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\rhead{Assignment}
\lhead{Psychology III}
\rfoot{\thepage}
\linespread{1.3}
\title{A fancy title for your assignment}
\subtitle{Subtitle/Subject\\
\hfill\includegraphics[height=2.5cm]{logo}
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\author{Harshvardhan}
\institution{2016IPM043 \\
Section - `A'}
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\begin{document}
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\begin{center}
\textbf{ASSIGNMENT}
\end{center}
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\textbf{Instructor's Name:} Prof. John Doe\\
\textbf{Course:} Social Psychology in Business Environment\\
\textbf{Date of Submission:} \today %change today to other dates of submissions
\medskip
\hrule
\hspace{1cm}
Hey, this is a template for assignment submissions at college. Don't try to make sense of the text in the document, they're copy-paste of my other assignments and are completely out of context. Edit it as you need and have fun!
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\begin{tcolorbox}[colback=blue!3!white,colframe=blue(ryb)!50!black,title=\textbf{Definition}]
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\section{Background and Introduction}
The effect is usually accompanied with,
\begin{itemize}
\item First item
\item Second item
\item Extend this list
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\section*{Examples} %Unnumbered sections. Use \section{Examples} for numbered sections.
\blindtext
Some real life examples of this effect are following,
\begin{enumerate}
\item First item
\item Second item
\item More items
\end{enumerate}
\cite{fest1959} gave an interesting account about forced compliance. You can also cite this paper in-paragraph. \citep{fest1959}
\section{Mathematical Tools and Computer Codes}
\subsection{Some symbols $\theta_k = - \beta^{\alpha_k} \rho_k$}
Another possible parrametrisation is $\theta_k = \beta^{\alpha_k} \rho_k$. The correlation function then used is,
$$
cov(z(x_i),z(x_j)) = \frac{1}{\Gamma(\nu)} \sum_{k=1}^{p} \rho_k^{2^\alpha_k |x_{ij} - x_{jk}|^\alpha_k}.
$$
\paragraph{Euclidean Distance.} It is defined as,
$$
d_0 = \sqrt[]{\sum_{j=1}^n (x_i - y_i)^2},
$$
where $x_i$ and $y_i$ refer to different observations of Variable i where there are n variables.
\subsection{Computer Codes}
\begin{verbatim}
library(factoextra)
fviz_cluster(list(data = x, cluster = sub))
#developing tanglegram - comparative tanglegram between average linkages for
correlation and euclidean distances
library("dendextend")
hc1=hc.average
d1=as.dendrogram (hc)
d2=as.dendrogram (hc1)
tanglegram(d1, d2)
\end{verbatim}
\subsection{Using matrices}
It can also be written as
$$
MSE(\hat{y}(x)) = \sigma^2 \left[ 1-(f'(x)r'(x)) \left(
\begin{array}{cc}
0 & F' \\
F & R
\end{array}
\right)^{-1} \right].
$$
\section{Tables and Images}
Here is a table,
\begin{center}
\begin{tabu}{|l|l|l|}
\hline
\textbf{Attribute} & \textbf{Explanation} & \textbf{Type}\\ \hline \hline
FRESH & Annual Spending on Fresh Products & Continuous\\ \hline
MILK & Annual Spending on Milk Products & Continuous\\ \hline
GROCERY & Annual Spending on Grocery Products & Continuous\\ \hline
FROZEN & Annual Spending on Frozen Products & Continuous\\ \hline
DETERGENTS & Annual Spending on Detergent & Continuous\\ \hline
DELICATESSEN & Annual Spending on delicatessen products & Continuous\\ \hline
CHANNEL & Hotel/Restaurant/Cafe & Nominal\\ \hline
REGION & Region (Lisnon, Oporto or Other) & Nominal\\ \hline
\end{tabu}
\end{center}
Here is an image.
\begin{figure}[h]
\includegraphics[scale=0.6]{clust}
\caption{Cluster Plot for the clusters obtained.}
\label{clustplot}
\end{figure}
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