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®.
Recommended: ECON 1221 or ECON 1901 and ECON 1951; STAT 1201, MIST 2611
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.
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
- 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
XLSTAT® is required and will be provided with the bundle of the textbook.
Open Learning Faculty Member
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.
In order to successfully complete this course, students must obtain at least 50% on the final mandatory examination and 50% overall.
|Final Exam *||50%|