Related Experiment Video
Updated: Mar 26, 2026

10:56
An Unbiased Approach of Sampling TEM Sections in Neuroscience
Published on: April 13, 2019
7.8K
A NOTE ON THE EFFECT OF SELECTIVE SAMPLING PROCEDURES ON THE PHI COEFFICIENT
Multivariate Behavioral Research
|January 31, 2016
Summary
This study introduces a general equation to calculate true population phi from sample data and population splits. A secondary method using the G Index is also presented for non-general solutions.
Area of Science:
- Population genetics
- Statistical modeling
Background:
- Estimating population genetic parameters like phi is crucial for understanding population structure.
- Existing methods may have limitations with arbitrary population splits.
Purpose of the Study:
- To present a general equation for calculating the true population phi.
- To offer a non-general solution using the G Index.
- To demonstrate the application of these methods with hypothetical data.
Main Methods:
- Development of a general equation for population phi estimation.
- Application of the G Index for a non-general solution.
- Use of hypothetical data for validation.
Main Results:
- A comprehensive equation is provided for diverse population split scenarios.
- The G Index offers an alternative estimation method.
- Demonstrations confirm the utility of the presented methods.
Conclusions:
- The general equation provides a robust framework for estimating population phi.
- The G Index serves as a viable alternative for specific cases.
- These methods enhance the toolkit for population genetic analysis.
More Related Videos
Related Concept Videos
Sampling Plans
1.3K
Sampling is a crucial step in analytical chemistry, allowing researchers to collect representative data from a large population. Common sampling methods include random, judgmental, systematic, stratified, and cluster sampling.
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
Random sampling is a method where each member of the population has an equal chance of being selected for the sample. It involves selecting individuals randomly, often using random number generators or lottery-type methods. For example, when analyzing the properties of a...
1.3K
Random Sampling Method
15.7K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population. Because measuring the entire population in a study is not practical, researchers use samples to represent the population of interest. Among the various sampling methods used by...
15.7K
Convenience Sampling Method
12.0K
Sampling is a technique to select a portion (or subset) of the larger population and study that portion (the sample) to gain information about the population. Data are the result of sampling from a population. The sampling method ensures that samples are drawn without bias and accurately represent the population.
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
Convenience sampling is a non-random method of sample selection; this method selects individuals that are easily accessible and may result in biased data. For example, a marketing...
12.0K
One-Way ANOVA: Equal Sample Sizes
4.4K
One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
4.4K
Fisher's Exact Test
1.4K
Fisher's exact test is a statistical significance test widely used to analyze 2x2 contingency tables, particularly in situations where sample sizes are small. Unlike the chi-squared test, which approximates P-values and assumes minimum expected frequencies of at least five in each cell, Fisher's exact test calculates the exact probability (P-value) of observing the data or more extreme results under the null hypothesis. This feature makes it especially valuable when the assumptions of...
1.4K
Sampling Distribution
19.1K
Given simple random samples of size n from a given population with a measured characteristic such as mean, proportion, or standard deviation for each sample, the probability distribution of all the measured characteristics is called a sampling distribution. How much the statistic varies from one sample to another is known as the sampling variability of a statistic. You typically measure the sampling variability of a statistic by its standard error. The standard error of the mean is an example...
19.1K

