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Related Concept Videos

Ranks01:02

Ranks

297
Unlike parametric methods, nonparametric statistics are ideal for nominal and ordinal data, requiring fewer assumptions about the population's nature or distribution. This makes nonparametric methods easier to apply and interpret, as they do not depend on parameters like mean or standard deviation. One common approach in nonparametric analysis is to sort data according to a specific criterion. For instance, we might arrange weather data from hottest to coldest days in a month or rank cities...
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Ordinal Level of Measurement00:55

Ordinal Level of Measurement

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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. For analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using an ordinal scale are similar to nominal scale data, but there is one major difference. The ordinal scale data can be ordered. An example of ordinal scale data is a list of the top five national parks...
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Group Design02:01

Group Design

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The most basic experimental design involves two groups: the experimental group and the control group. The two groups are designed to be the same except for one difference— experimental manipulation. The experimental group gets the experimental manipulation—that is, the treatment or variable being tested—and the control group does not. Since experimental manipulation is the only difference between the experimental and control groups, we can be sure that any differences between...
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Wald-Wolfowitz Runs Test I01:17

Wald-Wolfowitz Runs Test I

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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...
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How Data are Classified: Categorical Data01:11

How Data are Classified: Categorical Data

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A variable, usually notated by capital letters such as X and Y, is a characteristic or measurement that can be determined for each member of a population. Data are the actual values of variables. They may be numbers, or they may be words. Datum is a single value.
Data are classified based on whether they are measurable or not. Categorical data cannot be measured; instead, it can be divided into categories. For example, if Y denotes a person's party affiliation, some examples of Y include...
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Naming Enantiomers02:21

Naming Enantiomers

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The naming of enantiomers employs the Cahn–Ingold–Prelog rules that involve assigning priorities to different substituent groups at a chiral center. Each enantiomer, being a distinct molecule, is assigned a unique name by the Cahn–Ingold–Prelog (CIP) rules, also called the R–S system. The prefix R- or S- attached to the chiral centers in an enantiomer is dependent on the spatial arrangement of the four substituents on the chiral center. The R–S system...
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Comparing the Frequency Effect Between the Lexical Decision and Naming Tasks in Chinese
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ORDERED VERSUS UNORDERED CHARACTERS

Mark Wilkinson1

  • 1Department of Geology, University of Bristol, Bristol BS8 1RJ, UK.

Cladistics : the International Journal of the Willi Hennig Society
|December 21, 2021
PubMed
Summary

No abstract available in PubMed .

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