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\section { Linear Transformations}
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\definition { }
A \textit { function} or \textit { map} $ f $ from a set $ A $ to a set $ B $ is a rule that assigns an element of $ B $ to each element of $ A $ . We write this as $ f: A \to B $ .
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\definition { }
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Let $ V $ and $ U $ be vector spaces, and let $ f: V \to U $ be a map from $ V $ to $ U $ . \\
We say $ f $ is \textit { linear} if it satisfies the following for any $ v \in V $ , $ u \in U $ , $ a \in \mathbb { R } $ :
\begin { itemize}
\item $ f ( u + v ) = f ( u ) + f ( v ) $
\item $ f ( au ) = af ( u ) $
\end { itemize}
In other words, $ f $ is linear if it is \say { closed} under addition and scalar multiplication.
\problem { }
It is often convenient to combine the two conditions above into one. \\
Show that $ f ( au + v ) = af ( u ) + f ( v ) $ iff $ f $ is linear.
\vfill
\problem { }
Is $ f ( x ) = mx + b $ a linear map on $ \mathbb { R } $ ?
\vfill
\problem { }
In general, what does a linear map in $ \mathbb { R } ^ n $ look like?
\vfill
\problem { }
Is $ \text { median } ( v ) : \mathbb { R } ^ n \to \mathbb { R } $ a linear map on $ \mathbb { R } ^ n $ ?
\vfill
\problem { }
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Is $ \frac { d } { dx } ( p ) : \mathbb { P } ^ n \to \mathbb { P } ^ { n - 1 } $ a linear map on $ \mathbb { P } ^ n $ ? \\
\hint { $ \mathbb { P } ^ n $ is the set of all polynomials of degree $ n $ .}
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\vfill
\pagebreak