Related Experiment Video

Updated: Aug 15, 2026

Split-Ubiquitin Based Membrane Yeast Two-Hybrid (MYTH) System: A Powerful Tool For Identifying Protein-Protein Interactions
14:04

Split-Ubiquitin Based Membrane Yeast Two-Hybrid (MYTH) System: A Powerful Tool For Identifying Protein-Protein Interactions

Published on: February 1, 2010

How to write up a hypothesis: the good, the bad and the ugly

William Bains

    Medical Hypotheses
    |February 8, 2005
    PubMed

    More Related Videos

    Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations09:07

    Experimental Research Examining How People Can Cope with Uncertainty Through Soft Haptic Sensations

    Published on: September 16, 2015

    Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems05:47

    Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems

    Published on: June 13, 2025

    Related Concept Videos

    What is a Hypothesis?01:14

    What is a Hypothesis?

    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 statement. It...
    Null and Alternative Hypotheses01:16

    Null and Alternative Hypotheses

    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 population that is...
    Types of Hypothesis Testing01:11

    Types of Hypothesis Testing

    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 ≠ 0.5.
    Hypothesis: Accept or Fail to Reject?01:17

    Hypothesis: Accept or Fail to Reject?

    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 hypothesis and 'fail to...
    Statistical Hypothesis Testing01:16

    Statistical Hypothesis Testing

    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...
    Accuracy and Errors in Hypothesis Testing01:13

    Accuracy and Errors in Hypothesis Testing

    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% chance...