Abstract
Let’s assume we do an experiment, compute the t-value and p-value for our sample, and based on these values, reject the null hypothesis. As we mentioned in the previous chapter, and as you can prove to yourself through simulated replication of experiments, due to the very nature of random sampling it is always possible to stumble on a ‘rogue sample’, one whose statistic happens to be far from the population parameter. In this case it would, in fact, be an error to reject the hypothesis, though we wouldn’t know it. The technical name for this is a Type I error: the null hypothesis is true, but our sample leads us to reject it.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Baayen, R. (2008). Analyzing Linguistic Data. A Practical Introduction to Statistics Using R. Cambridge University Press.
Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2 ed.). Hillsdale, NJ: Lawrence Erlbaum.
Hoenig, J. M., & Heisey, D. M. (2001). The abuse of power: The pervasive fallacy of power calculations for data analysis. The American Statistician, 55 (1), 19–24.
Oakes, M. (1987). Statistical inference: A commentary for the Social and Behavioral Sciences. NY: John Wiley and Sons.
Schuirmann, D. (1987). A comparison of the two one-sided tests procedure and the power approach for assessing the equivalence of average bioavailability. Journal of Pharmacokinetics and Pharmacodynamics, 15 (6), 657–680.
Stegner, B. L., Bostrom, A. G., & Greenfield, T. K. (1996). Equivalence testing for use in psychosocial and services research: An introduction with examples. Evaluation and Program Planning, 19 (3), 193–198.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
Copyright information
© 2011 Springer-Verlag Berlin Heidelberg
About this chapter
Cite this chapter
Vasishth, S., Broe, M. (2011). Power. In: The Foundations of Statistics: A Simulation-based Approach. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16313-5_4
Download citation
DOI: https://doi.org/10.1007/978-3-642-16313-5_4
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16312-8
Online ISBN: 978-3-642-16313-5
eBook Packages: Mathematics and StatisticsMathematics and Statistics (R0)