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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

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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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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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The Availability Heuristic01:08

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A heuristic is a general problem-solving framework (Tversky & Kahneman, 1974). You can think of these as mental shortcuts that are used to solve problems. Different types of heuristics are used in different types of situations, and the impulse to use a heuristic occurs when one of five conditions is met (Pratkanis, 1989):
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Hindsight Biases01:12

Hindsight Biases

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Hindsight bias leads you to believe that the event you just experienced was predictable, even though it really wasn’t. In other words, you knew all along that things would turn out the way they did. Can you relate this to the phrase "Hindsight is 20/20" now? 
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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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Related Experiment Video

Updated: Mar 25, 2026

Evidence-based Knowledge Synthesis and Hypothesis Validation: Navigating Biomedical Knowledge Bases via Explainable AI and Agentic Systems
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Explicit Assumptions About Knowing.

Marie Flannery1

  • 1University of Rochester Medical Center.

Oncology Nursing Forum
|February 25, 2016
PubMed
Summary
This summary is machine-generated.

This column introduces conceptual frameworks, explaining their importance in oncology nursing research and practice. Understanding these foundational elements is key for advancing evidence-based care.

Keywords:
conceptframeworkmodeloncologytheory

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Area of Science:

  • Nursing Science
  • Research Methodology

Background:

  • Conceptual frameworks are essential for structuring and guiding research and practice in oncology nursing.
  • A clear understanding of these frameworks enhances the rigor and impact of nursing initiatives.

Purpose of the Study:

  • To define conceptual frameworks and related terminology.
  • To elucidate the role of conceptual frameworks within the research process.
  • To emphasize the significance of conceptual frameworks in oncology nursing.

Main Methods:

  • This column provides a foundational overview and conceptual analysis.
  • It synthesizes existing knowledge on conceptual frameworks in nursing.

Main Results:

  • Conceptual frameworks provide essential structure for oncology nursing research and practice.
  • Understanding these frameworks is crucial for developing and implementing evidence-based interventions.

Conclusions:

  • Conceptual frameworks are fundamental to advancing oncology nursing science and improving patient care.
  • This column serves as an introduction to their critical role and application.