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Statistical ideas behind the analysis of experiments related to crop composition and the genetic factors underlying composition are discussed. The emphasis is on concepts rather than statistical formulations. Statistical analysis and biological considerations are shown to be complementary rather than contradictory, in that the statistical analysis of a dataset depends on the experimental design, that no amount of statistical sophistication can rescue a badly designed study, and good experimental design is crucial. The traditional null hypothesis significance testing approach has severe limitations but p values and statistical significance still often seem to be the primary objective of an analysis. Emphasis instead should be on identifying the size of effects that are biologically important and, with the involvement of the "domain" scientist, using these to help design experiments with appropriate sample sizes and statistical power. The issues discussed here are also directly applicable to other areas of research.
This article was published in the following journal.
Name: Journal of agricultural and food chemistry
The use of p-value and statistical significance have been questioned since the early 80s in the last century until today. Much has been discussed about it in the field of statistics and its applicatio...
To illustrate and discuss current and proposed new concepts of effect size quantification and significance, with a focus on statistical and clinical/subjective interpretation and supported by empirica...
Microarrays are a powerful tool for studying differential gene expression. However, lists of many differentially expressed genes are often generated, and unraveling meaningful biological processes fro...
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Psoriasis is a multifactorial cutaneous disorders which affects about 100000 patients in Taiwan. Psoriatic arthritis is also present in about 20~30 percents. Many drugs have been shown to ...
1. Purpose and Objective: To determine the feasibility and short- and long-term efficacy of an empirically-based CST intervention (Keefe et al.) with caregivers of patients with...
Radiation pneumonitis is the most common complication and the major dose-limiting toxicity associated with radiotherapy, which can cause poor quality of life or life-threatening symptoms a...
Introduction: immersion cold water is a recuperative strategy commonly used, however, are not yet fully understood the real effects of this technique on specific conditions. Objective: To ...
To determine the ability of the Cimmunology process to lead to in vitro antibody production, the ability of the ELISA assays to detect any of those antibodies, and to establish the relatio...
Biological systems as affected by time. Aging, biological rhythms, and cyclic phenomena are included. Statistical, computer-aided mathematical procedures are used to describe, in mathematical terminology, various biological functions over time.
A multidisciplinary field of research and practice studying the periodicity of biological systems and the application of principles of chronobiology to various therapeutic strategies. Aging, biological rhythms, and cyclic phenomena are included. Statistical, computer-aided mathematical procedures are used to describe, in mathematical terminology, various biological functions over time.
The use of statistical and mathematical methods to analyze biological observations and phenomena.
Statistical formulations or analyses which, when applied to data and found to fit the data, are then used to verify the assumptions and parameters used in the analysis. Examples of statistical models are the linear model, binomial model, polynomial model, two-parameter model, etc.
Application of statistical procedures to analyze specific observed or assumed facts from a particular study.
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