Update1

.gitattributes

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+# Auto detect text files and perform LF normalization
+* text=auto
+
+# Custom for Visual Studio
+*.cs     diff=csharp
+*.sln    merge=union
+*.csproj merge=union
+*.vbproj merge=union
+*.fsproj merge=union
+*.dbproj merge=union
+
+# Standard to msysgit
+*.doc	 diff=astextplain
+*.DOC	 diff=astextplain
+*.docx diff=astextplain
+*.DOCX diff=astextplain
+*.dot  diff=astextplain
+*.DOT  diff=astextplain
+*.pdf  diff=astextplain
+*.PDF	 diff=astextplain
+*.rtf	 diff=astextplain
+*.RTF	 diff=astextplain

.gitignore

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+# Windows image file caches
+Thumbs.db
+ehthumbs.db
+
+# Folder config file
+Desktop.ini
+
+# Recycle Bin used on file shares
+$RECYCLE.BIN/
+
+# Windows Installer files
+*.cab
+*.msi
+*.msm
+*.msp
+
+# =========================
+# Operating System Files
+# =========================
+
+# OSX
+# =========================
+
+.DS_Store
+.AppleDouble
+.LSOverride
+
+# Icon must ends with two \r.
+Icon
+
+# Thumbnails
+._*
+
+# Files that might appear on external disk
+.Spotlight-V100
+.Trashes

DSS1/BigData.md

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+Big Data
+=============

DSS1/DSS1 Weekly Quiz.aux

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+\relax 
+\@writefile{toc}{\contentsline {subsection}{\numberline {0.1}Question 5}{4}}

DSS1/DSS1 Weekly Quiz.log

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DSS1/DSS1 Weekly Quiz.tex

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+\documentclass[12pt]{article}
+\usepackage{framed}
+\begin{document}
+
+\section*{The Data Scientist’s Toolbox - Week 1 Quiz}
+\subsection*{Question 1}
+We take a random sample of individuals in a population and identify whether they smoke and if they have cancer. We observe that there is a strong relationship between whether a person in the sample smoked or not and whether they have lung cancer. We claim that the smoking is related to lung cancer in the larger population. We explain we think that the reason for this relationship is because cigarette smoke contains known carcinogens such as arsenic and benzene, which make cells in the lungs become cancerous.
+\begin{itemize}
+\item This is an example of a causal data analysis.
+\item This is an example of a predictive data analysis.
+\item This is an example of an inferential data analysis.
+\item This is an example of a mechanistic data analysis.
+\end{itemize}
+%-------------------------------------------%
+\subsection*{Question 2}
+What is the most important thing in Data Science?
+\begin{itemize}
+\item Statistical inference.
+\item Machine learning and prediction.
+\item The data.
+\item The question you are trying to answer.
+\end{itemize}
+
+\newpage
+\section*{The Data Scientist’s Toolbox - Week 2 Quiz}
+
+%-----------------------------------------------------------------------------------%
+\subsection*{Question 1}
+Which of the following commands will create a directory called data in your current working directory?
+\begin{itemize}
+\item mkdir data
+\item pwd ../data
+\item pwd data
+\item mkdir /Users/data
+\end{itemize}
+%-----------------------------------------------------------------------------------%
+\subsection*{Question 2}
+Which of the following will initiate a git repository locally?
+
+\begin{itemize}
+\item git merge origin master
+\item git push
+\item git boom
+\item git init
+\end{itemize}
+%-----------------------------------------------------------------------------------%
+\subsection*{Question 3}
+Suppose you have forked a repository called datascientist on Github but it isn't on your local computer yet. Which of the following is the command to bring the directory to your local computer? (For this question assume that your user name is username)
+
+\begin{itemize}
+\item git pull datascientist master
+\item git init
+\item git push origin master
+\item git clone https://github.com/username/datascientist.git
+\end{itemize}
+%-----------------------------------------------------------------------------------%
+\subsection*{Question 4}
+Which of the following will create a markdown document with a secondary heading saying "Data Science Specialization" and an unordered list with the following for bullet points: Uses R, Nine courses, Goes from raw data to data products
+\begin{verbatim}
+*h2 Data Science Specialization 
+
+* Uses R 
+* Nine courses 
+* Goes from raw data to data products
+\end{verbatim}
+
+
+\begin{verbatim}
+## Data Science Specialization 
+
+li Uses R 
+li Nine courses 
+li Goes from raw data to data products
+\end{verbatim}
+\begin{verbatim}
+*** Data Science Specialization 
+
+* Uses R 
+* Nine courses 
+* Goes from raw data to data products
+\end{verbatim}
+\begin{verbatim}
+### Data Science Specialization 
+
+* Uses R 
+* Nine courses 
+* Goes from raw data to data products
+\end{verbatim}
+\begin{verbatim}
+## Data Science Specialization 
+
+* Uses R 
+* Nine courses 
+* Goes from raw data to data products
+\end{verbatim}
+%-----------------------------------------------------------------------------------%
+\subsection{Question 5}
+Install and load the KernSmooth R package. What does the copyright message say?
+\begin{itemize}
+\item Copyright M. P. Wand 1990-2009
+\item Copyright M. P. Wand 1997-2009
+\item Copyright Coursera 2009-2013
+\item Copyright Matthew Wand 1997-2009
+\end{itemize}
+
+\newpage
+
+\end{document}

DSS1/GitHub.md

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+GitHub
+==============
+- GitHub is a web-based hosting service for software development projects that use the Git revision control system. 
+- GitHub offers both paid plans for private repositories, and free accounts for open source projects. 

DSS1/Quiz1.tex

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+\subsection*{Question 1}
+Which of the following are courses in the Data Science Specialization? Select all that apply.
+\begin{itemize}
+\item Data Science 101
+\item Business Analytics
+\item R programming
+\item Practical Machine Learning
+\end{itemize}
+%-----------------------------------------------------------------%
+\subsection*{Question 2}
+Why are we using R for the course track? Select all that apply.
+\begin{itemize}
+\item R is free.
+\item R has a large number of add on packages that are useful for data analysis.
+\item R is a general purpose programming language.
+\item R is the best cloud computing language.
+\end{itemize}
+%-----------------------------------------------------------------%
+\subsection*{Question 3}
+What are good ways to find answers to questions in this course track? Select all that apply.
+\begin{itemize}
+\item  Searching Stack Overflow
+\item Searching Google.
+\item Emailing your instructors
+\item Posting homework assignments to mailing lists
+\end{itemize}
+%-----------------------------------------------------------------%
+\subsection*{Question 4}
+What are characteristics of good questions on the message boards? Select all that apply.
+\begin{itemize}
+\item Is insulting or rude.
+\item Provides the minimum amount of information necessary to communicate the problem.
+\item Includes follow-ups if you answer your own question.
+\item Provides no details.
+\end{itemize}
+%-----------------------------------------------------------------%
+\subsection*{Question 5}
+Which of the following packages provides machine learning functionality? Select all that apply
+\begin{itemize}
+\item shiny
+\item caret
+\item kernlab
+\item cacheSweave
+\end{itemize}
+%--------------------------------------------------------------------%