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Related Concept Videos

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...
Experimental Designs01:16

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An experimental design is a systematic process that allows researchers to evaluate the relationship between dependent and independent variables. There are three widely used types of experimental design - pre-experimental design, true experimental design, and quasi-experimental design. In pre-experimental design, the researcher compares the data before and after some interventions or treatments. The true-experimental design has more than one purposefully created group, a commonly measured...
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Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data

Statistical inference techniques, paramount in hypothesis testing, differentiate into two broad categories: parametric and nonparametric statistics.
Parametric statistics, as the name suggests, assumes that data follow a specific distribution, often a normal distribution. This assumption enables robust hypothesis testing and estimation. Parametric methods, like the Student's t-test or Goodness-of-fit test, are frequently employed in biostatistics due to their robustness. For instance, comparing...
Null and Alternative Hypotheses01:16

Null and Alternative Hypotheses

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Confirmation Biases01:31

Confirmation Biases

The confirmation bias is the tendency to focus on information that confirms our existing beliefs and ignore information that is inconsistent with our expectations. For example, if you think that your professor is not very nice, you notice all of the instances of rude behavior exhibited by the professor while ignoring the countless pleasant interactions he is involved in on a daily basis. Have you ever fallen prey to the confirmation bias, either as the source or target of such bias?
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Correspondence bias, also referred to as the fundamental attribution error, describes the tendency to attribute another person’s behavior to internal characteristics rather than situational influences. This cognitive bias leads individuals to overlook external factors that may be influencing actions, thereby fostering potentially inaccurate assessments of others’ intentions and dispositions.Empirical Evidence for Correspondence BiasResearch has consistently demonstrated the prevalence of...

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Problem-Solving Before Instruction (PS-I): A Protocol for Assessment and Intervention in Students with Different Abilities
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The strong-inference protocol: not just for grant proposals.

Sara M Hiebert1

  • 1Department of Biology, Swarthmore College, Swarthmore, Pennsylvania 19081-1390, USA. shieber1@swarthmore.edu

Advances in Physiology Education
|March 1, 2007
PubMed
Summary

The strong-inference protocol enhances scientific research by requiring explicit statements of experimental outcomes and their interpretations. This method improves experimental planning, design efficiency, and statistical analysis power for students.

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Area of Science:

  • Scientific methodology
  • Experimental design
  • Undergraduate education

Background:

  • Platt's strong-inference method is a foundational concept in scientific research.
  • Undergraduate lab protocols often lack rigorous planning and outcome prediction.
  • Current protocols may focus on procedural steps rather than inferential logic.

Purpose of the Study:

  • To introduce and illustrate the strong-inference protocol for undergraduate laboratory courses.
  • To emphasize the importance of predicting experimental outcomes and their interpretations.
  • To enhance the scientific rigor of student-led research projects.

Main Methods:

  • Developing a strong-inference protocol template.
  • Incorporating explicit statements of possible experimental outcomes.
  • Defining a priori predictions and statistical analysis plans.
  • Using a sample experiment on chicken embryo temperature-metabolism relations.

Main Results:

  • The strong-inference protocol promotes thorough experimental planning.
  • It enhances the efficiency and statistical power of experimental designs.
  • Explicitly stating predictions and analysis methods increases research clarity.

Conclusions:

  • The strong-inference protocol is a valuable tool for improving undergraduate scientific training.
  • Implementing this protocol can lead to more robust and insightful experimental work.
  • Instructors are encouraged to adopt this method to foster critical thinking in students.