The chi-square test for variance is used to test the null hypothesis that the variance of the population from which the data sample is drawn is equal to a hypothesized value.
To properly analyze and interpret results of chi-square test for variance, you should be familiar with the following terms and concepts:
If you are not familiar with these terms and concepts, you are advised to consult with a statistician. Failure to understand and properly apply chi-square test for variance may result in drawing erroneous conclusions from your data. Critical Chi-Square Values
Additionally, you may want to consult the following references:
- Brownlee, K. A. 1965. Statistical Theory and Methodology in Science and Engineering. New York: John Wiley & Sons.
- Daniel, Wayne W. 1995. Biostatistics. 6th ed. New York: John Wiley & Sons.
- Rosner, Bernard. 1995. Fundamentals of Biostatistics. 4th ed. Belmont, California: Duxbury Press.
- Sokal, Robert R. and Rohlf, F. James. 1995. Biometry. 3rd. ed. New York: W. H. Freeman and Co.
- Zar, Jerrold H. 1996. Biostatistical Analysis. 3rd ed. Upper Saddle River, NJ: Prentice-Hall.
Glossary | StatGuide Home | Home
