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Testing the mean for dependent business data.

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¹Department of Management, University of New Haven, West Haven, CT 06516, USA. jliang@newhaven.edu

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|December 2, 2008

Summary

This summary is machine-generated.

A new generalized F-test effectively compares population means with dependent data, overcoming limitations of the traditional F-test for survey and time-series analysis.

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Area of Science:

Statistics
Business Data Analysis
Econometrics

Background:

Traditional F-test in analysis of variance assumes independent data.
This assumption is often violated in survey and time-series data.
Direct application of the F-test to dependent means is problematic.

Purpose of the Study:

To develop a generalized F-test for comparing population means with dependent data.
To address the limitations of the traditional F-test in specific data contexts.

Main Methods:

Development of a generalized F-test.
Simulation studies to evaluate the test's performance.
Application to real-world survey and time-series datasets.

Main Results:

The proposed generalized F-test exhibits a simple approximate null distribution.
The test demonstrates feasible finite-sample properties.
Successful application illustrated with two real datasets.

Conclusions:

The generalized F-test provides a valid method for comparing means with dependent data.
This method is suitable for analyzing survey and time-series data.
The test offers a robust alternative to the traditional F-test in specific scenarios.