ECON 2331
Economic and Business Statistics 2

3.0 Credits

Description

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®.

Delivery Method

Online, self-paced.

Prerequisites

Recommended: ECON 1221 or ECON 1901 and ECON 1951; STAT 1201, MIST 2611

Objectives

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 Outline

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

Maximum Completion

30 weeks.

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

Additional Requirements

XLSTAT® is required and will be provided with the bundle of the textbook.

Open Learning Faculty Member Information

An Open Learning Faculty Member is available to assist students. Primary communication is through the Learning Environment's "Mail" tool or by phone. Students will receive the necessary contact information when starting the course.

Assessment

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