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Measures of Central Tendency

Measures of Central Tendency

The "center" of a data set is also a way of describing location. The two most widely used measures of the "center" of the data are the mean (average) and the median. The words "mean" and "average" are often used interchangeably. The substitution of one word for the other is common practice. The technical term is "arithmetic mean" and "average" is technically a center location. However, in practice among non-statisticians, "average" is commonly accepted for "arithmetic mean."

Measurement of Bioavailability: Pharmacodynamic Methods

Measurement of Bioavailability: Pharmacodynamic Methods

Pharmacodynamic methods provide insights into a drug's effects on physiological processes over time and play a crucial role in understanding bioavailability and therapeutic efficacy. These methods can be broadly classified into acute pharmacological and therapeutic response approaches, each with distinct mechanisms and applications.The acute pharmacological response method directly correlates a drug's physiological effects, such as ECG or pupil diameter changes, to its time course in the body.

Measurement of Bioavailability: Pharmacokinetic Methods

Measurement of Bioavailability: Pharmacokinetic Methods

Pharmacokinetics is a vital branch of pharmacology that examines how drugs are absorbed, distributed, metabolized, and excreted by the body. Two key methodologies in pharmacokinetics are plasma drug concentration studies and urinary drug excretion analyses, both of which provide critical insights into a drug's therapeutic efficacy and bioavailability.Plasma Drug Concentration-Time StudiesPlasma drug concentration-time studies involve analyzing blood samples at specific intervals to quantify...

Titrimetric Methods: Types and Commonly Used Strategies

Titrimetric Methods: Types and Commonly Used Strategies

In chemistry, titrimetric methods are broadly classified into three types: volumetric, gravimetric, and coulometric. Volumetric titrations involve measuring the volume of a titrant of known concentration that is required to react completely with an analyte. In gravimetric titrations, the standard solution reacts with the analyte to form an insoluble precipitate, which is filtered, dried, and weighed. In coulometric titrations, current is applied to an electrochemical reaction until the reaction...

Trimmed Mean

Trimmed Mean

While measuring the mean of a data set, care needs to be taken when associating the mean to its central tendency. The same goes for the arithmetic mean, the geometric mean, or the harmonic mean. This is because the presence of a single outlier data value can significantly affect the mean. That is, the mean is sensitive to fluctuations in the data set.
Although certain measures of central tendency are not sensitive to outliers, there are alternative versions of the mean that get around the...

Statistical Analysis: Overview

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When we take repeated measurements on the same or replicated samples, we will observe inconsistencies in the magnitude. These inconsistencies are called errors. To categorize and characterize these results and their errors, the researcher can use statistical analysis to determine the quality of the measurements and/or suitability of the methods.
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Related Experiment Video

Updated: May 31, 2026

Rapid Analysis and Exploration of Fluorescence Microscopy Images

Rapid Analysis and Exploration of Fluorescence Microscopy Images

Published on: March 19, 2014

The PhenX Toolkit: get the most from your measures.

Carol M Hamilton¹, Lisa C Strader, Joseph G Pratt

¹RTI International, Research Triangle Park, North Carolina 27709, USA. chamilton@rti.org

American Journal of Epidemiology

|July 14, 2011

Summary

The PhenX Toolkit offers standardized measures for large-scale genomic studies, enhancing data comparison and replication. This promotes powerful discovery of genetic variants linked to complex diseases and interactions.

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Area of Science:

Genomics
Biostatistics
Biomedical Research

Background:

Genome-wide association studies (GWAS) require comparable data for robust genetic variation analysis.
Cross-study data comparison is crucial for validating findings in complex disease research.

Purpose of the Study:

To establish a core set of high-priority, standardized measures for phenotypes and exposures.
To facilitate data harmonization and cross-study comparisons in large-scale genomic research.

Main Methods:

A consensus process involving domain experts and scientific community input.
Identification of 15 high-priority measures across 21 research domains.
Development and free dissemination of measures via the PhenX Toolkit.

Main Results:

The PhenX Toolkit provides a curated collection of well-established, low-burden measures.
Measures are designed for broad applicability in large-scale genomic studies.
Resources for data harmonization with legacy data are included.

Conclusions:

Widespread adoption of PhenX measures will increase statistical power for variant discovery and replication.
Standardized measures are essential for advancing research on complex diseases and gene-environment interactions.
Integrating PhenX measures early in experimental design maximizes their impact.