Related Experiment Video
Updated: Jul 16, 2026

Problem-Solving Before Instruction (PS-I): A Protocol for Assessment and Intervention in Students with Different Abilities
Published on: September 11, 2021
The strong-inference protocol: not just for grant proposals
1Department of Biology, Swarthmore College, Swarthmore, Pennsylvania 19081-1390, USA. shieber1@swarthmore.edu
Abstract:
The strong-inference protocol puts into action the important concepts in Platt's often-assigned, classic paper on the strong-inference method (10). Yet, perhaps because students are frequently performing experiments with known outcomes, the protocols they write as undergraduates are usually little more than step-by-step instructions for performing the experiment. The strong-inference protocol, however, includes an explicit statement of possible experimental outcomes and the interpretation that would follow from each. This approach encourages thorough planning, enhances the efficiency of experimental designs, and increases the power of statistical analysis by explicitly stating a priori predictions as well as the statistical methods that will be used to test them. A sample protocol for an experiment investigating temperature-metabolism relations in chicken embryos is provided to illustrate the important components of the strong-inference protocol and to encourage instructors to incorporate this powerful research tool into undergraduate laboratory courses.
Related Concept Videos
Hypothesis: Accept or Fail to Reject?
There are two ways to indicate that the null hypothesis is not rejected. 'Accept' the null hypothesis and 'fail to...
Experimental Designs
Statistical Inference Techniques in Hypothesis Testing: Parametric Versus Nonparametric Data
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 Hypotheses
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...
Confirmation Biases
Correspondence Bias

