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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.


Please be aware that should your course have a final exam, you are responsible for the fee to the online proctoring service, ProctorU, or to the in-person approved Testing Centre. Please contact 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.

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