Working Paper 05-47 Statistics and Econometrics Series 09 July 2005 Departamento de Estadística Universidad Carlos III de Madrid Calle Madrid‚ 126 28903 Getafe (Spain) Fax (34) 91 624-98-49 BAYESIAN INFERENCE FOR THE HALF-NORMAL AND HALF-T DISTRIBUTIONS M.P. Wiper‚ F.J. Girón‚ A. Pewsey* Abstract In this article we consider approaches to Bayesian inference for the half-normal and half-t distributions. We show that a generalized version of the normal- gamma distribution is conjugate to the
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Introduction Statistics is a set of tools used to organize and analyze data. Data must either be numeric in origin or transformed by researchers into numbers. For instance‚ statistics could be used to analyze percentage scores English students receive on a grammar test: the percentage scores ranging from 0 to 100 are already in numeric form. Statistics could also be used to analyze grades on an essay by assigning numeric values to the letter grades‚ e.g.‚ A=4‚ B=3‚ C=2‚ D=1‚ and F=0. Employing
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Statistics Real Life Example #2Article: http://america.aljazeera.com/articles/2014/10/21/us-ebola-airports.htmlMy article is covering the recent “Ebola Outbreak”. In this‚ people are direly afraid of catching the Ebola virus. They are even going as far as screening people in airports who come from‚ and travel to‚ places where Ebola is much more spread amongst the population (mostly in Africa‚ for now). The article quotes: “Some members of Congress have urged President Barack Obama to ban all travel
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Statistics Investigation Introduction A new drug was developed that was claimed to lower the cholesterol level in humans. A leading heart specialist was interested to know if the claim made by the company selling the drug was accurate. They enlisted the help of 50 patients. They agreed to take part in an experiment in which 25 patients would be randomly allocated to a group that would take the new drug and the other 25 would take an identical looking pill that was a placebo (a sugar pill that
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Statistics in Business Katherine Wolf QNT/275 April 3‚ 2015 Barry Adkins Statistics in Business Statistics is all about collecting numerical data‚ organizing it‚ and interpreting the data to form hypothesis. While interpreting the data we are able to draw all kinds of conclusions from weather forecasts to how much money a company is projected to make over the next year. There are different types of statistics that can be used for different outcomes. You have to first identify the
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Running head: Misuses Statistics 1 Misuses Statistics Regena Kelley MAT126: Survey of Mathematical Methods Instructor: Zhimin Huang January 21‚ 2013 Misuses Statistics 2 Misuses Statistics Statistics and survey are misused and not accurate because of many factors. The types of these statistics are found suspect samples‚ asking Biased questions and misleading graphs. There are businesses that use these statistics with questions to convice people to accept
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Statistics in Business QNT/275 January 12‚ 2015 Kim Gravelle Statistics in Business Statistics are simply a way of gathering information from data. Learning from data is the essential use of statistics. The extraction of answers from data provides the foot print for further investigation and research. There are several different types and levels of statistics‚ they are nominal‚ ordinal‚ interval‚ and ratio ("Data Levels of Measurement"‚ 2014). The first level being nominal‚ allows for the use
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of top 100 banks in the United States according to the total assets. Leading the list was Bank of America‚ followed by JP Morgan Chase and Citibank. Following is an Excel Analysis of total assets ($ billions) of these banks using the descriptive statistics feature. Study the output and describe what you can learn about the assets of these top 100 banks from the output. Top 100 Banks in the U.S Mean Standard Error Median Mode Standard Deviation Sample Variance Kurtosis Skewness Range Minimum
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Chapter one summary The use of statistics is research is noted in this chapter. It reveals that statistical procedure could be segregated into two section and they are descriptive and inferential. In analyzing both descriptive statistics does exactly what it says‚ it describes the set of data. The problem is presented and descriptive statistical basically describes what the data has to say about the same issue. However inferential statistics main goal is making predictions or inferences about
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not = 440 Statistic 4.9 With 98% confidence Lower limit 3.05348411 Upper limit 24.7249703 With 98% confidence we cannot reject Ho since the statistic is inside the acceptance zone b) Check the same hypothesis with 95% confidence. With 95% confidence Lower limit 3.81574825 Upper limit 21.9200493 With 95% confidence we cannot reject Ho since the statistic is inside
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