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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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Types of Hypothesis Testing01:11

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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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What is a Hypothesis?01:14

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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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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.
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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?
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Qualitative Analysis01:10

Qualitative Analysis

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Qualitative analysis is the process of identifying elements, ions, or compounds in an unknown sample. It is the first and most fundamental type of analysis based on the hierarchy of analytical goals. This hierarchy is significant as it provides a structured approach to scientific research, with qualitative analysis serving as the initial step, providing essential information before moving on to quantitative or other forms of analysis.
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Qualitative hypotheses.

Veli-Matti Karhulahti1

  • 1University of Jyväskylä, Jyväskylä, Central Finland, Finland.

Open Research Europe
|September 2, 2025
PubMed
Summary
This summary is machine-generated.

Qualitative hypotheses (QHs) can disclose researcher expectations without testing. QHs are useful for new reporting formats like preregistrations and registered reports, aiding pre-analytic reflection.

Keywords:
Epistemologymeta-sciencemethodologypreregistrationregistered reports

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Area of Science:

  • Social Sciences
  • Qualitative Research Methodology

Background:

  • Hypotheses are uncommon in qualitative research due to method limitations and epistemological focus on exploration over testing.
  • Qualitative researchers often hold pre-study expectations akin to hypotheses.
  • Disclosing these expectations is valuable for research transparency.

Purpose of the Study:

  • To introduce and discuss the concept of qualitative hypotheses (QHs).
  • To present QHs as a tool for disclosing pre-study expectations in qualitative research.
  • To highlight the utility of QHs within evolving reporting standards.

Main Methods:

  • Conceptual discussion and argumentation.
  • Exploration of the role of expectations in qualitative inquiry.
  • Analysis of the fit between QHs and new reporting formats.

Main Results:

  • Qualitative hypotheses (QHs) offer a framework for articulating researcher expectations prior to data collection.
  • QHs are distinct from traditional hypotheses as they are not intended for testing.
  • The concept of QHs aligns well with emerging practices like preregistration and registered reports.

Conclusions:

  • Qualitative hypotheses (QHs) provide a valuable mechanism for enhancing transparency and reflexivity in qualitative research.
  • Integrating QHs into preregistration and registered reports can strengthen the pre-analytic phase of qualitative studies.
  • The proposed concept of QHs addresses the need to acknowledge and manage researcher expectations within qualitative methodologies.