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| ==en construction==
| | #REDIRECTION[[Statistique inférentielle]] |
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| == Définition ==
| | [[Catégorie:ENGLISH]] |
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| == Français ==
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| ''' XXXXXXXXX '''
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| == Anglais ==
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| ''' Inferential Statistics '''
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| '''Descriptive Statistics'''
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| It is easiest to talk about inferential statistics if we first understand what descriptive statistics are. Descriptive statistics describe only the data collected. Inferential statistics take data collected and make predictions based on the data instead.
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| For example, let’s say there is a survey done on 100 people. You ask each of these 100 people if they like to ride horses. You find that 35 of the 100 people, or 35% answer that yes, they like to ride horses. A chart of this data would be descriptive statistics because it only uses the data collected to create the chart. If we were to infer that this data collection indicates that 35% of the American population likes to ride horses, we would be using inferential statistics. We did not survey the entirety of America and in fact, it would be difficult to do so. So instead, we infer the correct information instead using the data that we did collect.
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| [https://www.analyticsvidhya.com/glossary-of-common-statistics-and-machine-learning-terms/ Source : analyticsvidhya.com ]
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| [https://deepai.org/machine-learning-glossary-and-terms/inferential-statistics Source : DeepAI.org ]
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| [[Catégorie:DeepAI.org]]
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| [[Catégorie:vocabulary]] | |
