From 006b2407feac90030ad12c960d050d22ddfca1ef Mon Sep 17 00:00:00 2001
From: Morten Hjorth-Jensen <morten.hjorth-jensen@fys.uio.no>
Date: Mon, 11 Sep 2023 07:03:15 +0200
Subject: [PATCH] typo

---
 .../_build/.doctrees/environment.pickle       | Bin 306200 -> 307151 bytes
 .../_build/.doctrees/exercisesweek37.doctree  | Bin 20115 -> 20109 bytes
 .../html/_sources/exercisesweek37.ipynb       |  45 +++++++++---------
 .../_build/html/exercisesweek37.html          |   3 +-
 doc/LectureNotes/_build/html/searchindex.js   |   2 +-
 .../jupyter_execute/exercisesweek37.ipynb     |  45 +++++++++---------
 doc/LectureNotes/exercisesweek37.ipynb        |  45 +++++++++---------
 doc/src/week37/exercisesweek37.do.txt         |   3 +-
 8 files changed, 69 insertions(+), 74 deletions(-)

diff --git a/doc/LectureNotes/_build/.doctrees/environment.pickle b/doc/LectureNotes/_build/.doctrees/environment.pickle
index 697029a4d3bf6e8cf85050efd33f49eee7d1d539..92992074df7f8b35fe5d3c07b5b50a37b399e308 100644
GIT binary patch
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     "$$\n",
-    "\\mbox{Var}[\\boldsymbol{\\beta}^{\\mathrm{Ridge}}]=\\sigma^2[  \\mathbf{X}^{T} \\mathbf{X} + \\lambda \\mathbf{I} ]^{-1}  \\mathbf{X}^{T} \\mathbf{X} \\{ [  \\m\\\n",
-    "athbf{X}^{\\top} \\mathbf{X} + \\lambda \\mathbf{I} ]^{-1}\\}^{T},\n",
+    "\\mbox{Var}[\\boldsymbol{\\beta}^{\\mathrm{Ridge}}]=\\sigma^2[  \\mathbf{X}^{T} \\mathbf{X} + \\lambda \\mathbf{I} ]^{-1}  \\mathbf{X}^{T}\\mathbf{X} \\{ [  \\mathbf{X}^{\\top} \\mathbf{X} + \\lambda \\mathbf{I} ]^{-1}\\}^{T},\n",
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diff --git a/doc/LectureNotes/_build/html/exercisesweek37.html b/doc/LectureNotes/_build/html/exercisesweek37.html
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--- a/doc/LectureNotes/_build/html/exercisesweek37.html
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@@ -496,8 +496,7 @@ A given parameter <span class="math notranslate nohighlight">\(\beta_j\)</span>
 <p>Show also that the variance is</p>
 <div class="math notranslate nohighlight">
 \[
-\mbox{Var}[\boldsymbol{\beta}^{\mathrm{Ridge}}]=\sigma^2[  \mathbf{X}^{T} \mathbf{X} + \lambda \mathbf{I} ]^{-1}  \mathbf{X}^{T} \mathbf{X} \{ [  \m\
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+\mbox{Var}[\boldsymbol{\beta}^{\mathrm{Ridge}}]=\sigma^2[  \mathbf{X}^{T} \mathbf{X} + \lambda \mathbf{I} ]^{-1}  \mathbf{X}^{T}\mathbf{X} \{ [  \mathbf{X}^{\top} \mathbf{X} + \lambda \mathbf{I} ]^{-1}\}^{T},
 \]</div>
 <p>and it is easy to see that if the parameter <span class="math notranslate nohighlight">\(\lambda\)</span> goes to infinity then the variance of Ridge parameters <span class="math notranslate nohighlight">\(\boldsymbol{\beta}\)</span> goes to zero.</p>
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class=\"section-number\">3. </span>Linear Regression","<span class=\"section-number\">14. </span>Building a Feed Forward Neural Network","<span class=\"section-number\">15. </span>Solving Differential Equations  with Deep Learning","<span class=\"section-number\">16. </span>Convolutional Neural Networks","<span class=\"section-number\">17. </span>Recurrent neural networks: Overarching view","<span class=\"section-number\">4. </span>Ridge and Lasso Regression","<span class=\"section-number\">5. </span>Resampling Methods","<span class=\"section-number\">6. </span>Logistic Regression","<span class=\"section-number\">8. </span>Support Vector Machines, overarching aims","<span class=\"section-number\">9. </span>Decision trees, overarching aims","<span class=\"section-number\">10. </span>Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods","<span class=\"section-number\">11. </span>Basic ideas of the Principal Component Analysis (PCA)","<span class=\"section-number\">13. </span>Neural networks","<span class=\"section-number\">7. </span>Optimization, the central part of any Machine Learning algortithm","<span class=\"section-number\">12. </span>Clustering and Unsupervised Learning","Exercises week 34","Exercises week 35","Exercises week 36","Exercises week 37","Applied Data Analysis and Machine Learning","<span class=\"section-number\">2. </span>Linear Algebra, Handling of Arrays and more Python Features","Project 1 on Machine Learning, deadline October 9 (midnight), 2023","Teaching schedule with links to material","<span class=\"section-number\">1. </span>Elements of Probability Theory and Statistical Data Analysis","Teachers and Grading","Textbooks","Week 34: Introduction to the course, Logistics and Practicalities","Week 35: From Ordinary Linear Regression to Ridge and Lasso Regression","Week 36: Statistical interpretation of Linear Regression and Resampling techniques","Week 37: Statitsitcal interpretations and Resampling 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class=\"section-number\">3. </span>Linear Regression","<span class=\"section-number\">14. </span>Building a Feed Forward Neural Network","<span class=\"section-number\">15. </span>Solving Differential Equations  with Deep Learning","<span class=\"section-number\">16. </span>Convolutional Neural Networks","<span class=\"section-number\">17. </span>Recurrent neural networks: Overarching view","<span class=\"section-number\">4. </span>Ridge and Lasso Regression","<span class=\"section-number\">5. </span>Resampling Methods","<span class=\"section-number\">6. </span>Logistic Regression","<span class=\"section-number\">8. </span>Support Vector Machines, overarching aims","<span class=\"section-number\">9. </span>Decision trees, overarching aims","<span class=\"section-number\">10. </span>Ensemble Methods: From a Single Tree to Many Trees and Extreme Boosting, Meet the Jungle of Methods","<span class=\"section-number\">11. </span>Basic ideas of the Principal Component Analysis (PCA)","<span class=\"section-number\">13. </span>Neural networks","<span class=\"section-number\">7. </span>Optimization, the central part of any Machine Learning algortithm","<span class=\"section-number\">12. </span>Clustering and Unsupervised Learning","Exercises week 34","Exercises week 35","Exercises week 36","Exercises week 37","Applied Data Analysis and Machine Learning","<span class=\"section-number\">2. </span>Linear Algebra, Handling of Arrays and more Python Features","Project 1 on Machine Learning, deadline October 9 (midnight), 2023","Teaching schedule with links to material","<span class=\"section-number\">1. </span>Elements of Probability Theory and Statistical Data Analysis","Teachers and Grading","Textbooks","Week 34: Introduction to the course, Logistics and Practicalities","Week 35: From Ordinary Linear Regression to Ridge and Lasso Regression","Week 36: Statistical interpretation of Linear Regression and Resampling techniques","Week 37: Statitsitcal interpretations and Resampling Methods"],titleterms:{"1":[0,15,16,17,18,21,26,27],"10":[],"11":[],"12":[],"13":[],"14":29,"15":[],"16":[],"17":[],"18":[],"19":[],"2":[0,15,16,17,18,26,27],"20":[],"2021":[],"2022":[],"2023":[21,24],"21":[],"22":[],"23":[],"24":[],"25":[],"26":[],"27":[],"28":[],"29":[],"3":[0,15,16,26,27],"30":[],"31":27,"34":[15,26],"35":[16,27],"36":[17,28],"37":[18,29],"38":[],"39":[],"4":[0,27],"40":[],"41":[],"4155":[],"42":[],"43":[],"44":[],"45":[],"46":[],"47":[],"5":0,"6":[],"7":28,"8":[],"9":21,"case":[8,10,23,27,28],"do":[1,26,28,29],"final":[12,27,28],"function":[0,1,6,7,8,10,11,12,13,21,23,26,27,28,29],"import":[5,20,26,27],"new":[4,28,29],A:[0,1,4,8,9,26,28,29],And:[26,27,28],In:24,Ising:6,The:[0,1,2,3,5,6,7,8,9,11,12,17,19,26,27,28,29],To:[26,27],With:[4,28],about:[26,27],abov:28,activ:[1,12,28],actual:[],ad:[0,6,17,21,26,27],adaboost:10,adagrad:13,adam:13,adapt:10,adjust:1,adversari:4,again:[3,9],ai:26,aim:[8,9,17,18,26],aka:[26,27],algebra:[20,26],algorithm:[9,10,11,12,27],algortithm:13,all:8,an:[0,4,10,26],analys:[5,27],analysi:[0,5,6,11,19,21,23,26,27,28,29],analyt:[0,16,17],ani:13,anoth:[9,28,29],appli:19,approach:[0,8,14,26,29],approxim:12,architectur:1,arrai:[20,26],assist:24,assumpt:[28,29],august:27,autocorrel:23,autograd:[2,13],automat:13,b:[17,21],back:[1,11,12],background:[19,21,29],bag:10,base:[13,29],basic:[0,5,7,9,10,11,20,27,28,29],batch:1,bay:[5,28,29],befor:11,beta:[28,29],better:8,bia:[6,21,29],binari:1,bind:26,binomi:[],bird:10,block:[],boldsymbol:[27,28,29],boost:10,bootstrap:[6,10,29],boston:[0,27],breast:1,brief:[26,29],bring:12,build:[1,3,9],c:[21,26],calcul:27,can:[26,29],cancer:[1,7,9,11],cart:9,center:27,central:[13,19,23,29],chain:12,chang:10,channel:26,chi:[0,26],choos:1,cifar01:3,classic:11,classif:[1,9,10],classifi:8,clip:1,cluster:14,cnn:3,code:[0,1,2,5,9,11,12,13,14,26,27,28,29],collect:[1,3],commun:26,compar:[2,10],comparison:28,complet:27,complex:[0,6,21,27],complic:6,compon:11,comput:9,computation:29,computerlab:26,con:9,concept:23,condit:[28,29],confid:29,conjug:13,continu:[],contn:26,convex:[8,13],convolut:[3,12],correctli:[28,29],correl:[11,27],cost:[1,10,27,28,29],cours:[19,25,26],covari:[5,11,23,27],cover:26,cross:[6,21,29],cumul:[],cython:26,d:21,data:[0,1,3,6,7,9,11,15,16,19,21,23,26,27],dataset:[1,3],deadlin:[21,26],decai:2,decis:[9,10],decomposit:[5,11,17,20,27],deep:[1,2],defin:[1,26],definit:[],degre:[0,27],deliveri:21,delta:29,demonstr:[],dens:[0,26],deriv:[5,12,27,28,29],descent:[2,10,13],descript:21,design:27,detail:[3,26],develop:1,deviat:[],diagon:11,dice:[],differ:8,differenti:[2,13],diffus:2,dimension:[2,3,8,21,27],disadvantag:9,discret:23,disguis:[],distribut:[5,23,28,29],distrubut:[28,29],doe:[27,28],domain:23,down:1,dropout:1,e:21,economi:27,electron:21,element:[0,23,26],elimin:20,energi:26,ensembl:10,entropi:9,environ:[0,15,26],equat:[0,2,12,26,27,28],error:[0,10,26,27,29],essenti:26,estim:[28,29],etc:26,euler:2,evalu:1,event:[],exampl:[0,1,2,3,4,6,7,8,9,10,26,27,28,29],exercis:[0,6,15,16,17,18,26,27,29],expect:[18,23,28,29],expens:29,experi:23,explor:[0,15,16,26],exponenti:2,express:[17,18,26,27],extrapol:4,extrem:[10,26],ey:10,f:21,fall:24,famili:[1,26,27],famou:20,fantast:27,featur:[9,20,27],feed:[1,12],find:29,fine:1,first:[4,12,26,27,28],fit:[0,10,26,28],fix:27,fold:29,forc:3,forest:10,format:[21,26],forward:[1,2,12],fourier:3,frank:[6,21,27],freedom:[0,27],frequent:27,frequentist:[0,26],from:[5,10,12,27,28,29],full:2,further:[3,5,27],fy:[],g:21,gan:4,gaussian:20,gd:13,gener:[4,9,26],geometr:11,gini:9,good:[0,26],grade:[24,26],gradient:[1,2,10,13],growth:2,ha:19,handl:[20,26,27],happen:[28,29],have:26,heard:26,hessian:27,hidden:2,histogram:29,hous:[0,27],how:[],hyperparamet:1,hyperplan:8,i:1,id3:9,idea:11,ident:[28,29],identifi:29,ii:26,iid:[28,29],illustr:28,implement:1,implic:[5,27],improv:1,includ:13,increment:11,independ:[28,29],index:9,inform:24,input:2,instal:[19,21,26],instructor:24,intercept:27,interpret:[5,11,26,27,28,29],interv:29,introduc:[11,13,27],introduct:[0,6,19,20,21,26],invers:[5,20,28],invert:27,invok:28,iter:10,its:27,jackknif:[],jacobian:27,jax:13,julia:26,jungl:10,k:29,kera:[1,3],kernel:[8,11],lagrangian:8,lasso:[5,6,21,27,28,29],last:[27,29],later:[5,27],layer:[1,2,3,12],learn:[0,1,2,11,13,14,15,16,19,21,26,27,28,29],least:[5,6,18,21,26,27,28],lectur:[26,27,28,29],level:10,librari:[19,26],likelihood:[7,28,29],limit:[1,13,23,29],linear:[0,8,13,20,26,27,28],link:[5,11,22,25,27,28,29],literatur:21,logist:[7,26],loss:27,lu:20,machin:[0,8,13,19,21,26],made:[28,29],mai:26,main:23,make:[0,9,10,15,16,26,27],mani:[10,12],manipul:27,margin:[28,29],mass:26,materi:[22,26,27,28,29],math:[5,27],mathemat:[3,5,8,27],matric:[5,20,26,28],matrix:[1,5,11,12,20,26,27,28],matter:[0,26],max:27,maximum:[28,29],mean:[0,26,27,28],meet:[5,10,23,26,27],mercer:8,mersenn:[],method:[6,9,10,13,21,29],midnight:21,min:27,minim:26,ml:26,mle:[28,29],mlp:12,mnist:[3,4],model:[0,1,4,6,12,26],moment:[],momentum:13,moon:[8,9],more:[3,6,20,21,26,27,28,29],multila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\ No newline at end of file
diff --git a/doc/LectureNotes/_build/jupyter_execute/exercisesweek37.ipynb b/doc/LectureNotes/_build/jupyter_execute/exercisesweek37.ipynb
index 9fe8aa4ac..f5cfe5ddf 100644
--- a/doc/LectureNotes/_build/jupyter_execute/exercisesweek37.ipynb
+++ b/doc/LectureNotes/_build/jupyter_execute/exercisesweek37.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "28222517",
+   "id": "ebfc874e",
    "metadata": {
     "editable": true
    },
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c7ffd7b0",
+   "id": "8ecf95b0",
    "metadata": {
     "editable": true
    },
@@ -27,7 +27,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f687d0b0",
+   "id": "7940e437",
    "metadata": {
     "editable": true
    },
@@ -45,7 +45,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b0b5ae03",
+   "id": "964cf4c4",
    "metadata": {
     "editable": true
    },
@@ -57,7 +57,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a5442d69",
+   "id": "bc8b093a",
    "metadata": {
     "editable": true
    },
@@ -68,7 +68,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d9ac69f5",
+   "id": "bc1907b5",
    "metadata": {
     "editable": true
    },
@@ -80,7 +80,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6f42da1d",
+   "id": "c7d29897",
    "metadata": {
     "editable": true
    },
@@ -90,7 +90,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5690cef0",
+   "id": "e45dbe57",
    "metadata": {
     "editable": true
    },
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3834fc47",
+   "id": "0331d3dd",
    "metadata": {
     "editable": true
    },
@@ -114,7 +114,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bcfd68b4",
+   "id": "51159839",
    "metadata": {
     "editable": true
    },
@@ -125,7 +125,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9551e381",
+   "id": "6df6ca33",
    "metadata": {
     "editable": true
    },
@@ -137,7 +137,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e470afef",
+   "id": "6bf812e3",
    "metadata": {
     "editable": true
    },
@@ -150,7 +150,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6ece00ae",
+   "id": "1e04714b",
    "metadata": {
     "editable": true
    },
@@ -162,7 +162,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "98bad716",
+   "id": "621afaa2",
    "metadata": {
     "editable": true
    },
@@ -172,7 +172,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a8dad13c",
+   "id": "b7aa535d",
    "metadata": {
     "editable": true
    },
@@ -184,7 +184,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "94cddcc3",
+   "id": "45ea3a92",
    "metadata": {
     "editable": true
    },
@@ -195,7 +195,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8e5c2d66",
+   "id": "3851ded2",
    "metadata": {
     "editable": true
    },
@@ -207,7 +207,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5d7e493e",
+   "id": "c759e617",
    "metadata": {
     "editable": true
    },
@@ -220,7 +220,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "44050008",
+   "id": "c16482df",
    "metadata": {
     "editable": true
    },
@@ -233,20 +233,19 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c0bf3608",
+   "id": "2e2cda9b",
    "metadata": {
     "editable": true
    },
    "source": [
     "$$\n",
-    "\\mbox{Var}[\\boldsymbol{\\beta}^{\\mathrm{Ridge}}]=\\sigma^2[  \\mathbf{X}^{T} \\mathbf{X} + \\lambda \\mathbf{I} ]^{-1}  \\mathbf{X}^{T} \\mathbf{X} \\{ [  \\m\\\n",
-    "athbf{X}^{\\top} \\mathbf{X} + \\lambda \\mathbf{I} ]^{-1}\\}^{T},\n",
+    "\\mbox{Var}[\\boldsymbol{\\beta}^{\\mathrm{Ridge}}]=\\sigma^2[  \\mathbf{X}^{T} \\mathbf{X} + \\lambda \\mathbf{I} ]^{-1}  \\mathbf{X}^{T}\\mathbf{X} \\{ [  \\mathbf{X}^{\\top} \\mathbf{X} + \\lambda \\mathbf{I} ]^{-1}\\}^{T},\n",
     "$$"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "371484f8",
+   "id": "d69a45ab",
    "metadata": {
     "editable": true
    },
diff --git a/doc/LectureNotes/exercisesweek37.ipynb b/doc/LectureNotes/exercisesweek37.ipynb
index 8bf9e9691..3ae3ea9e9 100644
--- a/doc/LectureNotes/exercisesweek37.ipynb
+++ b/doc/LectureNotes/exercisesweek37.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "28222517",
+   "id": "ebfc874e",
    "metadata": {
     "editable": true
    },
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c7ffd7b0",
+   "id": "8ecf95b0",
    "metadata": {
     "editable": true
    },
@@ -27,7 +27,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "f687d0b0",
+   "id": "7940e437",
    "metadata": {
     "editable": true
    },
@@ -45,7 +45,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "b0b5ae03",
+   "id": "964cf4c4",
    "metadata": {
     "editable": true
    },
@@ -57,7 +57,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a5442d69",
+   "id": "bc8b093a",
    "metadata": {
     "editable": true
    },
@@ -68,7 +68,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "d9ac69f5",
+   "id": "bc1907b5",
    "metadata": {
     "editable": true
    },
@@ -80,7 +80,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6f42da1d",
+   "id": "c7d29897",
    "metadata": {
     "editable": true
    },
@@ -90,7 +90,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5690cef0",
+   "id": "e45dbe57",
    "metadata": {
     "editable": true
    },
@@ -102,7 +102,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "3834fc47",
+   "id": "0331d3dd",
    "metadata": {
     "editable": true
    },
@@ -114,7 +114,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "bcfd68b4",
+   "id": "51159839",
    "metadata": {
     "editable": true
    },
@@ -125,7 +125,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "9551e381",
+   "id": "6df6ca33",
    "metadata": {
     "editable": true
    },
@@ -137,7 +137,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e470afef",
+   "id": "6bf812e3",
    "metadata": {
     "editable": true
    },
@@ -150,7 +150,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "6ece00ae",
+   "id": "1e04714b",
    "metadata": {
     "editable": true
    },
@@ -162,7 +162,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "98bad716",
+   "id": "621afaa2",
    "metadata": {
     "editable": true
    },
@@ -172,7 +172,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "a8dad13c",
+   "id": "b7aa535d",
    "metadata": {
     "editable": true
    },
@@ -184,7 +184,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "94cddcc3",
+   "id": "45ea3a92",
    "metadata": {
     "editable": true
    },
@@ -195,7 +195,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8e5c2d66",
+   "id": "3851ded2",
    "metadata": {
     "editable": true
    },
@@ -207,7 +207,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "5d7e493e",
+   "id": "c759e617",
    "metadata": {
     "editable": true
    },
@@ -220,7 +220,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "44050008",
+   "id": "c16482df",
    "metadata": {
     "editable": true
    },
@@ -233,20 +233,19 @@
   },
   {
    "cell_type": "markdown",
-   "id": "c0bf3608",
+   "id": "2e2cda9b",
    "metadata": {
     "editable": true
    },
    "source": [
     "$$\n",
-    "\\mbox{Var}[\\boldsymbol{\\beta}^{\\mathrm{Ridge}}]=\\sigma^2[  \\mathbf{X}^{T} \\mathbf{X} + \\lambda \\mathbf{I} ]^{-1}  \\mathbf{X}^{T} \\mathbf{X} \\{ [  \\m\\\n",
-    "athbf{X}^{\\top} \\mathbf{X} + \\lambda \\mathbf{I} ]^{-1}\\}^{T},\n",
+    "\\mbox{Var}[\\boldsymbol{\\beta}^{\\mathrm{Ridge}}]=\\sigma^2[  \\mathbf{X}^{T} \\mathbf{X} + \\lambda \\mathbf{I} ]^{-1}  \\mathbf{X}^{T}\\mathbf{X} \\{ [  \\mathbf{X}^{\\top} \\mathbf{X} + \\lambda \\mathbf{I} ]^{-1}\\}^{T},\n",
     "$$"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "371484f8",
+   "id": "d69a45ab",
    "metadata": {
     "editable": true
    },
diff --git a/doc/src/week37/exercisesweek37.do.txt b/doc/src/week37/exercisesweek37.do.txt
index 737bb4b70..dcf647389 100644
--- a/doc/src/week37/exercisesweek37.do.txt
+++ b/doc/src/week37/exercisesweek37.do.txt
@@ -82,8 +82,7 @@ Show also that the variance is
 
 !bt
 \[
-\mbox{Var}[\bm{\beta}^{\mathrm{Ridge}}]=\sigma^2[  \mathbf{X}^{T} \mathbf{X} + \lambda \mathbf{I} ]^{-1}  \mathbf{X}^{T} \mathbf{X} \{ [  \m\
-athbf{X}^{\top} \mathbf{X} + \lambda \mathbf{I} ]^{-1}\}^{T},
+\mbox{Var}[\bm{\beta}^{\mathrm{Ridge}}]=\sigma^2[  \mathbf{X}^{T} \mathbf{X} + \lambda \mathbf{I} ]^{-1}  \mathbf{X}^{T}\mathbf{X} \{ [  \mathbf{X}^{\top} \mathbf{X} + \lambda \mathbf{I} ]^{-1}\}^{T},
 \]
 !et
 and it is easy to see that if the parameter $\lambda$ goes to infinity then the variance of Ridge parameters $\bm{\beta}$ goes to zero.