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Related Concept Videos

Null and Alternative Hypotheses01:16

Null and Alternative Hypotheses

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The actual hypothesis testing begins by considering two hypotheses. They are termed  the null hypothesis and the alternative hypothesis. These hypotheses contain opposing viewpoints.
The null hypothesis, denoted by H0 is a statement of no difference between the variables—they are not related. This can often be considered the status quo. As  a result if you cannot accept the null, it requires some action.
The alternative hypothesis, denoted by H1 or Ha, is a claim about the...
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Hypothesis: Accept or Fail to Reject?01:17

Hypothesis: Accept or Fail to Reject?

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The outcome of any hypothesis testing leads to rejecting or not rejecting the null hypothesis. This decision is taken based on the analysis of the data, an appropriate test statistic, an appropriate confidence level, the critical values, and P-values. However, when the evidence suggests that the null hypothesis cannot be rejected, is it right to say, 'Accept' the null hypothesis?
There are two ways to indicate that the null hypothesis is not rejected. 'Accept' the null...
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What is a Hypothesis?01:14

What is a Hypothesis?

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A hypothesis can be a simple sentence or statement about a property or any phenomenon observed or predicted for a population. It is usually a claim about a  property of the population. It can be stated for any field observations or experiments. A hypothesis statement cannot be said to be right or wrong as it is merely a statement. It needs to be tested through an elaborate data collection process and an appropriate statistical test. A hypothesis should be a general but not a vague...
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Modeling with Differential Equations01:25

Modeling with Differential Equations

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Population dynamics can be described mathematically by considering the population size P(t) as a function of time. The rate of change of the population is then represented by the derivative of P(t). A simple assumption is that the rate of growth is proportional to the size of the population itself. This leads to an exponential growth model, where the population increases rapidly without bound. While this is a useful first approximation, it does not reflect realistic long-term...
289
Longitudinal Research02:20

Longitudinal Research

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Sometimes we want to see how people change over time, as in studies of human development and lifespan. When we test the same group of individuals repeatedly over an extended period of time, we are conducting longitudinal research. Longitudinal research is a research design in which data-gathering is administered repeatedly over an extended period of time. For example, we may survey a group of individuals about their dietary habits at age 20, retest them a decade later at age 30, and then again...
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Limits to Natural Selection01:38

Limits to Natural Selection

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Organisms that are well-adapted to their environment are more likely to survive and reproduce. However, natural selection does not lead to perfectly adapted organisms. Several factors constrain natural selection.
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Related Experiment Video

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Setting Limits on Supersymmetry Using Simplified Models
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Published on: November 15, 2013

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Hypotheses, limits, models and life.

William Bains1

  • 1Rufus Scientific Ltd., 37 The Moor, Melbourn, Royston, Herts SG8 6ED, UK. bains@mit.edu.

Life (Basel, Switzerland)
|January 1, 2015
PubMed
Summary
This summary is machine-generated.

Life Sciences journal introduces "Hypotheses in the Life Sciences," a new section for rigorously evidenced ideas. This section aims to fill knowledge gaps across all life science disciplines, fostering innovative research and publication.

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Area of Science:

  • Life Sciences
  • Interdisciplinary Research

Background:

  • Existing publication models may not adequately support the dissemination of novel, evidence-based hypotheses.
  • A need exists for a dedicated platform to present well-supported, yet untested, scientific ideas.

Purpose of the Study:

  • To establish a new section in the journal Life, titled "Hypotheses in the Life Sciences."
  • To provide a dedicated venue for the publication of novel hypotheses supported by rigorous evidence and clear argumentation.
  • To stimulate research by addressing genuine gaps in understanding across the life sciences.

Main Methods:

  • Manuscript submission and peer review process tailored for hypothesis-driven research.
  • Inclusion of hypotheses supported by real-world evidence and logical reasoning.
  • Focus on hypotheses that address significant questions in any life science field.

Main Results:

  • Establishment of a new publication venue for scientific hypotheses.
  • Creation of a curated collection of well-supported ideas poised for testing.
  • Facilitation of interdisciplinary scientific discourse and exploration.

Conclusions:

  • The "Hypotheses in the Life Sciences" section will serve as a vital resource for researchers.
  • This initiative is expected to accelerate scientific discovery by bridging the gap between conceptualization and empirical testing.
  • The section aims to foster innovation and advance understanding across the breadth of life science disciplines.