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Related Concept Videos

Sample Size Calculation01:19

Sample Size Calculation

6.7K
Knowledge of the sample size is the first requirement to conduct random sampling or an experiment. The sample size is the total number of units, observations, or groups (in some cases) used to get the data to estimate a population parameter. As the name suggests, the sample size is that of the sample drawn from the population and differs from the population size.
The sample size for the given experiment or sampling effort is fundamental to any study design. Sample size decides the number of...
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One-Way ANOVA: Unequal Sample Sizes01:15

One-Way ANOVA: Unequal Sample Sizes

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One-way ANOVA can be performed on three or more samples of unequal sizes. However, calculations get complicated when sample sizes are not always the same. So, while performing ANOVA with unequal samples size, the following equation is used:
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One-Way ANOVA: Equal Sample Sizes01:15

One-Way ANOVA: Equal Sample Sizes

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One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
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Weighted Mean00:57

Weighted Mean

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While taking the arithmetic, geometric, or harmonic mean of a sample data set, equal importance is assigned to all the data points. However, all the values may not always be equally important in some data sets. An intrinsic bias might make it more important to give more weightage to specific values over others.
For example, consider the number of goals scored in the matches of a tournament. While computing the average number of goals scored in the tournament, it may be more important to...
6.4K
Curvilinear Motion: Rectangular Components01:23

Curvilinear Motion: Rectangular Components

1.3K
Curvilinear motion characterizes the movement of a particle or object along a curved path, notably evident when envisioning a car navigating a winding road. If the car starts at point A, its position vector is established within a fixed frame of reference, where the ratio of the position vector to its magnitude signifies the unit vector pointing in the position vector's direction.
As the car advances, its position evolves over time. Quantifying the car's velocity involves computing the...
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Curvilinear Motion: Polar Coordinates01:27

Curvilinear Motion: Polar Coordinates

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In polar coordinates, the motion of a particle follows a curvilinear path. The radial coordinate symbolized as 'r,' extends outward from a fixed origin to the particle, while the angular coordinate, 'θ,' measured in radians, represents the counterclockwise angle between a fixed reference line and the radial line connecting the origin to the particle.
The particle's location is described using a unit vector along the radial direction. Deriving the particle's position...
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Sample representativeness affects whether judgments are influenced by base rate or sample size.

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Related Experiment Video

Updated: Feb 8, 2026

Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging
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Co-analysis of Brain Structure and Function using fMRI and Diffusion-weighted Imaging

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Sample size weighting follows a curvilinear function.

Natalie A Obrecht1

  • 1William Paterson University.

Journal of Experimental Psychology. Learning, Memory, and Cognition
|July 10, 2018
PubMed
Summary

Laypeople

Area of Science:

  • Cognitive Psychology
  • Decision Making
  • Statistical Reasoning

Background:

  • Previous research on laypeople's sensitivity to sample size yields mixed results.
  • Discrepancies may stem from sample size sensitivity not being linear but curvilinear.

Purpose of the Study:

  • To propose and test a curvilinear function for sample size sensitivity.
  • To reconcile conflicting findings in the literature regarding sample size neglect.

Main Methods:

  • Analysis of existing literature and theoretical arguments.
  • Examination of confidence and estimation tasks with varying normative standards (square-root and linear).

Main Results:

  • Sample size sensitivity follows a curvilinear pattern, diminishing as sample size increases.

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  • This pattern holds across different task types and normative standards.
  • Higher numeracy correlates with greater, yet still insufficient, sample size sensitivity.
  • Presenting raw data improves sample size utilization in lower numeracy individuals.

    • Conclusions:

    • Laypeople's weighting of sample size is context-dependent and non-linear.
    • Intuitive understanding of sample size benefits does not translate to consistent application.
    • Interventions like providing raw data can mitigate biases for certain groups.