Exercise 1 4 points total Consider a vector yy1yn o.pdf

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This document describes a vector of observations from a normal distribution with unknown mean and variance. The Jeffreys' prior for this model assigns a prior of 1/σ to the mean and 1/σ^2 to the variance, making the mean and log variance a priori independent with a uniform joint prior distribution.

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Exercise 1 (4 points total). Consider a vector y=(y1,,yn) of n independent observations from a
univariate Normal distribution, N(,2), with both and 2 unknown model parameters. The Jeffreys'
prior distribution for this model has p()1 and p(2)21, with and 2 prior independent such that the
joint prior distribution is p(,2)21 Show that this corresponds to a flat/uniform prior distribution on (,
log), i.e., p(,log)1

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In the 1300s, Europe was in the midst of decline and turmoil, China dominated East Asia, and the Islamic empires were embarking on a 300-year long period of ascendency. Yet by the dawn of the nineteenth century (1800s), China had turned inward and stagnated, the late Islamic Empires crumbled, and European peoples and their descendants seemed poised to take over the globe. Using specific historical examples from the lectures and readings, explain the remarkable turnaround that brought this reversal.

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write on this code: /** * A Sentinel List has two special nodes with values __HEAD__ and * __SENTINEL__ at each end */ public class SentinelList { /** * Create an empty sentinel list */ public SentinelList() { } /** * Return the special head node */ public Node getHead() { return null; } /** * Return the special sentinel node */ public Node getSentinel() { return null; } /** * Return the number of elements in the sentinel list */ public int size() { return 0; } /** * Add this value to the front of the list */ public void addFront(String value) { } /** * Add this value to the back of the list */ public void addBack(String value) { } /** * Remove the first occurrence of this value from the list. * Return true if the value was found and removed, or false otherwise. */ public boolean remove(String value) { return false; } /** * Return if the value was found in the list, or false otherwise */ public boolean lookup(String value) { return false; } public static void main(String[] args) { SentinelList sl = new SentinelList(); sl.addBack("Bar"); sl.addFront("Foo"); sl.addFront("Clouds"); boolean result = sl.remove("Bar"); System.out.println(result); // should be true result = sl.remove("Thunder"); System.out.println(result); // should be false // Should print __Head__, Clouds, Foo, __Sentinel__ for (Node node = sl.getHead(); node != null; node = node.getNext()) { System.out.print(node.getValue() + " "); } System.out.println(); } } Introduction A Sentinel List is a singly linked list with two special nodes at each end: a head and a tail. The figure below illustrates a sentinel list with two elements, "foo" and "bar". The head node has a special value, "_HEAD__. The sentinel node at the end has a special value, "_SENTINEL_.". Note that there are double underscores at the beginning and end of the special values. An empty SentinelList has only the head connected to the sentinel, with the sentinel connected to null. The two special nodes are never removed and always anchor the two ends of the list. Having sentinels can be a big help in coding linked lists. They simplify adding and removing. Your Task You are given a class Node that implements a node in the linked list. Values are Strings. Your task is to implement the SentinelList class with these methods: - public sentinellist() - Create an empty sentinel list. The empty sentinel list of size 0 has two special nodes, a head with value "_HEAD__ and a sentinel at the end with value "_SENTINEL_". - public Node getHead() - Return the special head node. - public Node getsentinel() - Return the special sentinel node. - public int size() - Return the number of elements in the sentinel list. - public void addFront(String value) -- Add the value to the front of the list - public boolean lookup(String value) - Return true if the value was found at least once in the list, or false otherwise. - public void addBack(String value) - Add the value to the end of the list - public boolean remove(String value) - Remove the .

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Topic: Why is unemployment so high in Europe? Briefly discuss. Optional reading: You can use any Web browser to search for the words European unemployment. Just by scanning the headlines, see how many possible explanations you can list. Why Is Unemployment So High in Europe? Between World War II and the mid-1970s, unemployment in Western Europe was low. From 1960 to 1974, for example, the unemployment rate in France never got as high as 4 percent. The worldwide recession of the mid-1970s, however, jacked up unemployment rates. But unemployment continued to climb in Continental Europe long after the recession ended, topping 10 percent during the 1990s, and was still 8 percent to 9 percent in 2007. Some observers claim that the natural rate of unemployment has increased in these countries. Economists have borrowed a term from physics, hysteresis (pronounced his-ter-e-sis), to argue that the natural rate of unemployment depends in part on the recent history of unemployment. The longer the actual unemployment rate remains above what had been the natural rate, the more the natural rate itself increases. For example, those unemployed can lose valuable job skills, such as the computer programmer who loses touch with the latest developments. As weeks of unemployment stretch into months and years, the shock and stigma may diminish, so the work ethic weakens. Whats more, some European countries offer generous unemployment benefits indefinitely, reducing the hardship of unemployment. Some Europeans have collected unemployment benefits for more than a decade. No consensus exists regarding the validity of hysteresis. The theory seems to be less relevant in the United States and Great Britain, where unemployment fell from 10 percent in 1982 to 4.5 and 5.5, respectively, in 2007. An alternative explanation for high unemployment in Continental Europe is that legislation introduced there in the 1970s made it more difficult to lay off workers. In most European countries, job dismissals must be approved by worker councils, which consider such factors as the workers health, marital status, and number of dependents. Severance pay has also become mandatory and can amount to a years pay or more. With layoffs difficult and costly, hiring became almost an irreversible decision for the employer, so firms have become reluctant to add workers, particularly untested workers with little experience. Also, high minimum wages throughout Europe, high payroll taxes, and an expanded list of worker rights have increased labor costs. For example, in Sweden, women are guaranteed a years paid leave on having a child and the right to work no more than six hours a day until the child reaches grade school. Swedish workers are also guaranteed at least five weeks of vacation a year; French workers get at least six weeks (Americans have no minimum vacation guarantees). Regardless of the explanation, the result is high unemployment in Continental Europe, particularly among young workers. .

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Can someone give simple answers to these two questions. Thank you. 1) On what time scales are Western scientific studies conducted? On what time scales have systems of Indigenous Knowledge been constructed? How might these differing time scales of viewing the world impact observations? 2) Indigenous knowledge often looks at complex relationships within systems instead of individual separate variables the way Western science often does. How might this impact the conclusions Indigenous people come to about scientific topics versus the conclusions Western scientists might come to?.

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