345 search results for "boxplot"

Implied alpha and minimum variance

May 20, 2013
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Implied alpha and minimum variance

Under the covers of strange bedfellows. Previously The idea of implied alpha was introduced in “Implied alpha — almost wordless”. In a comment to that post Jeff noticed that the optimal portfolio given for the example is ever so close to the minimum variance portfolio.  That is because there is a problem with the example … Continue reading...

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Analyzing a simple experiment with heterogeneous variances using asreml, MCMCglmm and SAS

May 17, 2013
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Analyzing a simple experiment with heterogeneous variances using asreml, MCMCglmm and SAS

I was working with a small experiment which includes families from two Eucalyptus species and thought it would be nice to code a first analysis using alternative approaches. The experiment is a randomized complete block design, with species as fixed effect and family and block as a random effects, while the response variable is growth

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How R Grows – not so fast

May 9, 2013
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How R Grows – not so fast

I have had some work on CRAN stats on the back-burner but the recent article How R Grows tempted me to push it up the list In the interim, I have a couple of comments on Joseph Rickert`s article. Although the body of the article refers to packages either created or updated in a time

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Data Analysis for Marketing Research with R Language (1)

April 22, 2013
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Data Analysis for Marketing Research with R Language (1)

Data Analysis technologies such as t-test, ANOVA, regression, conjoint analysis, and factor analysis are widely used in the marketing research areas of A/B Testing, consumer preference analysis, market segmentation, product pricing, sales driver analysis, and sales forecast etc. Traditionally the analysis tools are mainly SPSS and SAS, however, the open source R language is catching

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How long is the average dissertation?

April 15, 2013
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How long is the average dissertation?

The best part about writing a dissertation is finding clever ways to procrastinate. The motivation for this blog comes from one of the more creative ways I’ve found to keep myself from writing. I’ve posted about data mining in the past and this post follows up on those ideas using a topic that is relevant

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Win Your Snake Draft: Calculating “Value Over Replacement” using R

April 14, 2013
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Win Your Snake Draft: Calculating “Value Over Replacement” using R

In prior posts, I have demonstrated how to download, calculate, and compare fantasy football projections from ESPN, CBS, and NFL.com and how to calculate players' risk levels. In this post, I will demonstrate how...

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Win Your Snake Draft: Calculating “Value Over Replacement” using R

April 14, 2013
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Win Your Snake Draft: Calculating “Value Over Replacement” using R

In prior posts, I have demonstrated how to download, calculate, and compare fantasy football projections from ESPN, CBS, and NFL.com and how to calculate players’ risk levels. In this post, I will demonstrate how to win your snake The post Win Your Snake Draft: Calculating "Value Over Replacement" using R appeared first on Fantasy Football Analytics.

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Mobile version of the graph gallery

April 10, 2013
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Mobile version of the graph gallery

The R Graph Gallery has been a popular website for many years now. The number of graphics keeps growing as people send me their code. When browsing the website with a mobile device the experience was frustrating, as too much … Continue reading →

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Organise your data

April 5, 2013
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Use R to specify factors, recode variables and begin by-group analyses. Video Files This file contains data on pain score after laparoscopic vs. open hernia repair. Age, gender and primary/recurrent hernia also included. The ultimate aim here is to work out which of these factors are associated with more pain after this operation. lap_hernia Script

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A pictorial history of US large cap correlation

April 1, 2013
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A pictorial history of US large cap correlation

How has the distribution of correlations changed over the last several years? Previously Posts about correlation boxplots explained Data Daily returns of 443 large cap US stocks from 2004 through 2012 were used.  The sample correlations — almost 98,000 of them — during each year were created. If we were actually using the correlations, then … Continue reading...

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