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Questions and Answers
Match the following descriptive statistics measures with their definitions:
Match the following descriptive statistics measures with their definitions:
La moyenne = Mesure qui add up all values and divide by the number of values Le mode = Mesure of the middle value of the data when in order La médiane = Mesure of the most frequent value in the data L'étendue = Mesure of the range of the data
Match the following statistical concepts with their explanations:
Match the following statistical concepts with their explanations:
Mesures de tendance centrale = Des grandeurs qui représentent au mieux un ensemble de données Dispersion = Mesure de l'écart entre les valeurs et la moyenne Fréquences = Nombre d'individus dans l'échantillon ayant une certaine caractéristique Analyse des données exploratoires = Phase qui regroupe des méthodes et des modèles quantitatifs pour aider à la prise de décision
Match the following statistical terms with their French translations:
Match the following statistical terms with their French translations:
Mean = La moyenne Mode = Le mode Median = La médiane Standard Deviation = L'écart type
Match the following statistical measures with their descriptions:
Match the following statistical measures with their descriptions:
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Match the following statistical concepts with their applications:
Match the following statistical concepts with their applications:
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Match the following statistical measures with their calculations:
Match the following statistical measures with their calculations:
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Match the following statistical concepts with their types:
Match the following statistical concepts with their types:
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Match the following statistical measures with their usage:
Match the following statistical measures with their usage:
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Match the following statistical concepts with their definitions:
Match the following statistical concepts with their definitions:
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Match the following types of statistical studies with their descriptions:
Match the following types of statistical studies with their descriptions:
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Match the following data visualization tools with their descriptions:
Match the following data visualization tools with their descriptions:
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Match the following statistical parameters with their descriptions:
Match the following statistical parameters with their descriptions:
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Match the following sampling methods with their descriptions:
Match the following sampling methods with their descriptions:
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Match the following statistical concepts with their applications:
Match the following statistical concepts with their applications:
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Match the following statistical concepts with their formulas:
Match the following statistical concepts with their formulas:
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Match the following statistical concepts with their applications in medicine:
Match the following statistical concepts with their applications in medicine:
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Match the following steps of the statistical approach with their descriptions:
Match the following steps of the statistical approach with their descriptions:
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Match the following types of statistics with their applications:
Match the following types of statistics with their applications:
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Match the following data visualization tools with their purposes:
Match the following data visualization tools with their purposes:
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Match the following characteristics of data collection with their descriptions:
Match the following characteristics of data collection with their descriptions:
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Match the following statistical analysis techniques with their purposes:
Match the following statistical analysis techniques with their purposes:
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Match the following types of data with their descriptions:
Match the following types of data with their descriptions:
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Match the following statistical concepts with their descriptions:
Match the following statistical concepts with their descriptions:
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Match the following purposes of statistical analysis with their descriptions:
Match the following purposes of statistical analysis with their descriptions:
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Study Notes
Les graphiques et la représentation des données
- Les graphiques sont des outils visuels puissants pour représenter des données de manière concise et significative.
- Ils permettent de visualiser des données, d'identifier des tendances et des motifs, de comparer des données et de prendre des décisions.
La démarche statistique
Phase 1 : Collecte des données
- Il faut déterminer le type d'information ou de données nécessaires.
- Il faut préciser comment les données seront recueillies : sur quoi portent-elles ? population ou échantillon, comment les obtenir ?
Phase 2 : Analyse statistique
- La statistique descriptive concerne les données exhaustives sur la population.
- La statistique inférentielle concerne les données de l'échantillon de la population.
Phase 3 : Décision statistique
- Cette phase regroupe des méthodes et des modèles quantitatifs pour aider à la prise de décision dans un contexte d'incertitude.
Analyse des données exploratoires
Les caractéristiques de tendance centrale des données
- Les paramètres de tendance centrale représentent un ensemble de données : mode, moyenne, médiane, quartilles, centilles décilles.
- Les paramètres de position : mode, moyenne, médiane.
- Les paramètres de dispersion : étendue, variance, écart type.
Les fréquences
- La fréquence absolue est le nombre d'individus correspondant à chaque modalité de la variable X.
- La fréquence relative est la fréquence absolue divisée par la taille de l'échantillon.
Les paramètres de dispersion
- L'étendue est la différence entre la valeur maximale et la valeur minimale.
- La variance est une mesure de la dispersion d'une série de données.
- L'écart type est la racine carrée de la variance.
Estimations et tailles d'échantillons
- Les types d'échantillonnage : aléatoire, stratifié, etc.
- Estimation de la proportion, de la moyenne et de la variance d'une population.
- Les critères d'échantillonnage : taille de l'échantillon, erreur d'échantillonnage.
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Description
Les graphiques sont des outils visuels puissants pour représenter des données de manière concise et significative. Ils sont utilisés dans de nombreux domaines, notamment la santé, pour analyser et communiquer des données de manière efficace.