ECON 2331: Economic and Business Statistics 2
Building on STAT 1201: Introduction to Probability and Statistics, students examine advanced statistical techniques and methods and their applications in business and economics. Topics include review of hypothesis tests; inferences about population variances; comparing multiple proportions for three or more populations and tests of independence; analysis of variance and experimental design; simple and multiple regressions; and time series analysis and forecasting. Students are required to apply statistical techniques using Excel® and/or XLSTAT®.
Learning outcomes
After completing this course, students should be able to:
- Demonstrate how to test hypotheses, including nonparametric methods.
- Test for the equality of three or more population proportions.
- Conduct analysis of variance under various experimental designs
- Estimate simple and multiple regression models and interpret the results.
- Use time series analysis and forecasting models to make accurate forecasts.
- Apply statistical techniques to various fields such as marketing, supply chain management, finance, accounting, and economics using real-world data.
- Demonstrate the ability to use Excel® and XLSTAT® in estimating applied statistical procedures, methods, and models.
Course topics
Module 1: Review of Hypothesis Testing and Statistical Inferences
- Developing null and alternative hypotheses
- One and two population(s) mean(s): known and unknown
- One and two population(s) proportion(s)
- Selected nonparametric tests of hypothesis
Module 2: Inference about Population Variances
- Inferences about a population variance
- Inferences about two population variances
Module 3: Comparing Multiple Proportions for Three or More Populations and Test of Independence
- Multiple comparison procedures
- Test of independence
- Tests of goodness of fit
Module 4: Analysis of Variance and Experimental Designs
- Concept of ANOVA
- Comparison of several population means
- Completely randomized design
- Randomized block design
- Factorial experiment
Module 5: Simple and Multiple Regression
- Simple linear and multiple regression models and regression equations
- Least square method
- Simple and multiple regression model assumptions
- Coefficient of determination
- Testing for significance
- Confidence and prediction intervals
- Categorical independent variables and interpreting the parameters
- Interaction
- Determining when to add or delete variable
Module 6: Time Series Analysis and Forecasting
- Time series patterns
- Forecast accuracy
- Moving average and exponential smoothing
- Trend projection
- Seasonality and trend
- Time series decomposition
Required text and materials
Anderson, D. R., Sweeney, D. J., Williams, T. A., Camm, J. D., & Cochran, J. J.
Statistics for business and economics (with XLSTAT Education Edition Printed Access
Card). (13th ed.). Mason, OH: South-Western (Cengage Learning), 2014.
Type: ISBN-13:
9781305585317
Or 13th “Revised” edition ISBN: 978-1-337-09416-0
Additional requirements
XLSTAT® is required and will be provided with the bundle of the textbook.
Assessments
Please be aware that should your course have a final exam, students are responsible for the fee to the online proctoring service, ProctorU, or to the in person approved Testing Centre. Please contact exams@tru.ca with any questions about this.
In order to successfully complete this course, students must obtain at least 50% on the final mandatory examination and 50% overall.
Assignment 1 | 5% |
Assignment 2 | 5% |
Assignment 3 | 5% |
Assignment 4 | 5% |
Assignment 5 | 15% |
Quiz 1 | 5% |
Quiz 2 | 5% |
Quiz 3 | 5% |
Final Exam * | 50% |
Total | 100% |
* Mandatory
Open Learning Faculty Member Information
An Open Learning Faculty Member is available to assist students. Students will receive the necessary contact information at the start of the course.