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Related Concept Videos

Construction of Frequency Distribution01:15

Construction of Frequency Distribution

11.3K
A frequency distribution table can be constructed using the steps given below.
First, make a table with two columns—one with the title of the data that needs to be organized, and the other column for frequency. [Draw a third column for tally marks if needed]. Then, take a look at the items given in the data set and decide if an ungrouped frequency distribution table or a grouped frequency distribution table would be more suitable. If there are large sets of different values, then it is...
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Determination of Expected Frequency01:08

Determination of Expected Frequency

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Suppose one wants to test independence between the two variables of a contingency table. The values in the table constitute the observed frequencies of the dataset. But how does one determine the expected frequency of the dataset? One of the important assumptions is that the two variables are independent, which means the variables do not influence each other. For independent variables, the statistical probability of any event involving both variables is calculated by multiplying the individual...
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Cumulative Frequency Distribution01:04

Cumulative Frequency Distribution

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A cumulative frequency distribution is another type of frequency distribution. Instead of reporting how many data values fall in some classes, it reports how many data values are contained in either that class or any class to its left. Technically, it means the sum of frequencies of the class and all the classes below it in a frequency distribution. A cumulative frequency is calculated by adding the frequency of each class lower than the corresponding class interval or category. In general, a...
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Relative Frequency Distribution00:55

Relative Frequency Distribution

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A relative frequency distribution is the proportion or fraction of times a value occurs in a data set. To find the relative frequencies, one can divide each frequency by the total number of data points in the sample. It is very similar to a regular frequency distribution, except that instead of reporting how many data values fall in a class, a relative frequency distribution reports the fraction of data values that fall in a class. These fractions or proportions are called relative frequencies...
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Relative Frequency Histogram01:14

Relative Frequency Histogram

6.0K
The relative frequency depicts the proportion of data points that have each value. The frequency tells the number of data points that have each value. Like the histogram, a relative frequency histogram also has the same shape with a horizontal scale (the x-axis), but the vertical scale (the y-axis) is marked with relative frequencies (percentages of the whole) instead of actual frequencies. A relative frequency histogram is a graphical representation of a frequency distribution where the...
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Percentage Frequency Distribution00:57

Percentage Frequency Distribution

60.8K
A percentage frequency distribution, in general, is a display of data that indicates the percentage of observations for each data point or grouping of data points. It is a commonly used method for expressing the relative frequency of survey responses and other data. The percentage frequency distributions are often displayed as bar graphs, pie charts, or tables.
The process of making a percentage frequency distribution involves the following few steps: note the total number of observations;...
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Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin
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Configural frequency trees.

Wolfgang Wiedermann1, Keith C Herman1, Wendy Reinke1

  • 1Department of Educational, School & Counseling Psychology and Missouri Prevention Science Institute, University of Missouri, Columbia, USA.

Development and Psychopathology
|March 22, 2021
PubMed
Summary

This study introduces Model-Based Recursive Partitioning Configural Frequency Analysis (MOB CFA) for analyzing developmental psychopathology data. MOB CFA accurately detects complex moderation processes in subpopulations, offering new insights into individual differences.

Keywords:
configural frequency analysismodel-based recursive partitioningmoderationperson-oriented researchregression trees

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Area of Science:

  • Developmental psychopathology
  • Quantitative psychology
  • Statistical modeling

Background:

  • Dominance of variable-oriented analyses in developmental psychopathology.
  • Growing interest in person-oriented approaches focusing on the individual as a whole.
  • Need for advanced statistical methods to test person-oriented hypotheses with categorical data.

Purpose of the Study:

  • Introduce a novel hybrid method, Model-Based Recursive Partitioning Configural Frequency Analysis (MOB CFA).
  • Test for type/antitype heterogeneity within populations using MOB CFA.
  • Demonstrate the capability of MOB CFA in detecting complex moderation and distinguishing subpopulation from population types/antitypes.

Main Methods:

  • Combination of Configural Frequency Analysis (CFA) and Model-Based Recursive Partitioning (MOB).
  • Application of MOB CFA for analyzing categorical data configurations.
  • Discussion of model specifications for first-order and prediction CFA within the MOB framework.
  • Validation through two simulation studies and two empirical examples from school mental health research.

Main Results:

  • Simulation studies confirm MOB CFA's high accuracy in detecting moderation processes.
  • MOB CFA effectively identifies heterogeneity in student behavior types/antitypes.
  • The method demonstrates utility in evaluating intervention effects on student behavior.

Conclusions:

  • MOB CFA is a powerful tool for person-oriented analyses of categorical data.
  • The approach enhances the ability to detect complex moderation and heterogeneity in subpopulations.
  • Provides a practical implementation in R for researchers in developmental psychopathology and related fields.