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Suppose $f$ and $g$ are functions from $\mathbb{R}$ to a topological space $X$, and $f$ converges to $l$ at $a$. If $g$ and $f$ agree on a neighborhood of $a$, then $g$ converges to $l$ at $a$.
If $f$ and $g$ are functions such that $f$ is continuous at $a$ and $g$ is continuous at $f(a)$, then $g \circ f$ is continuous at $a$.
If $f$ converges to $0$ and $g$ is bounded above by $f$ and bounded below by $0$, then $g$ converges to $0$.
A function $f$ is continuous at $a$ if and only if the function $h \mapsto f(a + h)$ is continuous at $0$.
A function $f$ is continuous at $x$ if and only if the function $h \mapsto f(x + h)$ converges to $f(x)$ as $h$ approaches $0$.
If $f$ is continuous at $a$ and $g$ is continuous at $f(a)$, then $g \circ f$ is continuous at $a$.
If $f$ is continuous at $a$, then $\|f\|$ is continuous at $a$.
If $f$ is continuous at $a$, then $\lvert f \rvert$ is continuous at $a$.
If $f$ and $g$ are continuous at $a$, then $f + g$ is continuous at $a$.
If $f$ is continuous at $a$, then $-f$ is continuous at $a$.
If $f$ and $g$ are continuous at $a$, then $f - g$ is continuous at $a$.
If $f$ and $g$ are continuous at $a$, then $f \cdot g$ is continuous at $a$.
If $g$ is a continuous function, then $f \circ g$ is continuous.
If $f$ and $g$ are continuous at $a$, then the function $f \cdot g$ is continuous at $a$.
The function $f(x) = ax$ is continuous.
The function $x \mapsto x$ is continuous.
If $f$ is continuous at $a$, then $f^n$ is continuous at $a$.
If $f_i$ is continuous at $a$ for all $i \in A$, then $\sum_{i \in A} f_i$ is continuous at $a$.
A function $f$ is uniformly continuous on a set $S$ if and only if for every $\epsilon > 0$, there exists a $\delta > 0$ such that for all $x, x' \in S$, if $|x - x'| < \delta$, then $|f(x) - f(x')| < \epsilon$.
A function $f$ is uniformly continuous if and only if for every $\epsilon > 0$, there exists $\delta > 0$ such that for all $x, y \in \mathbb{R}$, if $|x - y| < \delta$, then $|f(x) - f(y)| < \epsilon$.
If $f$ is uniformly continuous, then $f$ is continuous.
If $f$ is uniformly continuous on a set $S$, and if the sequence $X$ is Cauchy and takes values in $S$, then the sequence $f(X)$ is Cauchy.
If $f$ is uniformly continuous and $X$ is a Cauchy sequence, then $f(X)$ is a Cauchy sequence.
If $f$ is uniformly continuous on $S$ and $\sigma$ is a Cauchy sequence in $S$, then $f \circ \sigma$ is a Cauchy sequence.
If $f$ is a bounded linear operator, then $f$ is uniformly continuous.
If $X$ is a Cauchy sequence, then $f(X)$ is a Cauchy sequence.
If $f$ is continuous at $x$ and $f$ is non-negative on the interval $(b, x)$, then $f(x) \geq 0$.
If $f$ and $g$ are two nested sequences of real numbers such that $f_n \leq g_n$ for all $n$ and $\lim_{n \to \infty} (f_n - g_n) = 0$, then there exists a real number $l$ such that $\lim_{n \to \infty} f_n = l = \lim_{n \to \infty} g_n$.
If $P$ is a transitive relation on the real numbers and $P$ is locally true, then $P$ is true.
The closed interval $[a, b]$ is compact.
If $f$ is a continuous function on the closed interval $[a,b]$, then $f([a,b])$ is also a closed interval.
If $f$ is a continuous real-valued function defined on a set $s$, then there exists an open set $A$ such that $A \cap s = \{x \in s \mid f(x) > 0\}$.
If $f$ and $g$ are continuous real-valued functions defined on a set $S$, then the set $\{x \in S \mid f(x) < g(x)\}$ is open in $S$.
If $f$ is continuous on the closed interval $[a,b]$, then $f$ attains its supremum on $[a,b]$.
If $f$ is continuous on the closed interval $[a,b]$, then $f$ attains its least upper bound on $[a,b]$.
If $f$ is continuous on the closed interval $[a,b]$, then $f$ is bounded on $[a,b]$.
If $f$ is continuous on the closed interval $[a,b]$, then $f$ has a supremum on $[a,b]$.
If $f$ is continuous on the closed interval $[a,b]$, then $f$ attains its maximum and minimum on $[a,b]$.
Suppose $f$ is a function defined on an interval $(x-d, x+d)$ and $g$ is its inverse. If $f$ is continuous at $x$, then $g$ is continuous at $f(x)$.
Suppose $f$ and $g$ are functions such that $g(f(x)) = x$ for all $x$ in the interval $(a,b)$. If $f$ is continuous at $x$, then $g$ is continuous at $f(x)$.
If $f$ converges to a positive number $l$, then there exists a positive number $r$ such that $f$ is positive on the interval $(c - r, c + r)$.
If $f$ converges to $l < 0$, then there exists $r > 0$ such that for all $x$ with $|x - c| < r$, we have $f(x) < 0$.
If $f$ converges to $l \neq 0$, then there exists $r > 0$ such that $f(x) \neq 0$ for all $x$ with $|x - c| < r$.
If $f$ is a linear operator, then $f$ satisfies the usual linear properties.
The set of values of a function $f$ on a finite set is finite.
If $d$ is a subset of the basis of a Euclidean space, then the expansion of a vector $x$ in terms of the basis vectors in $d$ is unique.
If $d$ is a subset of the standard basis, then $d$ is independent.
For any real vector space $V$ and any $a \in V$, the set $a + S$ is a subset of $a + T$ if and only if $S$ is a subset of $T$.
The translation $x \mapsto a + x$ is injective on any set $A$.
For any set $S$ and any elements $a$ and $b$ of an abelian group, the set of all elements of the form $b + (a + x)$ for $x \in S$ is equal to the set of all elements of the form $(a + b) + x$ for $x \in S$.
If two sets are equal after translation by the same amount, then they are equal.
For any set $S$ and any element $a$, the set $T = \{a + x \mid x \in S\}$ is equal to the set $\{-a + x \mid x \in S\}$.
If $V$ is a subset of the translation of $S$ by $-a$, then $V$ is a subset of the translation of $S$ by $a$.
If $f$ is a linear map from $\mathbb{R}^n$ to $\mathbb{R}^m$, then the $j$th component of $f(x)$ is equal to the sum of the $j$th components of $f(e_i)$ times the $i$th component of $x$, where $e_i$ is the $i$th standard basis vector.
Two vectors are equal if and only if their inner products with themselves are equal and their inner products with each other are equal.
If $|y - x_1| < \frac{\epsilon}{2}$ and $|y - x_2| < \frac{\epsilon}{2}$, then $|x_1 - x_2| < \epsilon$.
If $|x - y| < \frac{e}{2}$ and $|x' - y| < \frac{e}{2}$, then $|x - x'| < e$.
If $|y - x_1| < \frac{e}{2}$ and $|y - x_2| < \frac{e}{2}$, then $|x_1 - x_2| < e$.
If $|x - y| < \frac{\epsilon}{2}$ and $|x' - y| < \frac{\epsilon}{2}$, then $|x - x'| < \epsilon$.
The sum of the empty set is zero. If $S$ is a finite set and $x \in S$, then the sum of $S$ is the same as the sum of $S \setminus \{x\}$. If $S$ is a finite set and $x \notin S$, then the sum of $S$ is the same as the sum of $S \cup \{x\}$.
Two vectors are equal if and only if they have the same dot product with every vector.
Two vectors are equal if and only if they are equal when dotted with any other vector.
If $n$ is less than or equal to the cardinality of $A$, then there exists a subset $S$ of $A$ such that $S$ has cardinality $n$.
The set of all vectors in $\mathbb{R}^n$ whose $i$th coordinate is zero whenever $P(i)$ is true is a subspace.
The dimension of the set of points in $\mathbb{R}^n$ that are orthogonal to a given set of $d$ linearly independent vectors is $d$.
Two vectors are orthogonal if and only if they are equal to zero.
The following are equivalent: $a$ is orthogonal to $0$. $a$ is orthogonal to $x$ and $c$ is a scalar. $a$ is orthogonal to $x$ and $-x$. $a$ is orthogonal to $x$ and $y$ and $x + y$. $a$ is orthogonal to $x$ and $y$ and $x - y$. $0$ is orthogonal to $a$. $x$ is orthogonal to $a$ and $c$ is a scalar. $x$ is orthogonal t...
Two vectors are orthogonal if and only if they are orthogonal.
If $c \neq 0$, then $cx$ is orthogonal to $y$ if and only if $x$ is orthogonal to $y$.
If $f_i$ and $g_j$ are pairwise orthogonal, then so are $a_i f_i$ and $a_j g_j$.
If $x$ is orthogonal to each $f(y)$ for $y \in s$, then $x$ is orthogonal to $\sum_{y \in s} f(y)$.
If $f$ is a finite set of vectors and $y$ is a vector such that $f(x)$ is orthogonal to $y$ for all $x \in f$, then the sum of the vectors in $f$ is orthogonal to $y$.
If two vectors are orthogonal, then the Pythagorean theorem holds for them.
If $f_i$ are pairwise orthogonal, then $\|\sum_i f_i\|^2 = \sum_i \|f_i\|^2$.
A linear transformation $f$ is an orthogonal transformation if and only if $\|f(v)\| = \|v\|$ for all $v$.
The identity function is an orthogonal transformation.
If $f$ is an orthogonal transformation, then $f(x)$ is orthogonal to $f(y)$ if and only if $x$ is orthogonal to $y$.
If $f$ and $g$ are orthogonal transformations, then so is $f \circ g$.
A linear transformation $f$ is orthogonal if and only if $-f$ is orthogonal.
If $f$ is an orthogonal transformation, then $f(c \cdot v) = c \cdot f(v)$.
If $f$ is an orthogonal transformation, then $f$ is linear.
If $f$ is an orthogonal transformation, then $f$ is injective.
If $f$ is an orthogonal transformation, then $f$ is surjective.
If $f$ is an orthogonal transformation, then $f$ is a bijection.
If $f$ is an orthogonal transformation, then $f^{-1}$ is an orthogonal transformation.
If $f$ is an orthogonal transformation, then $\|f(x)\| = \|x\|$.
If $h$ is bilinear, then $h(x + y, z) = h(x, z) + h(y, z)$.
If $h$ is a bilinear function, then $h(x, y + z) = h(x, y) + h(x, z)$.
The multiplication operation is bilinear.
If $h$ is a bilinear function, then $h(cx, y) = ch(x, y)$.
If $h$ is bilinear, then $h(x, c y) = c h(x, y)$.
If $h$ is bilinear, then $h(-x)y = -h(x)y$.
If $h$ is bilinear, then $h(x, -y) = -h(x, y)$.
In an abelian group, $x = x + y$ if and only if $y = 0$.
If $h$ is a bilinear function, then $h(0, x) = 0$ for all $x$.
If $h$ is bilinear, then $h(x, 0) = 0$.
If $h$ is bilinear, then $h(x - y)z = h(x)z - h(y)z$.
If $h$ is bilinear, then $h(z, x - y) = h(z, x) - h(z, y)$.
If $h$ is bilinear, then $h( \sum_{i \in S} f_i, \sum_{j \in T} g_j) = \sum_{(i,j) \in S \times T} h(f_i, g_j)$.
If $f$ is an adjoint of $g$, then $g$ is an adjoint of $f$.