Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

Wald-Wolfowitz Runs Test I01:17

Wald-Wolfowitz Runs Test I

1.0K
The Wald-Wolfowitz test, also known as the runs test, is a nonparametric statistical test used to assess the randomness of a sequence of two different types of elements (e.g., positive/negative values, successes/failures). It examines whether the order of the elements in a sequence is random or if there is a pattern or trend present. This nonparametric test applies to any ordered data despite the population and sample data distribution, even if a higher sample size is available.
The test works...
1.0K
Wald-Wolfowitz Runs Test II01:17

Wald-Wolfowitz Runs Test II

641
The Wald-Wolfowitz runs test, commonly referred to as the runs test, is a nonparametric test used to assess the randomness of ordered data. The test evaluates the number of runs, which are consecutive sequences of similar elements within the data. If the number of runs is significantly higher or lower than expected, the data is considered non-random, indicating a detectable pattern or structure.
For binary data, runs are identified using symbols such as + and −, or equivalently, 1s and 0s. In...
641
Statistical Hypothesis Testing01:16

Statistical Hypothesis Testing

7.1K
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.
Statistical significance measures the probability that an observed result occurred by chance. If this probability, known as...
7.1K
Randomized Experiments01:13

Randomized Experiments

9.3K
The randomization process involves assigning study participants randomly to experimental or control groups based on their probability of being equally assigned. Randomization is meant to eliminate selection bias and balance known and unknown confounding factors so that the control group is similar to the treatment group as much as possible. A computer program and a random number generator can be used to assign participants to groups in a way that minimizes bias.
Simple randomization
Simple...
9.3K
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

8.8K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
8.8K
Random and Systematic Errors01:20

Random and Systematic Errors

16.0K
Scientists always try their best to record measurements with the utmost accuracy and precision. However, sometimes errors do occur. These errors can be random or systematic. Random errors are observed due to the inconsistency or fluctuation in the measurement process, or variations in the quantity itself that is being measured. Such errors fluctuate from being greater than or less than the true value in repeated measurements. Consider a scientist measuring the length of an earthworm using a...
16.0K

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

Dataset for analyzing and modelling the eutrophication processes in groundwater-coastal lagoon systems: The La Pletera lagoons case study (NE Spain).

Data in brief·2023
Same author

Nitrogen in surface aquifer - Coastal lagoons systems: Analyzing the origin of eutrophication processes.

The Science of the total environment·2023
Same author

Two Wrongs May Not Make a Right.

Multivariate behavioral research·2016
Same author

Two Wrongs Still Do Not Make a Right.

Multivariate behavioral research·2016
Same author

Some Mathematical Relationships Between Three-Mode Component Analysis and Stationary Component Analysis.

Multivariate behavioral research·2016
Same author

Statistical Evidence in Salary Discrimination Studies: Nonparametric Inferential Conditions.

Multivariate behavioral research·2016
Same journal

Bayesian Machine Learning Tools for Alcohol Use Disorder Research: The bpaup R Package.

Multivariate behavioral research·2026
Same journal

A Unified Framework for Jointly modelling Response Times and Item Position Effects in Computer-Based Learning Assessments.

Multivariate behavioral research·2026
Same journal

Generalizability Theory Applied to Daily Relationship Quality: Substantive and Statistical Directions.

Multivariate behavioral research·2026
Same journal

A Modularized Higher-Order Diagnostic Classification Model for Clustered Attribute Hierarchies.

Multivariate behavioral research·2026
Same journal

Generalizing Causal Effects to a Target Population Without Individual-Level Data from the Target Population.

Multivariate behavioral research·2026
Same journal

betaselectr: Selective (and Proper) Standardization in Structural Equation Models.

Multivariate behavioral research·2026
See all related articles

Related Experiment Video

Updated: Mar 26, 2026

A Behavioral Test Battery for the Repeated Assessment of Motor Skills, Mood, and Cognition in Mice
07:18

A Behavioral Test Battery for the Repeated Assessment of Motor Skills, Mood, and Cognition in Mice

Published on: March 2, 2019

20.2K

A Stochastic Model For Repeated Testing.

J F Vinsonhaler, W Meredith

    Multivariate Behavioral Research
    |January 29, 2016
    PubMed
    Summary
    This summary is machine-generated.

    This study extends probability models for mental testing to account for practice effects. It introduces a stochastic process approach to model repeated item responses, enhancing assessment accuracy.

    More Related Videos

    Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats
    08:06

    Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats

    Published on: June 18, 2018

    7.7K
    Author Spotlight: Establishing a Rodent Model for Investigating Depression Factors in Traditional Mongolian Medicine
    05:56

    Author Spotlight: Establishing a Rodent Model for Investigating Depression Factors in Traditional Mongolian Medicine

    Published on: October 27, 2023

    2.0K

    Related Experiment Videos

    Last Updated: Mar 26, 2026

    A Behavioral Test Battery for the Repeated Assessment of Motor Skills, Mood, and Cognition in Mice
    07:18

    A Behavioral Test Battery for the Repeated Assessment of Motor Skills, Mood, and Cognition in Mice

    Published on: March 2, 2019

    20.2K
    Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats
    08:06

    Testing for Metacognitive Responding Using an Odor-based Delayed Match-to-Sample Test in Rats

    Published on: June 18, 2018

    7.7K
    Author Spotlight: Establishing a Rodent Model for Investigating Depression Factors in Traditional Mongolian Medicine
    05:56

    Author Spotlight: Establishing a Rodent Model for Investigating Depression Factors in Traditional Mongolian Medicine

    Published on: October 27, 2023

    2.0K

    Area of Science:

    • Psychometrics
    • Cognitive Psychology
    • Statistical Modeling

    Background:

    • Current probability models in mental testing do not fully account for practice effects.
    • Repeated exposure to test items can influence subsequent performance.
    • Understanding these effects is crucial for accurate ability assessment.

    Purpose of the Study:

    • To extend existing probability models of mental testing.
    • To incorporate the impact of practice effects in ability testing.
    • To develop a robust model for analyzing repeated test item responses.

    Main Methods:

    • Treating multiple presentations of the same item as a stochastic process.
    • Utilizing latent class models and linear operator learning models.
    • Developing methods for parameter estimation and goodness-of-fit testing.

    Main Results:

    • A novel model is proposed to quantify practice effects in mental testing.
    • The model integrates stochastic processes with latent class and linear operator learning.
    • Numerical examples demonstrate the application and validity of the proposed methods.

    Conclusions:

    • The extended probability models provide a more accurate representation of ability when practice effects are present.
    • The stochastic process approach offers a flexible framework for analyzing repeated measures in testing.
    • The proposed methods enhance the precision of ability estimation in longitudinal assessments.