Abstract
The results obtained in a particular study may or may not reflect those of the larger underlying population. Statistical inference is a mathematical process used to relate findings obtained from a sample (study) to those in the population. Two characteristics that influence how closely sample results are likely to reflect those in the population are sample size and variance. A larger sample size and a smaller variance increase the likelihood that the results obtained in a given study will be indicative of those in the underlying population. P-values and 95% confidence intervals are common measures of statistical inference.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this chapter
Cite this chapter
Kestenbaum, B. (2019). Statistical Inference. In: Epidemiology and Biostatistics. Springer, Cham. https://doi.org/10.1007/978-3-319-97433-0_13
Download citation
DOI: https://doi.org/10.1007/978-3-319-97433-0_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-97432-3
Online ISBN: 978-3-319-97433-0
eBook Packages: MedicineMedicine (R0)