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Frames Catherine White
Frames Catherine White
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Normalising standardising sub-data sets, and have a normalsuch that the whole dataset is standardised

Consider a data set $X$ made up of smaller subsets: $X=A \cup B \cup C$, with $A,B,C$ disjoint data sets. Eg: $A=\{1.0, -1.0, 0\}$, $B=\{5.0, -7.0, 2.0\}$, $C=\{1.5, -5.0, 8.0\}$

Is is possible to transform (scale, shift) $A,B,C$ such that each is individually standard normally distributed (mean=0standardised to have mean=0, stdand std dev=1.0), and so that $X$ is also standard normally distributedhas mean=0, std dev=1.0?

Normalising sub-data sets, and have a normal whole

Consider a data set $X$ made up of smaller subsets: $X=A \cup B \cup C$, with $A,B,C$ disjoint data sets. Eg: $A=\{1.0, -1.0, 0\}$, $B=\{5.0, -7.0, 2.0\}$, $C=\{1.5, -5.0, 8.0\}$

Is is possible to transform (scale, shift) $A,B,C$ such that each is individually standard normally distributed (mean=0, std dev=1.0), and so that $X$ is also standard normally distributed?

standardising sub-data sets, such that the whole dataset is standardised

Consider a data set $X$ made up of smaller subsets: $X=A \cup B \cup C$, with $A,B,C$ disjoint data sets. Eg: $A=\{1.0, -1.0, 0\}$, $B=\{5.0, -7.0, 2.0\}$, $C=\{1.5, -5.0, 8.0\}$

Is is possible to transform (scale, shift) $A,B,C$ such that each is individually standardised to have mean=0, and std dev=1.0, and so that $X$ also has mean=0, std dev=1.0?

Source Link
Frames Catherine White
Frames Catherine White
  • 3.2k
  • 1
  • 22
  • 36

Normalising sub-data sets, and have a normal whole

Consider a data set $X$ made up of smaller subsets: $X=A \cup B \cup C$, with $A,B,C$ disjoint data sets. Eg: $A=\{1.0, -1.0, 0\}$, $B=\{5.0, -7.0, 2.0\}$, $C=\{1.5, -5.0, 8.0\}$

Is is possible to transform (scale, shift) $A,B,C$ such that each is individually standard normally distributed (mean=0, std dev=1.0), and so that $X$ is also standard normally distributed?