02c - Data Cleaning Flashcards

1
Q

Was macht man grundsätzlich wenn manche Daten fehlen? (Missing Data Analysis)?

A

F19

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2
Q

Welche Methoden werden für eine Missing Data Analysis verwendet?

A

F19

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3
Q

In welche Typologien werden fehlende Daten eingeteilt?

A

F20

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4
Q

Was macht man, wenn man fehlende Daten ergänzt/einfügt?

A

F21

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5
Q

Was macht man, wenn man für fehlende Daten eine Expectation Maximization verwendet?

A

F21

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6
Q

Was macht man, wenn man für fehlende Daten eine Regression Imputation verwendet?

A

F22

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7
Q

Welche Methoden gibt es bei der Regression Imputation?

A

F22

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8
Q

Was macht man bei der Maximum Likelihood Estimation?

A

F23-26

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9
Q

Was macht man bei der Methode Multiple Imputation?

A

27

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10
Q

Wodurch ensteht Noise?

A

F28

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11
Q

Was sind die Auswirkungen von Noise auf den Datensatz?

A

F28

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12
Q

Welche Varianten gibt es , um mit Noise umzugehen?

A

F29

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13
Q

Welche Varianten gibt es beim Binning?

A

F30 - 34

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14
Q

Was kann man bei redundanten Daten machen?

A

F34, 35, 36

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