Started statistics lecture

statistics-fabian/assignments/Makefile

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+all:
+	for number in 001 002 003 004 005 006 007 007 009 010 011 012 013 014 015 016 017 ; do \
+		echo $$number ; \
+		sed "s/000/$$number/g" day1.tex > tmp.tex; \
+		pdflatex tmp.tex; \
+		mv tmp.pdf day1_$$number.pdf; \
+		cp ../data/example$$number.csv ./ ;\
+		rm tmp.* ; \
+		zip example$$number.zip example$$number.csv  day1_$$number.pdf ; \
+		rm example$$number.csv ;\
+		rm day1_$$number.pdf ; \
+	done
+
+clean:
+	rm *.zip
+	rm -rf auto

statistics-fabian/assignments/day1.tex

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+\documentclass[addpoints,10pt]{exam}
+\usepackage{url}
+\usepackage{color}
+\usepackage{hyperref}
+
+\pagestyle{headandfoot}
+\runningheadrule
+\firstpageheadrule
+
+\firstpageheader{Scientific Computing}{afternoon assignment day 01}{10/20/2014}
+%\runningheader{Homework 01}{Page \thepage\ of \numpages}{23. October 2014}
+\firstpagefooter{}{}{}
+\runningfooter{}{}{}
+\pointsinmargin
+\bracketedpoints
+
+%\printanswers
+\shadedsolutions
+
+
+\begin{document}
+%%%%%%%%%%%%%%%%%%%%% Submission instructions %%%%%%%%%%%%%%%%%%%%%%%%%
+\sffamily
+%%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
+
+\begin{questions}
+  \question To publish scientific results, you will usually need to
+  use statistical methods. Some journals provide you with a brief
+  description of how they expect you to apply statistical methods. One
+  example can be found in the author guidelines of the journal
+  Nature. 
+
+  Assume you collected the following dataset. You can download it from
+  Ilias as {\tt example000.csv}. Here is the description of the dataset:
+
+  \begin{quotation}
+    \tt 
+    \input{../examples/example000.tex}
+  \end{quotation}
+
+  \begin{parts}
+    \part Download the dataset and write a script that loads it into
+    matlab. 
+
+    \part Think about the type of your data (I might ask you that
+    tomorrow).
+
+    \part Produce a plot that displays the data in an appropriate
+    way. Make sure to respect all elements of good plotting we
+    discussed today.
+
+    \part Download the statistical checklist from nature. Produce {\bf
+      one} slide that contains the plot and a concise summary of your
+    data which respects the requirements made by nature (assume you
+    are producing a figure legend for the figure in nature). It is
+    good style to avoid expressions like ``the plot shows'' or
+    similar. 
+
+    \part Upload your code, the data, and the slide as a zip to
+    Ilias. Deadline is 19h00. Structure the zip such that you can
+    present you program in front of the class. Several students will
+    be asked to present their slide and their code tomorrow morning. 
+
+  \end{parts}
+  
+\end{questions}
+
+
+
+
+
+\end{document}

statistics-fabian/assignments/day2.tex

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+\documentclass[addpoints,10pt]{exam}
+\usepackage{url}
+\usepackage{color}
+\usepackage{hyperref}
+
+\pagestyle{headandfoot}
+\runningheadrule
+\firstpageheadrule
+
+\firstpageheader{Scientific Computing}{afternoon assignment day 02}{10/21/2014}
+%\runningheader{Homework 01}{Page \thepage\ of \numpages}{23. October 2014}
+\firstpagefooter{}{}{}
+\runningfooter{}{}{}
+\pointsinmargin
+\bracketedpoints
+
+%\printanswers
+\shadedsolutions
+
+
+\begin{document}
+%%%%%%%%%%%%%%%%%%%%% Submission instructions %%%%%%%%%%%%%%%%%%%%%%%%%
+\sffamily
+%%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
+
+\begin{questions}
+  \question Download example002 from yesterday (brain weights). 
+  \begin{parts}
+    \part Simulate a null distribution via permutation.
+    \part Determine whether you can reject ``means are equal'' on a
+    5\% significance level using the simulated null distribution.
+    \part Check whether the means are different with a two sample
+    t-test in matlab ({\tt ttest2}).
+    \part Plot the data appropriately and generate a single slide that
+    contains the plot and short discussion of the test that respects
+    the nature statistical checklist (ignore all question whether the
+    assumptions of the test are satisfied).
+    \part Upload the slide and the code to Ilias. Deadline is 19h00.
+  \end{parts}
+\end{questions}
+
+
+
+
+
+\end{document}

statistics-fabian/assignments/day3.tex

@@ -0,0 +1,65 @@
+\documentclass[addpoints,10pt]{exam}
+\usepackage{url}
+\usepackage{color}
+\usepackage{hyperref}
+
+\pagestyle{headandfoot}
+\runningheadrule
+\firstpageheadrule
+
+\firstpageheader{Scientific Computing}{afternoon assignment day 02}{10/22/2014}
+%\runningheader{Homework 01}{Page \thepage\ of \numpages}{23. October 2014}
+\firstpagefooter{}{}{}
+\runningfooter{}{}{}
+\pointsinmargin
+\bracketedpoints
+
+%\printanswers
+\shadedsolutions
+
+
+\begin{document}
+%%%%%%%%%%%%%%%%%%%%% Submission instructions %%%%%%%%%%%%%%%%%%%%%%%%%
+\sffamily
+%%%%%%%%%%%%%% Questions %%%%%%%%%%%%%%%%%%%%%%%%%
+
+\begin{questions}
+  \question When the p-value is small, we reject the null
+  hypothesis. For example, if you want to test whether two means are
+  not equal, the null hypothesis is ``means are equal''. If e.g. $p\le
+  0.05$ then we take it as sufficient evidence that the null
+  hypothesis is not true. Therefore, we assume that the means are not
+  equal (which is what you want to show). 
+
+  In this exercise we will look at what kind of p-values we expect if
+  the null hypothesis is true. In our example, this would be the case
+  if the true means of two datasets are actually equal. 
+  \begin{parts}
+    \part Think about how you expect the p-values to behave in that
+    situation. 
+    \part Simulate the situation in which the means are equal by
+    repeating the following at least $1000$ times:
+    \begin{enumerate}
+    \item Generate two arrays {\tt x} and {\tt y} with $10$ normally
+      (Gaussian) distributed random numbers using {\tt randn}. By
+      construction, the true means behind the random number are zero. 
+    \item Perform a two sample t-test ({\tt ttest2}) on {\tt x} and
+      {\tt y}. Store the p-value.
+    \end{enumerate}
+    \part Plot a histogram of the $1000$ p-values. What do you think
+    is the distribution the p-values (i.e. if you repeated this
+    experiment many more times, how would the histogram look like)?
+    \part Given what you find, think about whether the following
+    strategy is statistically valid: You collect $10$ data points from
+    each group and perform a test. If the test is not significant, you
+    collect $10$ more and repeat the test. If the test tells you that
+    there is a significant difference you stop. Otherwise you repeat
+    the procedure until the test is significant.
+  \end{parts}
+\end{questions}
+
+
+
+
+
+\end{document}

statistics-fabian/assignments/example001.csv

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+MAO,Diagnosis
+6.8,I
+4.1,I
+7.3,I
+14.2,I
+18.8,I
+9.9,I
+7.4,I
+11.9,I
+5.2,I
+7.8,I
+7.8,I
+8.7,I
+12.7,I
+14.5,I
+10.7,I
+8.4,I
+9.7,I
+10.6,I
+7.8,II
+4.4,II
+11.4,II
+3.1,II
+4.3,II
+10.1,II
+1.5,II
+7.4,II
+5.2,II
+10,II
+3.7,II
+5.5,II
+8.5,II
+7.7,II
+6.8,II
+3.1,II
+6.4,III
+10.8,III
+1.1,III
+2.9,III
+4.5,III
+5.8,III
+9.4,III
+6.8,III

statistics-fabian/assignments/example002.csv

@@ -0,0 +1,186 @@
+Weight,Sex
+1607,m
+1157,m
+1248,m
+1310,m
+1398,m
+1237,m
+1232,m
+1343,m
+1380,m
+1274,m
+1245,m
+1286,m
+1508,m
+1105,m
+1123,m
+1198,m
+1300,m
+1249,m
+1185,m
+915,m
+1345,m
+1107,m
+1357,m
+1227,m
+1205,m
+1435,m
+1289,m
+1093,m
+1211,m
+1260,m
+1193,m
+1330,m
+1130,m
+1357,m
+1193,m
+1232,m
+1321,m
+1260,m
+1380,m
+1230,m
+1136,m
+1029,m
+1223,m
+1240,m
+1264,m
+1020,m
+1415,m
+1410,m
+1275,m
+1230,m
+1085,m
+1048,m
+1181,m
+1103,m
+1165,m
+1547,m
+1173,m
+1660,m
+1307,m
+1535,m
+1315,m
+1257,m
+1424,m
+1309,m
+1170,m
+1412,m
+1270,m
+1230,m
+1233,m
+1561,m
+1193,m
+1272,m
+1355,m
+1137,m
+1354,m
+1110,m
+1265,m
+1407,m
+1227,m
+1330,m
+1222,m
+1305,m
+1475,m
+1177,m
+1337,m
+1145,m
+1070,m
+1305,m
+1085,m
+1303,m
+1390,m
+1532,m
+1238,m
+1233,m
+1280,m
+1245,m
+1459,m
+1157,m
+1302,m
+1385,m
+1310,m
+1342,m
+1303,m
+1248,m
+1115,m
+1365,m
+1227,m
+1353,m
+1125,f
+1027,f
+1112,f
+983,f
+1090,f
+1247,f
+1045,f
+983,f
+972,f
+1045,f
+937,f
+1245,f
+1200,f
+1270,f
+1200,f
+1145,f
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+1010,f
+1095,f
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+1168,f
+1095,f
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+1235,f
+1050,f
+1038,f
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+1255,f
+1228,f
+1000,f
+1225,f
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+1117,f
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+1190,f
+1153,f
+1037,f
+1120,f
+1212,f
+1024,f
+1135,f
+1177,f
+1096,f
+1114,f