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Related Concept Videos

Numerical Calculations01:24

Numerical Calculations

In engineering applications, the representation of the numerical value is critical. Presenting or reporting the answer is one of the essential parts of engineering practices. Numerical calculations are performed using handheld calculators or computers since numerically accurate answers are always preferred.
The solution to a problem is obtained using different methods. While manually solving algebraic symbols is one of the most common methods, the graphical method is often preferred. Computers...
How Data are Classified: Numerical Data00:59

How Data are Classified: Numerical Data

Data that are countable or measurable in specific units are called numerical or quantitative data. Quantitative data are always numbers. Quantitative data are the result of counting or measuring the attributes of a population. Amount of money, pulse rate, weight, number of people living in a town, and number of students who opt for statistics are examples of quantitative data.
Quantitative data may be either discrete or continuous. All quantitative data that take on only specific numerical...
Significant Figures in Calculations00:58

Significant Figures in Calculations

Uncertainty in measurements can be avoided by reporting the results of a calculation with the correct number of significant figures. This can be determined by the following rules for rounding numbers:
Nominal Level of Measurement00:56

Nominal Level of Measurement

The way a set of data is measured is called its level of measurement. Correct statistical procedures depend on a researcher being familiar with levels of measurement. Not every statistical operation can be used with every set of data. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
The data that cannot be measured but can be grouped into categories fall under the nominal level of measurement. Data that is measured using a nominal scale is...
Regression Toward the Mean01:52

Regression Toward the Mean

Regression toward the mean (“RTM”) is a phenomenon in which extremely high or low values—for example, and individual’s blood pressure at a particular moment—appear closer to a group’s average upon remeasuring. Although this statistical peculiarity is the result of random error and chance, it has been problematic across various medical, scientific, financial and psychological applications. In particular, RTM, if not taken into account, can interfere when researchers try to extrapolate results...
5-Number Summary01:04

5-Number Summary

In a dataset, the 5-number summary includes the minimum data value, the data value of the first quartile, the median data value or data value of the second quartile, the data value of the third quartile, and the maximum data value. These 5 data values can be visualized as a box and whisker plot.
In a box plot, the minimum and maximum data values represent the lower and upper whiskers in the graph, and the median is designated as the center of the box in the chart. The first quartile and third...

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Related Experiment Video

Updated: Jun 18, 2026

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)
10:58

Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)

Published on: August 28, 2021

Living by the numbers.

Michael B Yaffe

    Science Signaling
    |December 3, 2009
    PubMed
    Summary
    This summary is machine-generated.

    Journal impact scores undermine scientific progress by devaluing individual research. Articles should be judged by their own merit, not by journal rankings, to foster innovation.

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    Last Updated: Jun 18, 2026

    Multimedia Battery for Assessment of Cognitive and Basic Skills in Mathematics (BM-PROMA)
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    Published on: August 28, 2021

    Optimization of Processing of Tiebangchui with Highland Barley Wine Based on the Box-Behnken Design Combined with the Entropy Method
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    Optimization of Processing of Tiebangchui with Highland Barley Wine Based on the Box-Behnken Design Combined with the Entropy Method

    Published on: May 19, 2023

    Area of Science:

    • Bibliometrics
    • Scientific Publishing
    • Research Evaluation

    Background:

    • Journal impact factors are widely used to assess research quality.
    • This practice can inadvertently discourage high-risk, high-reward research.

    Discussion:

    • Evaluating scientific articles based on journal metrics rather than intrinsic merit is detrimental.
    • This system mirrors flawed approaches in rating medical care, potentially stifling scientific advancement.

    Key Insights:

    • Article worth should be determined by its own impact and contribution.
    • Over-reliance on journal scores can misdirect research efforts away from critical, complex problems.

    Outlook:

    • Promoting a shift towards article-level evaluation is crucial for a healthy scientific ecosystem.
    • Future research assessment should prioritize the substance and influence of individual publications.