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Related Concept Videos

Confidence Coefficient01:24

Confidence Coefficient

The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under both the...
Interpretation of Confidence Intervals01:19

Interpretation of Confidence Intervals

A confidence interval is a better estimate of the population than a point estimate, as it uses a range of values from a sample instead of a single value.
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
Confidence Intervals01:21

Confidence Intervals

An unbiased point estimate is often insufficient to predict a population estimate, such as population mean or population proportion. In this scenario, a confidence interval is used. A confidence interval is an estimate similar to a sample proportion. However, unlike the point estimate which is a single value, the confidence interval contains a range of values. These values have lower and upper limits, known as confidence limits, and can be designated as L1 and L2, respectively.
A confidence...
Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor 't,' or...
Theory of Attribution II: Kelley's Covariation Theory01:29

Theory of Attribution II: Kelley's Covariation Theory

Attribution theory plays a crucial role in social psychology, helping to explain how individuals interpret the causes of behavior. One prominent model within this field is Harold Kelley's covariation theory, which provides a systematic approach to determining whether internal traits or external circumstances drive a person's actions. The model posits that individuals rely on three key types of information—consensus, consistency, and distinctiveness—to make these judgments.Consensus: Comparing...
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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Related Experiment Video

Updated: Jun 5, 2026

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

Exploring separable components of institutional confidence.

Joseph A Hamm1, Lisa M PytlikZillig, Alan J Tomkins

  • 1Public Policy Center, 215 Centennial Mall South, Lincoln, NE 68588-0228, U.S.A.

Behavioral Sciences & the Law
|January 26, 2011
PubMed
Summary
This summary is machine-generated.

This study clarifies distinct measures of institutional confidence, finding that dispositional trust, institutional trust, legal obligation, and cynicism are separable yet correlated. These factors uniquely contribute to public confidence in courts, aiding research clarity.

Related Experiment Videos

Last Updated: Jun 5, 2026

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm
06:18

The Collective Trust Game: An Online Group Adaptation of the Trust Game Based on the HoneyComb Paradigm

Published on: October 20, 2022

Area of Science:

  • Social Psychology
  • Criminology
  • Political Science

Background:

  • Institutional confidence research lacks consensus on key constructs like trust and legitimacy.
  • Existing studies often use related but distinct measures, hindering clear interpretation.
  • Understanding these nuances is crucial for social scientific disciplines.

Purpose of the Study:

  • To examine the separability and relationships among four confidence-related constructs: dispositional trust, trust in institutions, obligation to obey the law, and cynicism.
  • To assess the independent contribution of each construct to confidence in the courts.
  • To replicate findings and examine the stability of these constructs over time.

Main Methods:

  • Exploratory factor analyses to assess construct separability.
  • Correlation analyses to examine relationships among constructs.
  • Multiple regression analyses to determine independent contributions to confidence in the courts.

Main Results:

  • The four confidence-related constructs were found to be separable and correlated.
  • Each construct's independent contribution to confidence in the courts varied based on measurement operationalization.
  • Replication confirmed initial findings and demonstrated construct stability over time.

Conclusions:

  • The study supports the distinct yet interrelated nature of key institutional confidence constructs.
  • Findings offer implications for refining measurement strategies in institutional confidence research.
  • Further research directions are suggested for a more robust understanding of public trust in institutions.