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author | Julian T <julian@jtle.dk> | 2021-03-12 11:56:20 +0100 |
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committer | Julian T <julian@jtle.dk> | 2021-03-12 11:56:20 +0100 |
commit | 8430a7f363589260c809f180bfa2c0a7097d5e6b (patch) | |
tree | 8570ea72000616e7f59d66285615cf9013905a94 /sem6/prob/stat2/opgaver.tex | |
parent | 1455ccc4eb1047aba2a50b8c2c3a5bd3887d0226 (diff) |
Added assignments for prob
Diffstat (limited to 'sem6/prob/stat2/opgaver.tex')
-rw-r--r-- | sem6/prob/stat2/opgaver.tex | 23 |
1 files changed, 23 insertions, 0 deletions
diff --git a/sem6/prob/stat2/opgaver.tex b/sem6/prob/stat2/opgaver.tex new file mode 100644 index 0000000..0596cce --- /dev/null +++ b/sem6/prob/stat2/opgaver.tex @@ -0,0 +1,23 @@ +\title{Opgaver til Statistics Module 2} + +\section{Exercise 2} + +\subsection{Opgave A} + +Her kan vi sige at $y_i \sim \mathcal{N}(S', \sigma^2)$ hvor $S' = \alpha S$ og derfor er det at estimere $S'$ og isolere for $d$. + +Først kan vi estimere for $S'$, og eftersom $y_i$ er normal fordelt kan man estimere mean $S'$ med: \[ + \hat{\mu} = \sum_{i=1}^{n} \frac {x_i} n +.\] + +Nu kan vi isolere for $d$. +\begin{align*} + S' = \hat{\mu} = S \cdot \frac {0.5} d = \frac 1 n \sum_{i=1}^{n} x_i \\ + d = S \cdot \frac{0.5 n}{\sum_{i=1}^{n} x_i} +\end{align*} + +\section{Exercise 3} + +\subsection{Part 1} + +Okay jeg fortsætter på papir. |