Lectures and computer seminars.
- Review of Statistics: interval estimation and hypothesis testing, 1 and 2 populations.
- Inference about Population Variance: Multinomial population, contingency tables, Poisson and Normal Distributions.
- Tests of Goodness of Fit and Independence. Chi-squared distribution.
- Analysis of Variance.
- Linear Regression: Least Squares Method, r and R2, variance, t and F tests, estimation and prediction, computer solution, residuals.
- Multiple Regression: Least Squares Method, adjusted R2, t and F tests, multicollinearity, estimation and prediction, qualitative variables, residuals.
- Index Numbers: price indices, computing an aggregate index, deflating a series.
- Forecasting and Time Series: components, smoothing, trend projection, seasonality, projection using regression.
- Decision Analysis: structuring the problem, decision-making with and without probabilities.
- Linear Programming: formulating problems, graphical solutions, computer solutions, sensitivity analysis.
The student will be able to:
- carry out interval estimation, hypothesis testing and other analyses related to variance;
- conduct tests related to goodness of fit and independence;
- find relationships between data sets using regression techniques;
- develop forecasts using price indices, smoothing and regression;
- analyze decisions using probability theory;
- use computer spreadsheets in solving statistical problems.
|Term Examination (1-3)||40%-50%|
|Computer Lab Test||5%-10%|
Textbooks and Materials to be Purchased by Students
Anderson, D.R., Sweeney et al. Statistics for Business and Economics, Latest Ed. Thompson South-Western
DeVeaux, Velleman and Wright. Business Statistics, latest Cdn Ed., Pearson Canada
or similar Business Statistics textbook
Supplement: Linear Programming
Excel spreadsheet applications text as selected by instructor:
Department approved Business Calculator
BUSN 2429 or BUSN 430