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Related Concept Videos

Reliability and Validity01:29

Reliability and Validity

Reliability and validity are two important considerations that must be made with any type of data collection. Reliability refers to the ability to consistently produce a given result. In the context of psychological research, this would mean that any instruments or tools used to collect data do so in consistent, reproducible ways.
Surveys02:16

Surveys

Often, psychologists develop surveys as a means of gathering data. Surveys are lists of questions to be answered by research participants, and can be delivered as paper-and-pencil questionnaires, administered electronically, or conducted verbally. Generally, the survey itself can be completed in a short time, and the ease of administering a survey makes it easy to collect data from a large number of people.
Range Rule of Thumb to Interpret Standard Deviation01:13

Range Rule of Thumb to Interpret Standard Deviation

The range rule of thumb in statistics helps us calculate a dataset's minimum and maximum values with known standard deviation. This rule is based on the concept that 95% of all values in a dataset lie within two standard deviations from the mean.
For instance, the range rule of thumb can be used to find the tallest and the shortest student in a class, given the mean student height and standard deviation. If the mean student height is 1.6 m and the standard deviation, s is 0.05 m, the height of...
Testing a Claim about Standard Deviation01:19

Testing a Claim about Standard Deviation

A complete procedure to test a claim about population standard deviation or population variance is explained here.
The hypothesis testing for the claim of population standard deviation (or variance) requires the data and samples to be random and unbiased. The population distribution also must be normal. There is no specific requirement on the sample size as the estimation is based on the chi-square distribution.
As a first step, the hypothesis (null and alternative) concerning the claim about...
Estimating Population Mean with Unknown Standard Deviation01:22

Estimating Population Mean with Unknown Standard Deviation

In practice, we rarely know the population standard deviation. In the past, when the sample size was large, this did not present a problem to statisticians. They used the sample standard deviation s as an estimate for σ and proceeded as before to calculate a confidence interval with close enough results. However, statisticians ran into problems when the sample size was small. A small sample size caused inaccuracies in the confidence interval.
William S. Gosset (1876–1937) of the Guinness...
Decision Making: Traditional Method01:14

Decision Making: Traditional Method

The process of hypothesis testing based on the traditional method includes calculating the critical value, testing the value of the test statistic using the sample data, and interpreting these values.
First, a specific claim about the population parameter is decided based on the research question and is stated in a simple form. Further, an opposing statement to this claim is also stated. These statements can act as null and alternative hypotheses, out of which a null hypothesis would be a...

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Related Experiment Video

Updated: Jun 27, 2026

Problem-Solving Before Instruction (PS-I): A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction (PS-I): A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

Standard setting in student assessment: is a defensible method yet to come?

A Barman1

  • 1Department of Medical Education,School of Medical Sciences, Universiti Sains Malaysia, Malaysia. barman@kb.usm.my

Annals of the Academy of Medicine, Singapore
|December 17, 2008
PubMed
Summary

Setting assessment standards in medical education is crucial but often subjective. Linking standards to practice requirements and using expert-developed tests enhances validity and reliability.

Related Experiment Videos

Last Updated: Jun 27, 2026

Problem-Solving Before Instruction (PS-I): A Protocol for Assessment and Intervention in Students with Different Abilities
10:26

Problem-Solving Before Instruction (PS-I): A Protocol for Assessment and Intervention in Students with Different Abilities

Published on: September 11, 2021

Area of Science:

  • Medical Education
  • Educational Assessment

Background:

  • Periodic setting, maintenance, and re-evaluation of assessment standards are critical in medical education.
  • Current cut-off score determination methods often lack objectivity, relying on arbitrary percentages or subjective judgments.
  • Existing standard-setting procedures exhibit a high degree of uncertainty and lack universal agreement on the best methods.

Purpose of the Study:

  • To review the validity, reliability, feasibility, and legal issues associated with various standard-setting procedures in educational assessment.
  • To explore methods for establishing credible and defensible performance standards in medical education.

Main Methods:

  • A literature review of published articles by educational assessment researchers focusing on standard-setting issues.
  • Analysis of existing methodologies for determining cut scores on educational tests.

Main Results:

  • No single method for determining cut scores is universally accepted as perfect or best.
  • The legitimacy of a performance standard is strengthened when it is directly linked to the requirements of professional practice.
  • Test-curriculum alignment and content validity are essential components of educational test validity arguments.

Conclusions:

  • Linking test items and pass/fail marks to a representative percentage of essential curriculum learning objectives, identified through practice analysis, can enhance standard credibility.
  • Expert-developed test items, vetted by multidisciplinary faculty, contribute to the reliability of both the test and the established standard.
  • Well-defined standards improve the validity, defensibility, and comparability of assessment outcomes.