Answer:
a) v ∈ ker(<em>L</em>) if only if ![[V]_{E}](https://tex.z-dn.net/?f=%5BV%5D_%7BE%7D)
∈ <em>N</em>(<em>A</em>)
b) w ∈ <em>L</em>(<em>v</em>) if and only if ![[W]_{F}](https://tex.z-dn.net/?f=%5BW%5D_%7BF%7D)
is in the column space of <em>A</em>
<em />
<em>See attached</em>
Step-by-step explanation:
See attached the proof Considering the vector spaces <em>V</em> and <em>W</em> with other bases <em>E</em> and <em>F</em> respectively.
Let <em>L</em> be the Linear transformation form <em>V</em> and <em>W</em> and A is the matrix representing <em>L</em> relative to<em> E</em> and <em>F</em>
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Answer:
the greater the precision the smaller the standard deviation
there is no relationship between standard deviation and accuracy
Step-by-step explanation:
The standard deviation of a set measures how close the measures of this set are, that is, how precise they are.
The lesser the standard deviation is, the higher the precision is.
So the correct answer is:
the greater the precision the smaller the standard deviation
Accuracy is how close a measurement comes from the correct value. There is no relation between standard deviation and accuracy.
So:
there is no relationship between standard deviation and accuracy
Answer:
(a x b ) : (b x b ) : (b x c)
5x3 : 6x3 : 6 x 8
Step-by-step explanation:
15:18:48
