Info 281 Intermediate Business Statistics

This syllabus is a bare minimum information about the course.  For detailed information please visit Myclasses at Salisbury University

Info 281-001	Intermediate Business Statistics	Tuesday/Thursday 9:30AM-10:45AM	352 Perdue Hall
Info 281-002	Intermediate Business Statistics	Tuesday/Thursday 11:00AM-12:15PM	352 Perdue Hall
Info 281-003	Intermediate Business Statistics	Tuesday/Thursday 2:00PM-3:15PM	249 Perdue Hall

INSTRUCTOR

Fati Salimian

Office:  Perdue Hall 341                   Office Phone:  543-6321

Office Hours: 
Tuesdays:   4:00 PM – 5:00 PM

Wednesdays: 10:00 AM - 1200 PM                       
and by appointments.

E-Mail: mailto:fxsalimian@salisbury.edu

RECOMMENDED TEXTS

MindTap® Business Statistics with XLSTAT; 1 term (6 months) Instant Access for Anderson/Sweeney/Williams/Camm/Cochran's Statistics for Business & Economics; Revised; 13th Edition

AUTHORS: Anderson/Sweeney/Williams/Camm/Cochran - ©2018 
ISBN-10: 1-337-40660-0 
ISBN-13: 978-1-337-40660-4

I have made a special arrangement with the publisher and the above package can be purchased exclusively from them at a special low price based on these instructions:

Internet resources:  http://en.wikipedia.org/wiki/Main_Page

COURSE DESCRIPTION

Prerequisites:  MATH 160 or 201, MATH 155, INFO 211 and will be enforced.

Learning Goals: Upon the completion of this course students should be able to:

· Understand the importance of Statistics in effectively analyzing business problems and providing support for optimal decision making.

·  Construct thought provoking theories and test their validity by applying appropriate statistical techniques.

· Develop knowledge in gathering primary and secondary data collection.

· Utilize computer technology in collecting, organizing, analyzing, and presenting statistical information.

Learning Objectives:

1. Design instruments and gathering strategies to obtain primary data.
2. Identify, access, and import reliable sources of secondary data.
 3. Conduct statistical analyses to test for differences between groups using parametric and nonparametric methods.
4. Perform tests related to the nature of data distributions .
5. Perform simple linear, multiple and non-linear regression analyses.
6. Build models with an optimal mix of variables and reliable results.
7. Address dimensionality in data, such as structure and time.

Grading and Examination:  The final grade for the course will be determined according to the following scheme:

Grading and Examination:  The final grade for the course will be determined according to the following scheme:

EXAM I 10%
EXAM II 20%
EXAM III 20%
ASSIGNMENTS 20% 
UNANNOUNCED QUIZZES AND
 CLASS PARTICIPATION 10% 
FINAL EXAM 20%

TOTAL 100%

Attendance:  Students are expected to attend all classes and take good notes.  Should there be any absence, students are held fully responsible for the material assigned and presented. Students are allowed to have one absence. Each additional absence will result in 1 point deduction from your overall score. This class adheres to the School of Business Code of Conduct.

Assignments:  All students are required to have all assignments completed before the due dates.

Make-Ups:       Students who miss any examination are required to notify the instructor immediately.  A make-up examination will be arranged only if the missed exam is due to circumstances beyond the control of the student. 

WATC:  The University writing across the curriculum requirement will be fulfilled through various written assignments and the Lab activities.

Data Collection:    In order to intensely engage students in the complex statistical topics discussed throughout the duration of the semester a questionnaire  related to the issues of concern to students will be examined, fine-tuned and completed by all the students. The resulting Student Questionnaire Excel File  will be used to illustrate the covered topics.

Computer Use: Microsoft Office Professional Plus 2016 (optional) 

Computer packages are used to facilitate computational aspects of various statistical methods.  A brief description of at least one software package (MINITAB, Microsoft Excel 2013) will be discussed throughout the duration of the semester.

COURSE CONTENT

UNIT 1

Module 1.  Introduction to Data and Statistics

Module 2. Measures of location, measures of variability

Module 3. Normal distribution

Module 4.  Fundamentals of hypothesis testing

EXAM I

UNIT 2

Module 5. Tests of Goodness of Fit and Independence 

  A Multinomial population.

Test of Independence: Contingency Tables. 

Goodness of Fit Tests: Multinomial, Normal & Poisson Distributions.

Marascuilo Procedure.

Module 6. Experimental Design and Analysis of Variance 

Basic Concepts.

One Way ANOVA.

Completely randomized designs.

Randomized block designs.

 Factorial Experiments: Two Way ANOVA

EXAM II

UNIT 3

Module 7. Simple Linear Regression

Types of Regression Models  

Scattergram

 Using least square method to find regression line

 Confidence and Prediction Intervals

 Correlation Analysis

  Inferences about population parameters and correlation

  Residual Analysis

  Pitfalls in Regression and Ethical Issues

Module 8.  Multiple Regression

Developing the Multiple Regression equation. 

Standard error of estimate and coefficient of multiple determination

Inference about population parameters

Analysis of Variance

Using Dummy variables And Interaction Terms.

Residual Analysis

Qualitative Variables

Multicollinearity

Other issues in multiple linear regression

Module 9.  Regression Analysis: Model Building

Transformation of dependent & Independent variables

Nonlinear Regression Model

Variable selection procedure

Multicollinearity

Stepwise Regression

Best subset Regression 

EXAM III 

UNIT 4

Module 10. Index Numbers

            Index Numbers

            Price Relatives  

 Aggregate Price Index

Some Important Price Indexes: Dow Jones Industrial Average,    Consumer Price Index

            Quantity Indexes.

Module 11. Time Series Analysis and Forecasting

Classical time series model

Description of trend

Measurement of seasonal variations

Measurement of cyclical movements

Smoothing Techniques

Seasonal Indexes

FINAL EXAM    

Final Exam Schedule

Section 001(T, Th 9:30 AM-10:45 AM class) Tuesday Dec 18, 10:45 AM – 1:15 PM

Section 002(T, Th 11:00 AM-12:15 PM class) Thursday, Dec. 13, 10:45 AM – 1:15 PM

Section 003(T, Th 2:00 PM-3:15 PM class) Thursday, Dec. 13, 4:15 PM – 6:45 PM