Rearranged handout

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Mark 2023-04-03 11:13:33 -07:00
parent ef6fa1da2b
commit ef0abb5f17
5 changed files with 24 additions and 27 deletions

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@ -26,9 +26,6 @@
Prepared by Mark on \today \\ Prepared by Mark on \today \\
} }
\section{Fields and Vector Spaces}
\input{parts/0 fields} \input{parts/0 fields}
\input{parts/1 spaces} \input{parts/1 spaces}
\input{parts/2 linearity} \input{parts/2 linearity}
@ -40,7 +37,7 @@
\section{Bonus} \section{Bonus}
\definition{} \definition{}
Show that $\mathbb{P}^n$, the set of polynomials of degree $n$, is a vector space. Show that $\mathbb{P}^n$ is a vector space.
\vfill \vfill
\problem{} \problem{}

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@ -1,3 +1,5 @@
\section{Fields}
\definition{Fields and Field Axioms} \definition{Fields and Field Axioms}
A \textit{field} $\mathbb{F}$ consists of a set $A$ and two operations $+$ and $\times$. \\ A \textit{field} $\mathbb{F}$ consists of a set $A$ and two operations $+$ and $\times$. \\
As usual, we may abbreviate $a \times b$ as $ab$. \\ As usual, we may abbreviate $a \times b$ as $ab$. \\

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@ -1,3 +1,5 @@
\section{Spaces}
\definition{Vector Spaces} \definition{Vector Spaces}
A \textit{space} over a field $\mathbb{F}$ consists of the following elements: A \textit{space} over a field $\mathbb{F}$ consists of the following elements:
\begin{itemize}[itemsep = 2mm] \begin{itemize}[itemsep = 2mm]
@ -5,7 +7,7 @@ A \textit{space} over a field $\mathbb{F}$ consists of the following elements:
\item An operation called \textit{vector addition}, denoted $+$ \\ \item An operation called \textit{vector addition}, denoted $+$ \\
Vector addition operates on two elements of $V$. \\ Vector addition operates on two elements of $V$. \\
\item An operation called \textit{scalar multilplication}, denoted $\times$ \\ \item An operation called \textit{scalar multiplication}, denoted $\times$ \\
Scalar multiplication multiplies an element of $V$ by an element of $\mathbb{F}$. \\ Scalar multiplication multiplies an element of $V$ by an element of $\mathbb{F}$. \\
Any element of $\mathbb{F}$ is called a \textit{scalar}. Any element of $\mathbb{F}$ is called a \textit{scalar}.
\end{itemize} \end{itemize}

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@ -1,4 +1,4 @@
\section{Linearity} \section{Linear Transformations}
\definition{} \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 $f: A \to B$. 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 $f: A \to B$.
@ -36,7 +36,8 @@ Is $\text{median}(v): \mathbb{R}^n \to \mathbb{R}$ a linear map on $\mathbb{R}^n
\vfill \vfill
\problem{} \problem{}
Is $\frac{d}{dx}(p): \mathbb{P}^n \to \mathbb{P}^{n-1}$ a linear map on $\mathbb{P}^n$? 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 $n$.}
\vfill \vfill
\pagebreak \pagebreak

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@ -17,8 +17,8 @@ Draw a $3 \times 2$ matrix.
\vfill \vfill
\definition{} \definition{}
We can define the \say{product\footnotemark{}} of a matrix $A$ and a vector $v$: We can define the product of a matrix $A$ and a vector $v$:
\footnotetext{This is an uncommon word to use in this context. You will soon see why.}
$$ $$
Av = Av =
\begin{bmatrix} \begin{bmatrix}
@ -34,7 +34,7 @@ Av =
4a + 5b + 6c 4a + 5b + 6c
\end{bmatrix} \end{bmatrix}
$$ $$
Look closely. Each element of the resulting $2 \times 1$ matrix is the dot product of a row of $A$ with $v$: Each element of the resulting $2 \times 1$ matrix is the dot product of a row of $A$ with $v$:
$$ $$
Av = Av =
@ -61,9 +61,9 @@ Compute the following:
$$ $$
\begin{bmatrix} \begin{bmatrix}
2 & 9 \\ 1 & 2 \\
7 & 5 \\ 3 & 4 \\
3 & 4 5 & 6
\end{bmatrix} \end{bmatrix}
\begin{bmatrix} \begin{bmatrix}
5 \\ 3 5 \\ 3
@ -84,16 +84,16 @@ It is a bit more interesting to think of matrix-vector multiplication in the fol
$$ $$
\begin{bmatrix} \begin{bmatrix}
2 & 9 \\ 1 & 2 \\
7 & 5 \\ 3 & 4 \\
3 & 4 5 & 6
\end{bmatrix} \end{bmatrix}
\begin{bmatrix} \begin{bmatrix}
5 \\ 3 5 \\ 3
\end{bmatrix} \end{bmatrix}
= =
\begin{bmatrix} \begin{bmatrix}
37 \\ 50 \\ 27 11 \\ 27 \\ 43
\end{bmatrix} \end{bmatrix}
$$ $$
\end{center} \end{center}
@ -110,9 +110,9 @@ It is a bit more interesting to think of matrix-vector multiplication in the fol
left delimiter={[}, left delimiter={[},
right delimiter={]} right delimiter={]}
] (A) { ] (A) {
2 & 9 \\ 1 & 2 \\
7 & 5 \\
3 & 4 \\ 3 & 4 \\
5 & 6 \\
}; };
\node[ \node[
@ -133,21 +133,21 @@ It is a bit more interesting to think of matrix-vector multiplication in the fol
\node[ \node[
fit=(A-1-2)(A-1-2), fit=(A-1-2)(A-1-2),
inner xsep=8mm,inner ysep=0mm, inner xsep=8mm,inner ysep=0mm,
label=right:{$10 + 27 = 37$} label=right:{$5 + 6 = 11$}
](Y) {}; ](Y) {};
\draw[->, gray] ([xshift=3mm]A-1-2.east) -- (Y); \draw[->, gray] ([xshift=3mm]A-1-2.east) -- (Y);
\node[ \node[
fit=(A-2-2)(A-2-2), fit=(A-2-2)(A-2-2),
inner xsep=8mm,inner ysep=0mm, inner xsep=8mm,inner ysep=0mm,
label=right:{$35 + 15 = 50$} label=right:{$15 + 12 = 27$}
](H) {}; ](H) {};
\draw[->, gray] ([xshift=3mm]A-2-2.east) -- (H); \draw[->, gray] ([xshift=3mm]A-2-2.east) -- (H);
\node[ \node[
fit=(A-3-2)(A-3-2), fit=(A-3-2)(A-3-2),
inner xsep=8mm,inner ysep=0mm, inner xsep=8mm,inner ysep=0mm,
label=right:{$15 + 12 = 27$} label=right:{$25 + 18 = 43$}
](N) {}; ](N) {};
\draw[->, gray] ([xshift=3mm]A-3-2.east) -- (N); \draw[->, gray] ([xshift=3mm]A-3-2.east) -- (N);
\end{tikzpicture} \end{tikzpicture}
@ -187,11 +187,6 @@ Before you start, answer the following questions:
Show that any linear transformation can be written as a matrix. Show that any linear transformation can be written as a matrix.
\vfill \vfill
\pagebreak
\problem{}
Show that $\mathbb{P}^n$, the set of polynomials of degree $n$, is a vector space.
\vfill
\problem{} \problem{}