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Related Concept Videos

Sampling Plans01:23

Sampling Plans

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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...
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Random Sampling Method01:09

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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...
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Convenience Sampling Method00:55

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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.
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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.
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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...
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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...
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A NOTE ON THE EFFECT OF SELECTIVE SAMPLING PROCEDURES ON THE PHI COEFFICIENT.

J W Holley, U Eriksson

    Multivariate Behavioral Research
    |January 31, 2016
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    Summary
    This summary is machine-generated.

    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.

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    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.