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JKISeason3-23

Description: You are a social scientist who needs to create some synthetic data for an imaginary population consisting of 1000 people, including attributesage, height, and weight. Start by generating a Gaussian age distribution using a mean of 40 and a standard deviation of 10, then bin people into four agegroups: 'Children', 'Young Adults', 'Adults', and 'Seniors’. For each group, generate heights using a beta distribution with realistic parameters. Categorizeheights into three groups: ‘< 160cm', ‘> 180', and 'rest’. Based on the binned height information, generate weights using a gamma distribution that accuratelymodels weight distributions per age group. Visualize the relationships and identify patterns and correlations within this synthetic population. Node 1Node 2Age lower age @ 5Node 12M/FNode 42Category Age_GenderNode 51Node 52heightNode 54Node 56Node 57Node 62weightNode 72Node 74Node 75Node 87weightNode 89 Empty Table Creator Counter Generation Gaussian DistributedAssigner Numeric Binner Random LabelAssigner Double to Integer String Manipulation Group Loop Start Table Creator Beta DistributedAssigner ReferenceRow Filter Table Rowto Variable Loop End Gamma DistributedAssigner Math Formula Column Filter Numeric Binner Sorter Row Sampling Math Formula Concatenate Data Viz Description: You are a social scientist who needs to create some synthetic data for an imaginary population consisting of 1000 people, including attributesage, height, and weight. Start by generating a Gaussian age distribution using a mean of 40 and a standard deviation of 10, then bin people into four agegroups: 'Children', 'Young Adults', 'Adults', and 'Seniors’. For each group, generate heights using a beta distribution with realistic parameters. Categorizeheights into three groups: ‘< 160cm', ‘> 180', and 'rest’. Based on the binned height information, generate weights using a gamma distribution that accuratelymodels weight distributions per age group. Visualize the relationships and identify patterns and correlations within this synthetic population. Node 1Node 2Age lower age @ 5Node 12M/FNode 42Category Age_GenderNode 51Node 52heightNode 54Node 56Node 57Node 62weightNode 72Node 74Node 75Node 87weightNode 89Empty Table Creator Counter Generation Gaussian DistributedAssigner Numeric Binner Random LabelAssigner Double to Integer String Manipulation Group Loop Start Table Creator Beta DistributedAssigner ReferenceRow Filter Table Rowto Variable Loop End Gamma DistributedAssigner Math Formula Column Filter Numeric Binner Sorter Row Sampling Math Formula Concatenate Data Viz

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Created by: jrpan
Created at: 2024-10-17
On NodePit since: 2024-10-21
Last update: 2024-10-22
Created with KNIME version: v5.2.5
Tags: JKISeason3-23

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