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Related Concept Videos

Interpretation of Confidence Intervals01:19

Interpretation of Confidence Intervals

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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...
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Confidence Coefficient01:24

Confidence Coefficient

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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...
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Confidence Intervals01:21

Confidence Intervals

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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...
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Design Consideration01:22

Design Consideration

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Designing a structure involves a series of considerations, primarily the material's ultimate strength, calculated through tests that measure changes under increased force until the material reaches its breaking point or limit. The ultimate load, where the material breaks, is divided by its original cross-sectional area, resulting in the ultimate normal stress or strength. The ultimate shearing stress is another significant factor taken into account.
The factor of safety is another key...
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Uncertainty: Confidence Intervals00:54

Uncertainty: Confidence Intervals

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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...
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Design Example: Managing Concrete Workability01:14

Design Example: Managing Concrete Workability

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This example deals with managing the workability of concrete for a raft foundation project under hot weather conditions. Workability is crucial for ensuring the concrete is easy to place, compact, and finish. In this scenario, a slump test — a common method to measure the workability of fresh concrete — initially indicated low workability. This was attributed to the rapid water loss from the concrete mix, exacerbated by the high temperatures causing the course aggregates to heat up.
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Embracing the Value of Confidence and Intention in Program Design.

Karen S Reed

    Journal of Continuing Education in Nursing
    |December 29, 2020
    PubMed
    Summary

    Continuing education programs can be more effective when using active learning strategies. These methods boost participants' confidence and intention to apply new knowledge and skills learned in nursing education.

    Area of Science:

    • Nursing Education
    • Adult Learning Theory

    Background:

    • Continuing education is vital for healthcare professionals.
    • Assessing learning effectiveness requires evaluating participant confidence and intention.
    • Traditional methods may not fully engage adult learners.

    Purpose of the Study:

    • To evaluate the impact of active learning strategies on participant confidence and intention.
    • To provide insights into effective continuing education methodologies in nursing.
    • To analyze learner outcomes in professional development programs.

    Main Methods:

    • Analysis of participant confidence and intention levels.
    • Comparison of outcomes from two continuing education programs.
    • Implementation and assessment of active learning strategies.

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    Main Results:

    • Active learning strategies positively influenced participant confidence.
    • Learner intention to apply new skills significantly increased.
    • Demonstrated a measurable impact of specific teaching methodologies.

    Conclusions:

    • Active learning is an effective strategy for enhancing continuing nursing education.
    • Increased confidence and intention correlate with effective pedagogical approaches.
    • Findings support the integration of active learning in professional development.