PROPHET StatGuide: t Test--Testing equality of means

one-sample (test whether population mean is equal to hypothesized value)
two-sample paired (test whether population mean of paired differences is 0)
two-sample unpaired (test whether two population means are equal)

The full version of StatGuide for the t test will be available in a future release. In the meantime, to properly analyze and interpret results of the t test, 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 t Tests may result in drawing erroneous conclusions from your data. 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.
Miller, Rupert G. Jr. 1986. Beyond ANOVA, Basics of Applied Statistics. 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.

PROPHET StatGuide: t Test--Testing equality of means

Examine the glossary.
Do a keyword search of PROPHET StatGuide.
Back to StatGuide home page.

Last modified: February 14, 1997

PROPHET StatGuide: t Test--Testing equality of means

Examine the glossary. Do a keyword search of PROPHET StatGuide. Back to StatGuide home page.

Last modified: February 14, 1997

Examine the glossary.
Do a keyword search of PROPHET StatGuide.
Back to StatGuide home page.