% This LaTeX document needs to be compiled with XeLaTeX. \documentclass[10pt]{article} \usepackage[utf8]{inputenc} \usepackage{amsmath} \usepackage{amsfonts} \usepackage{amssymb} \usepackage[version=4]{mhchem} \usepackage{stmaryrd} \usepackage{bbold} \usepackage{graphicx} \usepackage[export]{adjustbox} \graphicspath{ {./images/} } \usepackage{caption} \usepackage{multirow} \usepackage{hyperref} \hypersetup{colorlinks=true, linkcolor=blue, filecolor=magenta, urlcolor=cyan,} \urlstyle{same} \usepackage[fallback]{xeCJK} \usepackage{polyglossia} \usepackage{fontspec} \usepackage{newunicodechar} \IfFontExistsTF{Noto Serif CJK TC} {\setCJKmainfont{Noto Serif CJK TC}} {\IfFontExistsTF{STSong} {\setCJKmainfont{STSong}} {\IfFontExistsTF{Droid Sans Fallback} {\setCJKmainfont{Droid Sans Fallback}} {\setCJKmainfont{SimSun}} }} \setmainlanguage{english} \IfFontExistsTF{CMU Serif} {\setmainfont{CMU Serif}} {\IfFontExistsTF{DejaVu Sans} {\setmainfont{DejaVu Sans}} {\setmainfont{Georgia}} } \newunicodechar{∴}{\ifmmode\therefore\else{$\therefore$}\fi} \newunicodechar{→}{\ifmmode\rightarrow\else{$\rightarrow$}\fi} \newunicodechar{⇒}{\ifmmode\Rightarrow\else{$\Rightarrow$}\fi} \begin{document} \captionsetup{singlelinecheck=false} ofloy 126 Stat 571 Probability \& Messure Lecture 5. Measure Furetions Simple furtion (simple rendom veriable) net $(\Omega, \mp, \mathbb{P})$ be a probability space be $\mathbb{P}(\Omega)=1$ Simple revetom veriable $x: \Omega \rightarrow \mathbb{R}$ L $x(w)$ only takes a finite \# of values $\left\{x_{1}, x_{p}\right\}$ also, the set $\left\{w \in \Omega: x(w)=x_{i}\right\} \in \Psi$ Let $\left[A_{i}\right]_{i=1}^{P}, A_{i} \in F$ be a dirjoint portitus of $\Omega$, $L_{i=1}^{p} A_{i}=\Omega \quad A_{i} \cap A_{j}=\phi \quad$ f $\quad c \neq j x(\omega)=\sum_{i}^{p} x_{1}\left[\omega \in A_{i}\right]$ We can then gey that the probability that $x$ is epual to $x_{c}$ is $\mathbb{P}\left(x=x_{i}\right)=\mathbb{P}\left(\left\{\omega \in \Omega: x(\omega)=x_{i}\right\}\right)=\mathbb{P}\left(A_{i}\right)$ can also deline the expectation of $x$ to be $$E x=\left\{x_{i} \mathbb{P}\left(x=x_{i}\right)\right.$$ Example: $\Omega=(0,1]$\\ $x_{1}=\overline{4}$ \begin{figure}[h] \begin{center} \includegraphics[alt={},max width=\textwidth]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_643_800_2445_1269} \captionsetup{labelformat=empty} \caption{Simple measurathe function $(\Omega, F, \mu)$ be a meaxue space $F: \Omega \rightarrow R$ is st $F(\omega)=\sum_{i=1}^{p} x_{i}$ II $\left[\omega \in B_{i}\right]$} \end{center} \end{figure} \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_1819_2352_3714_0} So are $f+g, f \cdot g=f(\omega) g(\omega)$, mex $\{f, g\}$ min $\{f, g\}$\\ are also simple funtions\\ We define the integral of a simple finetion to be $$f f d_{\mu}=\sum_{i x, \mu(B i)}^{a}$$ \begin{center} \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_3058_2367_4576_0} \end{center} $$\begin{aligned} & \text { Secordly, }(Y(, Y) \text { is otten }(\mathbb{R}, B(\mathbb{R})) \\ & \text { ( } \left.\mathbb{R}, \beta(\mathbb{R})^{+}\right) \\ & \text {In this ase, me a say that } f \text { is Borel measurable } \\ & \text { Similarly, me can replace } \beta(\mathbb{R}) \text { with } M_{\lambda}(\mathbb{R}) \text { to } \\ & \text { Set lebesgue measurable finctions. } \end{aligned}$$ \begin{center} \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_157_1301_8902_62} \end{center} \section*{i.e. for images of set firections preserve set perchous} $$\begin{aligned} & \text { Anint : If I wait to show thet sets A,B are } \\ & \text { equal, thein shal thet both } A \subseteq B \text { and } B \in A \text { hold }) \end{aligned}$$ g. het $A_{t}=(-\infty, t] \forall t \in \mathbb{R}$ these sets generte $p(R)$\\ $\Rightarrow f$ is measurable as long as $\{x: f(x) \leqslant t\}$ are\\ measu-ble\\ 2. For any $A \in X$, the malicator function $f(x)=\mathbb{I}[x \in A$ is measurester, The $\theta$-field generented by $f^{-1}$ is simply $$\text { 3. For reasurcule knotions } f, g \cdot X \rightarrow \mathbb{R} \text { then } f+g$$ following ane also measureble\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_267_1975_12131_78}\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_236_2348_12570_31} a courtable pacrsection of messivelle sits is restivelse\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_189_2285_12931_94} $=$ " $\left.\left\{x: f^{(x)}\right\}+1\right\}$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_205_1129_13448_78}\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_266_1156_13655_87}\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_189_2227_13903_125}\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_204_2335_14075_31}\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_205_2274_14294_31}\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_220_2273_14451_31} over\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_330_2336_15047_31}\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_283_2321_15235_31} West wer $\sigma\left(\Sigma f^{-1}(\omega): u \subset R\right.$, ven $\left.\xi\right) \leq \beta(x)$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_235_2147_15580_31}\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_266_2132_15674_31}\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_235_2317_15862_62}\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_249_2171_16011_59} vi,vety\\ Let $(\Omega, 7, \mu)$ Lo a maxtro speci for $f, g: e \rightarrow \mathbb{R}$, and ong that $f=9$ a.e When the Beet $N=\left\{N: f(u) \neq g^{(L)}\right\} \mu(N)=0$\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_267_2007_17367_141} for awth probablify 7\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-1_205_2242_17711_31} excepplee Let $((0,1,3, \beta, 3)$ be a meave speev. We $f(t)=0 \quad \forall t \in(0,1]$. Let $g(t)= \begin{cases}0 & \forall ta, g(y) \leq b\})$ \(=\lambda((F(a), F(b)])\) \\ \hline any other measure $\mu$ s.t $\mu((-b])=F(b)-F(a)$ must comender with $d F$ on all bovel sets. \\ \hline \end{tabular} \end{center} \section*{Def: (Ladon measure) \\ Let $(\Omega, \beta, \mu)$ be a reasure spore $\beta$ s the Borel $\sigma$-ficld $\mu$ is sall to be knolon if $\mu(k)$. Inite for all compact $k \epsilon \beta$} \begin{center} \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-3_238_2194_8626_18} \end{center} \begin{center} \begin{tabular}{|l|} \hline \begin{tabular}{l} $\therefore F(b)-F(a)=\mu((a, b])$ for $a+\})=0\}$ \begin{itemize} \item ess spe \{lfl\}\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_598_664_2540_1436}\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_222_796_2872_0}\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_288_1392_3225_44}\\ , 1 and $\infty$ an anyouges.\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_287_1966_3712_0}\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_244_1105_3910_0}\\ ten $\{f\}<\}=\{\omega \in \Omega: f(\omega)>i\}$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_266_1481_4352_265}\\ $\mu(2 f f+3) \leqslant \frac{1}{4} \int f d \mu$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_266_1238_4905_44}\\ $t_{p}(2 \leqslant z+3)=+\int \eta_{p+x} d x$ $\_\_\_\_$\\ Ant\\ $\leq \int f d \mu$\\ $\Rightarrow \mu(\varepsilon f+t) \leq \frac{1}{+} \int f d \mu$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_266_1503_5965_44}\\ (1)7) clexysten's They\\ for of measurable, and $m \in \mathbb{R}$\\ $\mu(\{|f-m|+t\}) \leq t^{-2} \int(f-m)^{2} d \mu$\\ (2) chenate's In\\ for $\quad f \quad$ mesuruble, $\eta \in \mathbb{R}$\\ $\quad \mu(\varepsilon f+3) \leq e^{-\eta+} \int e^{\eta f} d \mu$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_399_1216_7821_44}\\ Let $I \subseteq \mathbb{R}$ be an internal ; a fultion $\phi: I \rightarrow \mathbb{R}$ is convex\\ $\forall t \in[0,1]$ and all $x, y=\sum \phi(t x+(1-t) y) \leq \phi(x)+(1-t) \phi(y)$\\ $\_\_\_\_$ "Seciart line "\\ amogs on top"\\ Therem (Jensen's Treq)\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_421_2232_9191_0}\\ have $\quad \phi\left(\int x d r\right) \leq \int \phi(x) d r$\\ T.e. $\phi(\mathbb{E} x) \leq \mathbb{E}[\phi(x)]$ \end{itemize} Proof : For Some $c0}|f|^{p} d \mu$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_354_1636_14185_44}\\ $\left[\leqslant\left[\int x^{2} x\right]^{2}-1+4 \ln 4 y^{2} l\right.$ Note: $p=q=2$, m have canchy Schiner $z$ Ineq\\ Therem: (Minhershish's Ing)\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_398_2299_16505_44}\\ Root: If $\|f\|_{p}=\infty$ or $\| g l_{p}=\infty$ the done\\ If $\|f+g\|_{p}=0$ done\\ Mffillp =0 dore\\ otherwise, $|f+g|^{p}=2^{p}\left|\frac{\left.\right|^{f+g}}{2}\right|$\\ $\leqslant 2^{p}\left(\frac{1}{2}|f|^{p}+\frac{1}{2}|g| p\right)$\\ $2^{p-1}\left(1 f_{i}^{p}+g_{g^{p}} \rho^{p}\right)$\\ $\int|f+g|{ }^{p} d \mu \leq z^{p-1} \int|f|^{p} d \mu+\left.z^{p-1} \int \lg \right|^{p} d \mu<\infty$\\ $\therefore f+g \in L(\Omega, F, \mu)$\\ Assariy, $\|f+g\|_{p}>0$ and $p>1$ and $p, z$ congyotes then\\ $\left\|\left.f_{f+g}\right|^{r^{-1}}\right\|_{q}=\left[\int\left(f_{f}\right]^{(f-)} q_{q}\right]^{\frac{1}{2}}$\\ $\left[\int|i+g|^{p} d \mu\right] \frac{t-1}{r}$\\ $\left\|f^{+} J\right\|_{p}^{+-1}$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_244_2122_19311_132}\\ Ulfeglis?\\ $+\|q\|_{+}\left\|p_{t y} p^{p^{-1}}\right\|_{2}$\\ $\|f\|_{p}\|\mathrm{Arg}\|_{p}^{+}+\|\mathrm{g}\|_{p}^{-}\|\mathrm{Alg}\|_{1}^{+}$\\ $\|f+g\|_{f}^{[r-1]}$\\ Theorem (Apper in $c^{p}$ spout)\\ Let $(\Omega, \mathcal{F}, \mu)$ an a reaste space, $A \Omega$ :\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_309_2320_20659_44} \begin{tabular}{l} $-d A_{i} \in A_{\text {s.t. }} A_{i} \lambda \Omega$ \\ \hline \end{tabular} For $p \in[1, \infty), V_{0} \subset L^{p}$ and $\forall f \in L^{p}, \forall z>0 \quad \exists \in V_{0}$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_377_2321_21520_44}\\ $\mu(A)^{\frac{1}{c}}<\Delta$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_421_2321_21984_44}\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_465_2216_22565_31}\\ $\left\|(f+g)-\left(v_{f}+v_{y}\right)\right\|_{p} \leq\left\|f-v_{f}\right\|_{p}+\left\|_{q}-v_{y}\right\|_{p}<2 \varepsilon$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_575_1769_23465_88}\\ We have $A \subset \mathcal{L}$ ad ∴ $\Omega \in \mathcal{Z}{ }_{\text {for }}$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_266_1305_24260_220}\\ Let $A=\bigcup_{j=1}^{\infty} A_{i}, G_{j}=\bigcup_{j=1}^{J} A_{i}$\\ Then $\varepsilon_{j} \uparrow A$ and $\left\|\frac{1}{A}-n_{B_{j}}\right\|_{i}=\Gamma\left(A \backslash B_{j}\right)^{\frac{1}{p}} \longrightarrow 0$\\ $\Rightarrow \mathcal{L}$ is $-\lambda$-system\\ ⇒ Pymin $\pi-\lambda$ says $\mathcal{F}=\sigma(A) \leq z$\\ Now for am ron-regative $f \in L^{+}$, we construt suple\\ fn $=$min $\left[n, i^{-n}\right]$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-5_355_2321_26138_44}\\ and $\mid f-$ m $\left._{n}\right|^{p} \leq|f|^{p} \leq$ bound \begin{itemize} \item By Domint-al convegerres $\left(f-f_{n} \| p-\left[\int\left|f-f_{n}\right|^{p} d \mu\right]^{\bar{P}} \rightarrow 0\right.$ \end{itemize} Lasty, for guered $\Omega \notin A, L_{4}$ assumption $A_{1} \uparrow \Omega$\\ and $|f-f|_{A} \mid p \rightarrow 0$ pointairse and $\left.|f-f|_{A i}\right|^{p}|f|^{p} \therefore\left\|f-f p_{A}\right\|_{P}$ and $\left.|f-f|_{A i}\right|^{P} \leq|f|^{P}$ \section*{Lecture 10: Convergence of Measure} Weale convergence of measure \begin{center} \begin{tabular}{|l|l|} \hline \multicolumn{2}{|l|}{$(\Omega, \neq)$ be a messurble space $\left\langle A_{i} S_{i=1}^{\infty}\right.$ a saq of prob medures s.t. $\mathbb{P}_{1}: \mathcal{F} \rightarrow \mathbb{R}^{+}$} \\ \hline \multicolumn{2}{|l|}{$Q:$ What does $\mathbb{P}_{i} \rightarrow \mathbb{P}$ mean?} \\ \hline \multicolumn{2}{|l|}{\begin{tabular}{l} e.g. Maybe we want $\mathbb{P}_{i}(A) \rightarrow \mathbb{P}(A) \forall A \in \neq$ ? \\ $\uparrow$ \\ , \\ \end{tabular}} \\ \hline \multicolumn{2}{|l|}{\multirow[b]{2}{*}{Let $s$ be $a$ metric space $\rho$ be the Bord $\sigma$-fierd on $s$}} \\ \hline & \\ \hline \multicolumn{2}{|c|}{\begin{tabular}{l} Then, we write $\mathbb{P}_{i} \Rightarrow \mathbb{P}$ for wead annegerves if $\int f d \mathbb{P}_{i} \rightarrow \int f d \mathbb{P}$ \\ $\forall f \in C_{B}^{r}(\mathbb{R})$, all continuous bounded funtions $S \rightarrow \mathbb{R}$ \\ \end{tabular}} \\ \hline \multicolumn{2}{|c|}{$d: s \times s \rightarrow R^{+}$} \\ \hline if [ $\mathbb{P}_{3}$ ] converges then $\mathbb{R}$ prosusely, for a finite collection & \begin{tabular}{l} $\_\_\_\_$ \\ thin \\ \end{tabular} \\ \hline an $\varepsilon$-reighborhand, any $\varepsilon>0$, of $P$ to $e$ all $\mathbb{Q}$ Q & \\ \hline \(\left|\int f_{i} d t-f_{f i} d Q\right|<\varepsilon \quad \theta_{i}=1, \ldots\) & \(\binom{Q_{0}}{g^{R}}\) \(\cdot^{\mathbb{R}}\) \\ \hline \end{tabular} \end{center} \begin{center} \begin{tabular}{|l|} \hline Theorem: (Portmantear) \\ \hline Proof: (1) ⇒(2). If convergence holds $\forall f \in C_{\beta}(\mathbb{R})$ then it holds for $f \in C_{B}(\mathbb{R})$ that are also uniformy con 17 $(2) \rightarrow(3)$. \\ \hline \\ \hline \begin{tabular}{l} ∴ tabe limsup and $\varepsilon \downarrow 0$ \\ $\limsup \mathbb{R}_{i}(c) \leq \mathbb{P}(c)$ \\ \end{tabular} \\ \hline \begin{tabular}{l} (3) ⇒ (1) Let $f \in C_{B}(\mathbb{R})$. hoal is to show limsup $\int f d \mathbb{P} i \leq \int f d \mathbb{P}$ and similarly for limint: \\ $f$ is bounded by assumption $\therefore$ we can shift and scile it whoc assure $00$, \\ \end{tabular} \\ \hline \\ \hline \end{tabular} \end{center} \begin{center} \begin{tabular}{|l|} \hline \(\mu\left(\left\{\omega \in \Omega: d\left(X_{i}(\omega) ; X(\omega) ; \tau\right\}\right) \rightarrow 0\right.\) \\ \hline In short, $\mathbb{P}\left(d\left(x_{1}, x\right)>\varepsilon\right) \rightarrow 0$. Convergence in posberility is closefy recated to $x$ Convergencie Almost Survely \\ \hline \(x_{i} \xrightarrow{a, s} x \quad \text { if } \mu\left(\left[\omega \in \Omega: x_{i}(\omega) \rightarrow x(\omega)\right]\right)=1\) \\ \hline i.e. pointaite onergence almost everyobtere/ surely andayst. robabilist \\ \hline \(\mu\left(\left\{\omega \in \Omega: x_{i}(\omega) \nrightarrow x(\omega)\right\}\right)=0\) \\ \hline Noter: Hu rettir $d$ does not apper here Convergence $L L^{P}$ \\ \hline \(x_{i}^{L P} x, \mathbb{E}\left[d\left(x_{i} ; x\right)^{p}\right]=\int_{\Omega} d \underbrace{\left(x_{i}(\omega), x(\omega)\right)}_{\text {finfor }})_{\Omega \rightarrow R^{p}}^{p} \cdot d_{\mu}(\omega) \rightarrow 0\) \\ \hline \(\text { if } \rho=\mathbb{R} \text { then } \int\left|x_{i}-x\right|^{p} d \mu \rightarrow 0\) \\ \hline Hieviarchy of Convegerve \\ \hline \end{tabular} \end{center} Conv a.s ⇒ conv prob\\ conv prob → conv dist any $p \in[1, \infty]$, conv $L^{p} \Rightarrow$ conv prob\\ But convegarie $9.9 . \longleftrightarrow$ conv $L^{p}$\\ Borel - Contelli Lemmas\\ $\frac{\text { Borel-Contelli Lemmas }}{\text { Let }(\Omega, F, \mu) L e \text { a probability space }\left\{A_{i}\right\}_{i=1}^{\infty}, A_{i} \in Z}$\\ them\\ $\therefore \liminf A_{i}=\bigcup_{j=1}^{\infty} a_{j>i} A_{j}$\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-6_263_2289_17849_34} → we also say $A_{i}$ everaltuly", $A_{i}$ ev. for limitot $A_{i}$\\ because $\exists w \in \mathbb{N}$ s.t. $\forall n \geqslant N \quad w \in A_{n}$\\ Theorem (1 $1^{\text {st }}$ Borel-Contelii)\\ Let $\left\{A_{i}\right\}_{j=1}^{\infty}$ with $A_{i} \in F$ if $\Sigma_{i=1}^{\infty} \mu\left(A_{i}\right)<\infty$ then $\mu\left(\right.$ mimspep $\left.A_{i}\right)=0$\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-6_228_2271_18652_0} Proof: As\\ as $\begin{aligned} \therefore \mu \rightarrow \infty\left(\limsup A_{i}\right) & =\mu\left(\bigcap_{i=1}^{\infty} \cup A_{i}\right) \\ & \leq \mu\left(\bigcup_{j>i} A_{i}\right) \\ & \leq \sum_{j>i} \mu\left(A_{i}\right) \rightarrow 0 \text { as → } \square\end{aligned}$ \begin{center} \begin{tabular}{|l|l|} \hline Thorem $\left(2^{\text {rt }}\right.$ Bord-Cantellit Iomm $)$ & \\ \hline Let $\left\{A_{i}\right\}_{i=1}^{\infty}$ be redepreduct and $A_{i} \in \mathcal{F}$. Then $A_{i=1}^{\infty} \sum_{i=1}^{\infty}\left(A_{i}\right)=\infty$ & \\ \hline then $\mu\left(\right.$ cims $\left.p_{1}, p_{1}\right)=1$ & \\ \hline Prod: Note thet $1-t \leq e^{-t}, \forall t \in \mathbb{R}$ & Ove con chech that if $\left\{A_{1}\right\}_{i}^{\infty}=1$ are \\ \hline independent then $\left[A_{i}^{c}\right]_{i}^{\infty}$ ore independent & \\ \hline - for any $i \in \mathbb{N}$ and $k \geqslant 1$ & \(\begin{aligned} \mu\left(\prod_{j=1}^{k} A_{j}^{c}\right)^{\prime} & =\pi\left[1-\mu\left(A_{j}^{i}\right)\right] \\ & \leq \exp \left[-\sum_{j}^{k} \mu\left(A_{j}\right)\right] \end{aligned}\) \\ \hline & \\ \hline Take $K \rightarrow \infty$ and $R H S \rightarrow 0$ & \\ \hline \(\begin{aligned} \therefore \mu\left(\bigcap_{j A^{c}}^{c}\right) & =0 \quad \forall i \\ \therefore \mu\left(\limsup A_{i}\right) & =\mu\left(\bigcup_{i=1}^{\infty} \nu_{j i} A_{j}\right) \\ & =1_{-\mu\left(\bigcup_{i=1}^{\infty} A_{j}^{c} A_{j}^{c}\right)}=1 \end{aligned}\) & \\ \hline \end{tabular} \end{center} Lecture II: The story Law of Lage Number $01 / 05 / 26$ Let $\left\{x_{i}\right\}_{j=1}^{\infty}$ be restern variables from $(\Omega, F, \mathbb{P})$ to $(\mathbb{R}, B)$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-7_169_812_338_33} \begin{itemize} \item $\mathbb{P}(x \in A)=\mathbb{P}\left(\sum \omega G \Omega: x(\omega) \in A()\right.$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-7_440_1454_743_287}\\ $E X=\int x(0) d \mathbb{R}$\\ $S_{n}=\sum_{n} x_{n}$\\ Defrition (todesendence)\\ $x$ and $y$ on the same polabolitity space $(\Omega, F, \mathbb{P})$ wit with possibly different $(x, x)$ and $(y, y)$. \end{itemize} \begin{center} \begin{tabular}{|l|} \hline Then we say that $x$ all $y$ are indepindent if $\mathbb{P}(\{x \in A\} \cap\{y \in B))=\mathbb{P}(x \in A) \mathbb{P}(y \in B) \quad \forall A \in \mathbb{X}$ and $B \in \mathcal{Y}$ \\ \hline This con be extardel to finite overations $\left[x_{i}\right\}_{i=1}^{\wedge}$ with \\ \hline - Also, $\left\{x_{i}\right\}_{i=1}^{a}$ s independent if every finite set of $X_{i}$ 's is independent → similor to what me saw for j-freble \\ \hline Then $x$ and $\varphi$ ore solependert if and only if $\sigma$-firely $\sigma(x)$ and $\sigma(y)$ are molepredult. \\ \hline Identically Distributed "you want the RV's to have the same distribution \\ \hline \\ \hline Theorem (Weal las of lage numbers) \\ \hline het $(\Omega, F ; 1, P)$ be a probability space, $\left\{x_{i}\right\}_{i=1}^{\infty}$ se renotom vateles from $\Omega \rightarrow \mathbb{R}$ s.t. $\mathbb{E} X_{i}=c \in \mathbb{R}$ and $\mathbb{E} X^{2}=1 \quad \forall i=1, a$ \\ \hline and $\mathbb{4}\left[\left(x_{i}-c\right)\left(x_{j}-c\right)\right]=0 \quad \forall i \neq j$ Then $\frac{S_{n}}{n} \xrightarrow{\mathbb{R}} c$ in porbability\includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-7_427_657_5415_1618} \\ \hline Proot: $w \log c=0$, therwise replace $x_{i}$ with $x_{i}=c$ Then for any $t>0$, Chelysher says, \\ \hline \\ \hline \(\mathbb{P}\left(\frac{\left|S_{n}\right|}{n} \geqslant t\right) \leq \frac{\mathbb{E} S_{n}^{2}}{t^{2} n^{2}}=\sum_{1, j=1}^{n} \frac{\mathbb{E}\left[x_{i} x_{j}\right]}{t^{2} n^{2}}=\frac{1}{n t^{2}} \rightarrow 0\) \\ \hline In the rext theorm, me require independent $X_{1}$ 's' me also need the voriance \(V_{o r}(x)=\int(x-\mathbb{E} x)^{2} d \mathbb{P}(\omega)\) \\ \hline Thomem (Strong Loge Nonbers) \\ \hline het $\left\{x_{i}\right\}_{i}^{\infty}=$ rentom veriables from $\Omega \rightarrow \mathbb{R}$, \\ \hline \begin{tabular}{l} If $\mathbb{E}\left|x_{i}\right|<\infty$, then $\frac{S_{n}}{n} \xrightarrow{\text { a.s. }} c$ for $c=\mathbb{E} x_{1}$ (a) - Also, if $E\left|X_{i}\right|=\infty$, then $\frac{S_{n}}{n}$ does not converge to\includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-7_299_351_8004_1992} \\ finite limit. ${ }^{(2)}$ \\ \end{tabular} \\ \hline \\ \hline Proof: (2) Assume $n^{-1} S_{n} \rightarrow C \in \mathbb{R}$ att afo $\mathbb{E}\left|X_{1}\right|=\infty$ Note that $\frac{x_{n}}{n}=\frac{S_{n}-S_{n-1}}{n} \rightarrow 0$ \(\frac{S_{n}}{n}-\frac{S_{n-1}}{n} \rightarrow c-c=0\) \\ \hline Since $\mathbb{E}\left|x_{i}\right|=\infty$ then $\sum_{n=0}^{\infty} \mathbb{P}\left(x_{i}>n\right)=\infty$, twe Borel - cartell: \\ \hline says that $\left|x_{n}\right|>n$ for 10 . Thus: $\mathbb{P}\left(\left\{\omega \in \Omega: \frac{S_{n}-S_{n-1}}{n} \rightarrow 0\right\}\right)=0$ manituely often \(\therefore n^{-1} S_{n}+c \Rightarrow \mathbb{R}\)\includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-7_325_487_9699_1822} \\ \hline (1) Assume $\mathbb{E} x_{i}=c \in \mathbb{R}$ - wilog $x_{1} \geqslant 0 \quad \theta_{1}$ else write $x=x^{+}-x^{-}$ and do everything for $x^{+}, x^{-}$ \\ \hline \\ \hline Also, independence of $x, y$ implies Independence of $x^{t}$ and $\varphi^{t}$ Also, $F$ devotes the low of $X$ i.e $F(x)=\mathbb{P}(X \leq x)$ \\ \hline \\ \hline \\ \hline \\ \hline \(\begin{aligned} & \sum_{n=1}^{\infty} k_{n}^{-2} \mathbb{1}_{k n \geq a} \leq 4 \sum_{n=1}^{\infty} \delta^{-2 n} \mathbb{1}_{\delta^{n} \geq i} \leq \frac{4}{2^{2}\left(1-f^{-2}\right)} \leq c_{0} i^{-2} c^{-2} \\ & \text { for Some } c_{0}>0 \end{aligned}\) \\ \hline \end{tabular} \end{center} $\sum_{i=k+1}^{\infty} i^{2}<\int_{k}^{-1} x^{-2} d x=\frac{1}{k}$\\ Now, for any $t>0, \exists c>0$ depereling ony on $t$ and $\delta$ s.t.\\ $\sum_{n=1}^{\infty} \mathbb{P}\left(\left|T_{k_{n}}-\mathbb{E} T_{k_{n}}\right|>+k_{n}\right) \leq c_{1} \sum_{n=1}^{\infty} k_{n}^{-2} \operatorname{Var}\left(T_{k_{n}}\right)$\\ $=c_{1} \sum_{n=1}^{\infty} \frac{1}{k_{n}^{2}} \sum_{i=1}^{k_{n}} V_{r}\left(Y_{i}\right)$\\ $=c_{i}^{\infty} \sum_{i=1}^{\infty}\left[\begin{array}{ll}V_{i}-\left(y_{i}\right) & \sum_{k_{n} ?} \\ k_{n}^{2}\end{array}\right]$\\ $\leq c_{2} \sum_{1}^{\infty} c^{-2} \mathbb{E} Y_{1}^{2}$\\ $=c_{i} \sum_{i=1}^{\infty}-2 \int_{0}^{\infty} x^{2} d F(x)$\\ $\left.=c_{2} \sum_{i=1}^{n} \sum_{n=0}^{i-1} \int_{k}^{k+1} x^{2} d F(x)\right\}$\\ $\leq c_{3} \sum_{k=0}^{\infty} \frac{1}{k+1} \int_{k}^{k+1} x^{2} d F(x)$\\ $\leq c_{3} \sum_{k=0}^{n} \int_{k}^{k+1} x d F(x)$\\ $\leq c_{3} \sum_{k=0}^{\infty} e^{-} x_{i}<\infty$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-7_423_863_15379_1487} In the we, $\sum_{n=1}^{\infty} \mathbb{R}\left(\left|T_{m}-\varepsilon_{T_{m}}\right| \geqslant \mathrm{Fth}_{n}\right)<\infty$\\ Borel-Cantelli (RC) says $\frac{1}{K_{n}}\left|T_{u_{n}}-\mathbb{E} T_{\text {in }}\right| \xrightarrow{a . s_{n}} 0$ Since $\mathbb{E} Y_{n} \uparrow \mathbb{E} X_{i}$ we have that $\quad$ Ubrip in convergent in $K_{n}^{-1} \mathbb{E} T_{k_{n}} \uparrow \mathbb{E} X_{i}$ as $n \rightarrow \infty \quad$ probability to almost currely $\therefore K_{n}^{-1} T_{k n} \xrightarrow{0 . s} \mathbb{E} X_{i}$\\ To get beel to $S_{n}$, note that for $x, \mathbb{E} X<\infty \Longrightarrow \sum_{i=0}^{\infty} \mathbb{T}$ Then $\sum_{i=1}^{\infty} \mathbb{P}\left(x_{i} \neq y_{i}\right)=\sum_{i=1}^{\infty} \mathbb{P}\left(x_{i}>i\right)<\infty$\\ BC says $\pi\left(\operatorname{limap}\left\{x_{i} \neq y_{i}\right\}\right)=0$\\ Hence, for $z$ longe enough $x_{i}=y_{i}$ a.s.\\ het large enough rean all $i>M(\omega) \left(\right.$ i.e. $\left.x_{i}(\omega)=y_{i}(\omega) \theta_{i}>m(\omega)\right)$\\ Forthermore, $K_{n}^{-1} S_{m(\omega)} \rightarrow 0$ and $K_{n}^{-1} T_{m(\omega)} \rightarrow 0$\\ as $n \rightarrow \infty$ terms's where\\ negigible $$\therefore K_{n}^{-1} S_{K_{n}} \xrightarrow{\text { a.s. }} Z X_{i} \quad \therefore \text { we have almost sire (a.s.) aniegene }$$ Finally, $\frac{k_{n}+1}{k} \rightarrow \delta$ as $n \rightarrow \infty$ $$k_{n} \quad \text { An lorge enough st. } 1 \leq \frac{k_{n+1}}{k_{n}}<\delta^{2}$$ This, for $k_{n}0$ JK compart s.t. $\mu_{i}\left(K_{\varepsilon}\right)>1-\varepsilon$ \\ \hline Theorem (Proborous) $\leftarrow$ couple different versions \\ \hline \\ \hline $\Rightarrow \mu$ to some $\mu$ depe \\ \hline \\ \hline Apposition: \\ \hline If $\left\{\mu_{i}\right\}_{j=1}^{\infty}$ and $\left(\mu\right.$ ore prob reasures st. $\theta_{\text {ik }} \mu_{i_{k}}=\mu$ \\ \hline \multirow{2}{*}{\begin{tabular}{l} Proof: \\ Assume not, then $\exists f t_{c}$ b ret. $\int f d \mu \rightarrow \int f d \mu \exists \varepsilon>0 \quad \exists_{k}$ s.t. $\left(\int f d_{\mu_{k}}-\int f d_{\mu} / 2 \varepsilon \forall \varepsilon\right.$ \\ \end{tabular}} \\ \hline \\ \hline \\ \hline Defn (Gonssi- measire) \\ \hline A Broel measure $\gamma$ on $(\mathbb{R}, T B)$ id said to be Cearston with mean $m$ and voriance $g^{2}$ if \\ \hline $\gamma((a, b])=\frac{1}{\sigma \sqrt{2 \pi}} \int_{a}^{b} \exp \left[-\frac{1}{2 \sigma^{2}}(x-m)^{2}\right] d \lambda(x)$ \\ \hline \multirow{2}{*}{\begin{tabular}{l} Also, for $\sigma=0, \gamma=\delta_{m}$ (Dirac measure) we say $\gamma$ is a deoperente Coussian mesove. \\ degrented Coussion resolve. \\ \end{tabular}} \\ \hline \\ \hline \\ \hline $\gamma$ on $\left(\mathbb{R}^{-1}, \beta\right)$ is Caussian it Ulinem furbions $f: \mathbb{R}^{d} \rightarrow \mathbb{R}$ the rabled nerred $\gamma \circ f^{-1}$ or $(R, \beta)$ is Gaussian. Ary thear combination of Coussion \\ \hline Defn ( $R . V$ ) \\ \hline A RV. Z from $(\Omega, F, \mu)$ to $\left(R^{l}, \beta\right)$ is Causitan if $\gamma:=\mu \cdot Z^{-1}$ is a caussian measure. \\ \hline For rectors $u, v \in \mathbb{R}^{\alpha}$, the inver product $\langle u, v\rangle=\left\{4 v_{i}\right.$ \\ \hline \multirow{2}{*}{\begin{tabular}{l} $141^{2}=\langle 4,4\rangle$ \\ Chereforsistic foretion \\ \end{tabular}} \\ \hline \\ \hline \\ \hline \(\begin{gathered} \tilde{\mu}(\nu):=\int \exp \{i\} d \mu(x) \\ \tilde{r}(\text { to sealling } \\ =\sqrt{1} \end{gathered}\) \\ \hline \\ \hline \\ \hline $p(x)$ is the probability density funtion for $\gamma$ a.e. \\ \hline \begin{tabular}{l} \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-8_136_698_7900_1621} \\ Convolution fintions" \\ \end{tabular} \\ \hline \multirow{3}{*}{\includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-8_598_2308_8148_56} } \\ \hline \\ \hline \\ \hline \\ \hline \\ \hline Also, for indelpendent $C V^{\prime} \backslash X, Y$ with megures $\mu_{\nu} \nu$ X $X Y$ has reduced measure $\mu * \nu$ \\ \hline Theoren (uniqueness of $\sim$ ) \\ \hline Proof : Let $\gamma_{j}$ be a mean zero Gairsia measure a $\mathbb{R}^{d}$ with co-vertance $\sigma^{2} \mathbb{P}_{d}$. \\ \hline Devote $\mu^{(\sigma)}=\mu * \gamma_{0}$ and Same for $\nu^{(\sigma)}$. \\ \hline It cal be shown that the correspondiry sensity functions for $\mu^{(\sigma)}$ and $\nu^{(\sigma)}$ are \\ \hline \multirow{5}{*}{\begin{tabular}{l} $q^{(\sigma)}(u)=\frac{1}{(2 \pi)^{d}} \int \tilde{\nu}(t)$ exp $\left[-i-\frac{1}{2} \sigma^{2}|t|^{2}\right] d l(t)$ \(\begin{aligned} & \text { Then } \mu^{(\sigma)} \text { comer from } x+\sigma z \\ & \therefore x+\sigma z \xrightarrow{a .5} x \text { as ovo} \end{aligned}\) \\ ∴ onv in probability \\ \end{tabular}} \\ \hline \\ \hline \\ \hline \\ \hline \\ \hline \multirow[t]{2}{*}{} \\ \hline \multirow[b]{2}{*}{} \\ \hline \\ \hline \\ \hline \\ \hline Let $S_{n}=\sum_{j=1}^{n} x_{j}$, then $n^{-\frac{1}{2}} S_{n} \rightarrow z$, where $z$ is Caussion \\ \hline \\ \hline \\ \hline \end{tabular} \end{center} \begin{center} \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-8_1658_2338_14547_0} \end{center} \begin{center} \begin{tabular}{|l|l|l|} \hline \multicolumn{3}{|l|}{\begin{tabular}{l} By the prop form above $\mu_{i} \Rightarrow \mu$ \\ 口 \\ \end{tabular}} \\ \hline \multicolumn{3}{|c|}{\multirow{3}{*}{\begin{tabular}{l} $\_\_\_\_$ "Cherafferistic \\ $R v^{\prime} s^{\prime} x_{j} \rightarrow$ no non to \\ cheracterstic funfion of Coursia \\ \end{tabular}}} \\ \hline & & \\ \hline & & \\ \hline \multicolumn{3}{|l|}{\begin{tabular}{l} TLUS Turs \\ $\mathbb{E}\left|n^{-\frac{1}{2}} S_{n}\right|^{2}=\frac{1}{n} \mathbb{E}\left[\sum_{j, k=1}^{\{ }\left\langle x_{j}, x_{a}\right\rangle\right]$ \\ \end{tabular}} \\ \hline \multicolumn{3}{|c|}{"Mator iretion" $=\mathbb{E}\left|x_{j}\right|^{2}$} \\ \hline \multicolumn{3}{|l|}{En any $\varepsilon>0 \quad \exists m_{\varepsilon}>0$ s.t. $\frac{E\left(x_{j}\right)^{2}}{m_{\varepsilon}^{2}}<\varepsilon$} \\ \hline \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-8_210_1118_18001_41} & & \\ \hline \(\mathbb{P}\left(\left|n^{\frac{-1}{2}} \Sigma_{n}\right|>n_{\varepsilon}\right)<\varepsilon\) & \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-8_224_545_18196_1688} & \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-8_266_545_18168_1674} \\ \hline \multicolumn{3}{|l|}{\(\therefore \text { Seq } n^{\frac{-1}{2}} S_{n} \mapsto \quad u .7\)} \\ \hline \multicolumn{3}{|l|}{\includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-8_168_1969_18782_55} with $\mathbb{E}\left\langle v, x_{j}\right\rangle=0, \mathbb{E}\left\langle v, x_{j}\right\rangle^{2}<\infty$} \\ \hline \multicolumn{3}{|l|}{$\sqrt{ }$} \\ \hline $h(0)=1 \nabla L(0)=0 \nabla^{2} h(0)=-f\left[x_{j} x_{j}^{\top}\right]$ \(\text { foren: } B^{2}\) & Geldear Nom & \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-8_196_615_19759_1423} \\ \hline \multicolumn{3}{|c|}{\multirow{3}{*}{\begin{tabular}{l} By Taybor's Thesery, $h(v)=1$ \(-\frac{1}{2} v^{\top} 2^{v} v+o\left(v^{2}\right)\) \\ ∴ for ang fixed v, $\operatorname{Fexp}\left\{i\left\langle n^{-\frac{1}{2}} s_{n, v}\right\rangle\right\}=h\left(n^{-\frac{1}{2}} v\right)^{-}$ \\ \end{tabular}}} \\ \hline \multicolumn{3}{|c|}{} \\ \hline & & \\ \hline \end{tabular} \end{center} \section*{\begin{center} \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_308_1407_571_395} \end{center}} \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_220_1605_747_351}\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_243_1649_966_351} resienting $x$ and $a\left(T^{-1}(A)\right)$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_264_616_1538_351} \begin{itemize} \item set $A e^{\prime} z^{\prime \prime}$ is note: the vilution\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_265_572_1999_395}\\ $\_\_\_\_$ $\forall A \in F$\\ $\_\_\_\_$\\ $f=f \cdot T$\\ $=f(T \cdots)$ f vani (Cengodite)\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_243_770_2724_373} Garres es $(0,1], B, \lambda)$ Subt mas : $T(x)=x+a$ mod $\begin{cases}x+a & x \\ x+a-1, & x+a>1\end{cases}$\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_265_1539_3581_417} $\frac{\text { Fon Farts }}{\text { (i) } 16}$ f $\_\_\_\_$ resolve - proseming\\ $\int f d \mu=\int f . \bar{x} d \mu$ 2) If T as erg $\_\_\_\_$\\ $\_\_\_\_$\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_309_418_4350_1516} Engotic Thorems $\Omega, F$,\\ $\_\_\_\_$\\ $\_\_\_\_$ not me obefiee $S_{n}=S_{n}(f)=f+f$ \end{itemize} Changent\\ $\_\_\_\_$\\ $\_\_\_\_$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_397_1100_6437_21}\\ $\_\_\_\_$\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_242_1824_6899_43} Samemo a\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_287_1231_7404_615}\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_330_1605_7866_307}\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_463_1979_8217_87} D - scortant\\ $\_\_\_\_$\\ $\_\_\_\_$ Tuile $\int_{0,0} f d_{0}=\ln \iint_{0}\left(d_{0}\right)>0$\\ $\Delta_{10} \Delta_{10}+\Delta_{2}+\psi_{11}$\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_265_1451_9975_0} $\_\_\_\_$ ) calmost areajo spended\\ $\_\_\_\_$\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_242_2287_10371_43} $\int|\bar{f}| d_{p}\left|\leq \int\right| \bar{f} \mid d_{p}$ and $\frac{S(E)}{\lambda} \rightarrow \bar{f}$\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_243_2088_10942_0} I whand, $a^{-1}$ \href{http://S.Cf}{S.Cf}. T $=\left[\frac{S_{n+1}(E)-f}{n}\right] =\left(\frac{N+1}{N}\right) \frac{S_{n-}(C)}{N+1}-\frac{f}{N}$\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_264_946_11997_65} $D_{a, b}=\left\{\omega \in \Omega: \lim _{n \rightarrow \infty} n\right\}$ 'S. Cf $c a\mathrm{N} \left\|\frac{H_{s}(t)}{n}-\bar{f} U_{p} \leq\right\| \frac{S_{s}}{n}(f-g)\left\|_{p}+\right\| \frac{S_{n}}{n}(g)-\bar{J}\left\|_{p}+\right\| \bar{F}-\overline{H_{p}}$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_332_2334_22741_20}\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_287_2313_23092_41} tF ,.. $\quad d F(A)=\int \frac{1}{A} \mu \mathrm{~F}$\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_352_2177_23840_43} $\rho=\sigma(N)$ were $\left.A=\sum_{n=1}^{\pi_{n}}: A_{n} \in B \forall_{n}, A_{n}=\mathbb{R}\right\}$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_395_2286_24719_65}\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_331_2143_25159_38}\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_286_1496_25532_43} Theam (sclew)\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_335_2142_26019_38} Prove: Prove: not $f: \mathbb{R}^{2} \sim \mathbb{R}$\\ \includegraphics[max width=\textwidth, alt={}, center]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_352_2045_27004_87}\\ \includegraphics[max width=\textwidth, alt={}]{29c59e08-e494-45b8-8250-1c6bdf808a29-9_287_1386_27333_43} $\int F d x=\ln _{n \times m}\left(\int_{n}-\int_{n}(6) d x=\int f d x\right.$ \end{document}