PROPHET StatGuide: One-sample t test
The one-sample t test is used to test the
null hypothesis that the
mean of the population
from which the data
sample
is drawn is equal to a hypothesized value.
Assumptions:
Guidance:
Ways to detect before performing the
one-sample t test whether your data violate any
assumptions.
Ways to examine one-sample t test results to detect
assumption violations.
Possible alternatives if your data or one-sample t test
results indicate assumption violations.
To properly analyze and interpret
results of the one-sample 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 the
one-sample t test 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.
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Last modified: February 20, 1997
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