaluate and cite information. In the tutorial, students study concepts and practice them through interactions. At the conclusion of each module, they can test their comprehension and receive immediate feedback. Each module takes less than 20 minutes to complete. Please view the tutorial at

Academic Policies

Academic Dishonesty/Plagiarism: In an effort to foster a spirit of honesty and integrity during the learning process, ArgosyUniversity requires that the submission of all course assignments represent the original work produced by that student. All sources must be documented through normal scholarly references/citations and all work must be submitted using the Publication Manual of the American Psychological Association, 5th Edition (2001). WashingtonDC: American Psychological Association (APA) format. Please refer to Appendix A in the Publication Manual of the American Psychological Association, 5th Edition for thesis and paper format. Students are encouraged to purchase this manual (required in some courses) and become familiar with its content as well as consult the ArgosyUniversity catalog for further information regarding academic dishonesty and plagiarism.

Scholarly writing: The faculty at ArgosyUniversity is dedicated to providing a learning environment that supports scholarly and ethical writing, free from academic dishonesty and plagiarism. This includes the proper and appropriate referencing of all sources. You may be asked to submit your course assignments through “Turnitin,” (), an online resource established to help educators develop writing/research skills and detect potential cases of academic dishonesty. Turnitin compares submitted papers to billions of pages of content and provides a comparison report to your instructor. This comparison detects papers that share common information and duplicative language.

Americans with Disabilities Act Policy

It is the policy of ArgosyUniversity to make reasonable accommodations for qualified students with disabilities, in accordance with the Americans with Disabilities Act (ADA). If a student with disabilities needs accommodations, the student must notify the Director of Student Services. Procedures for documenting student disability and the development of reasonable accommodations will be provided to the student upon request.

Students will be notified by the Director of Student Services when each request for accommodation is approved or denied in writing via a designated form. To receive accommodation in class, it is the student’s responsibility to present the form (at his or her discretion) to the instructor. In an effort to protect student privacy, the Department of Student Services will not discuss the accommodation needs of any student with instructors. Faculty may not make accommodations for individuals who have not been approved in this manner.

The ArgosyUniversity Statement Regarding Diversity

The ArgosyUniversity provides equitable access through its services and programs to students of any social, geographic and cultural background, regardless of gender, and strives to prepare all candidates to work with and provide services to diverse populations. Argosy demonstrates its commitment to diversity through the development and support of a diverse educational community.

SYLLABUS ACKNOWLEDGEMENT FORM:
I have read and understand the syllabus and the course requirements as outlined in theR7103 Solutions OrientedBusiness Research Methods Course Syllabus.
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Student Signature Date
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Print Name of Student

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