## Curriculum Guideline

Effective Date:
Course
Discontinued
No
Course Code
BUSN 3431
Descriptive
Department
Faculty
Credits
3.00
Start Date
End Term
201430
PLAR
No
Semester Length
15 Weeks X 4 Hours per Week = 60 Hours
Max Class Size
35
Contact Hours
Lecture: 3 Hours Seminar: 1 Hour Total: 4 Hours
Method Of Instruction
Lecture
Seminar
Methods Of Instruction

Lectures and computer seminars.

Course Description
This course covers advanced topics in quantitative analysis including: analysis of variance, forecasting, trend analysis using linear and multiple regression, probability, decision analysis, and linear programming. Spreadsheets will be utilized in problem-solving.
Course Content
1. Review of Statistics: interval estimation and hypothesis testing, 1 and 2 populations.
2. Inference about Population Variance: Multinomial population, contingency tables, Poisson and Normal Distributions.
3. Tests of Goodness of Fit and Independence. Chi-squared distribution.
4. Analysis of Variance.
5. Linear Regression: Least Squares Method, r and R2, variance, t and F tests, estimation and prediction, computer solution, residuals.
6. Multiple Regression: Least Squares Method, adjusted R2, t and F tests, multicollinearity, estimation and prediction, qualitative variables, residuals.
7. Index Numbers:  price indices, computing an aggregate index, deflating a series.
8. Forecasting and Time Series:  components, smoothing, trend projection, seasonality, projection using regression.
9. Decision Analysis:  structuring the problem, decision-making with and without probabilities.
10. Linear Programming:  formulating problems, graphical solutions, computer solutions, sensitivity analysis.
Learning Outcomes

The student will be able to:

1. carry out interval estimation, hypothesis testing and other analyses related to variance;
2. conduct tests related to goodness of fit and independence;
3. find relationships between data sets using regression techniques;
4. develop forecasts using price indices, smoothing and regression;
5. analyze decisions using probability theory;
6. use computer spreadsheets in solving statistical problems.
Means of Assessment
 Final Examination 30% Term Examination (1-3) 40%-50% Computer Lab Test 5%-10% Assignments 15%-25% Participation 0%-5% 100%
Textbook Materials

Textbooks and Materials to be Purchased by Students

Anderson, D.R., Sweeney et al.  Statistics for Business and Economics, Latest Ed.  Thompson South-Western