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Related Concept Videos

Types of Hypothesis Testing01:11

Types of Hypothesis Testing

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There are three types of hypothesis tests: right-tailed, left-tailed, and two-tailed.
When the null and alternative hypotheses are stated, it is observed that the null hypothesis is a neutral statement against which the alternative hypothesis is tested. The alternative hypothesis is a claim that instead has a certain direction. If the null hypothesis claims that p = 0.5, the alternative hypothesis would be an opposing statement to this and can be put either p > 0.5, p < 0.5, or p...
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Errors In Hypothesis Tests01:14

Errors In Hypothesis Tests

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When performing a hypothesis test, there are four possible outcomes depending on the actual truth (or falseness) of the null hypothesis and the decision to reject or not.
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Statistical Hypothesis Testing01:16

Statistical Hypothesis Testing

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Hypothesis testing is a critical statistical procedure facilitating informed, evidence-based decisions. It begins with a hypothesis, which is a tentative explanation, or a prediction about a population parameter. This hypothesis can be either a null hypothesis (H0), indicating no effect or difference, or an alternative hypothesis (Ha), suggesting an effect or difference.
Statistical significance measures the probability that an observed result occurred by chance. If this probability, known as...
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Evolutionary Relationships07:32

Evolutionary Relationships

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Forming an Evolutionary Hypothesis
ExpandNOTE: A cladogram is an important tool for forming an evolutionary hypothesis. A cladogram is a tree-shaped chart used to depict the hypothetical genealogical relationships between species. The tips or leaves of the chart represent specific species and the branches of the tree are different lengths. The different lengths represent the degree of change between each of the species. The common ancestor of all of the species that a specific line branches...
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What is Evolutionary History?02:35

What is Evolutionary History?

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Scientists record evolutionary history by analyzing fossil, morphological, and genetic data. The fossil record documents the history of life on Earth and provides evidence for evolution. However, both fossil and living organisms offer evidence that outlines Earth’s evolutionary history.
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Accuracy and Errors in Hypothesis Testing01:13

Accuracy and Errors in Hypothesis Testing

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Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
In hypothesis testing, the probability of making a Type I error, denoted as α, is commonly set at 0.05. This significance level indicates a 5%...
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Evolutionary Relationships: Using BLAST to Test Evolutionary Hypotheses - Procedure
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HyPhy 2.5-A Customizable Platform for Evolutionary Hypothesis Testing Using Phylogenies.

Sergei L Kosakovsky Pond1, Art F Y Poon2, Ryan Velazquez1

  • 1Institute for Genomics and Evolutionary Medicine, Temple University, Philadelphia, PA.

Molecular Biology and Evolution
|September 11, 2019
PubMed
Summary
This summary is machine-generated.

Hypothesis testing using Phylogenies (HyPhy) is an open-source package for evolutionary model fitting and hypothesis testing. The 2.5 release offers enhanced performance, new models, and improved usability for evolutionary analyses.

Keywords:
evolutionary analysishypothesis testingnatural selectionsoftware engineeringstatistical inference

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Related Experiment Videos

Last Updated: Jan 19, 2026

Evolutionary Relationships: Using BLAST to Test Evolutionary Hypotheses - Procedure
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Area of Science:

  • Evolutionary biology
  • Computational biology
  • Bioinformatics

Background:

  • Phylogenetic analysis is crucial for understanding evolutionary processes.
  • Existing tools for evolutionary modeling and hypothesis testing have limitations.
  • The Hypothesis testing using Phylogenies (HyPhy) package is widely used in evolutionary research.

Purpose of the Study:

  • To introduce the HyPhy 2.5 release, highlighting its re-engineered core and new features.
  • To provide an enhanced platform for fitting evolutionary models and conducting statistical tests.
  • To improve the performance, usability, and extensibility of the HyPhy package.

Main Methods:

  • Utilizes a scriptable, open-source package for fitting evolutionary models to multiple sequence alignments.
  • Employs maximum likelihood statistical framework for parameter estimation and hypothesis testing.
  • Incorporates a re-engineered computational core and analysis library in the 2.5 release.

Main Results:

  • The 2.5 release offers substantial performance and stability enhancements.
  • New classes of evolutionary models and statistical tests have been introduced.
  • Usability has been improved, streamlining analysis workflows and facilitating custom analyses.

Conclusions:

  • HyPhy 2.5 provides a powerful and versatile platform for evolutionary research.
  • The enhancements in HyPhy 2.5 support a broader range of evolutionary analyses, including selection, rates, recombination, and coevolution.
  • The package remains largely backward compatible, ensuring accessibility for existing users.