1685 search results for "regression"

A Call for Context-Aware Measurement

April 25, 2013
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A Call for Context-Aware Measurement

Context awareness seems to be everywhere, and everyone seems to be saying that context matters.  Gartner foresees "a game-changing opportunity" in what it calls context-aware computing.  The title of their report states it best, "Context Shap...

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Announcing Revolution R Enterprise 6.2

April 24, 2013
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Announcing Revolution R Enterprise 6.2

We are pleased to announce that Revolution R Enterprise Release 6.2 is available to new subscribers today. This new software release from Revolution Analytics includes a number of key new features: Support for open source R 2.15.3, the latest stable release of R. Since Release 2.14.2, the R Project has added 89 new features, 11 performance enhancements and 139...

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Disaggregating Annual Losses into Each Quarter

April 23, 2013
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Disaggregating Annual Losses into Each Quarter

In loss forecasting, it is often necessary to disaggregate annual losses into each quarter. The most simple method to convert low frequency to high frequency time series is interpolation, such as the one implemented in EXPAND procedure of SAS/ETS. In the example below, there is a series of annual loss projections from 2013 through 2016.

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R et Twitter

April 22, 2013
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R et Twitter

(This article was first published on Learning Data Science , and kindly contributed to R-bloggers) On va dans ce post, illustrer une utilisation simple des packages twitteR, StreamR, tm qui permettent faire du textmining. En réalité, les deux premiers permettent de récuperer les tweets et de faire des comptages simples et complexes et le dernier permet de faire du...

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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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What Is the Probability of a 16 Seed Beating a 1 Seed?

April 21, 2013
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What Is the Probability of a 16 Seed Beating a 1 Seed?

Note: I started this post way back when the NCAA men's basketball tournament was going on, but didn't finish it until now. Since the NCAA Men's Basketball Tournament has moved to 64 teams, a 16 seed as never upset a 1 seed. You might be tempted to say ...

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What Is the Probability of a 16 Seed Beating a 1 Seed?

April 20, 2013
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What Is the Probability of a 16 Seed Beating a 1 Seed?

Note: I started this post way back when the NCAA men's basketball tournament was going on, but didn't finish it until now. Since the NCAA Men's Basketball Tournament has moved to 64 teams, a 16 seed as never upset a 1 seed. You might be tempted to say...

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THE FINAL FOUR – Drag Race season 5, episode 11 predictions

April 15, 2013
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THE FINAL FOUR – Drag Race season 5, episode 11 predictions

We’re in the Final Four now, the actual final four that matters (sorry sports forecasters). Last week, Coco got the chop, which made sense statistically (she had a huge relative risk AND had been the first queen to have had to lipsync four times) and from a narrative standpoint — Alyssa got eliminated the week… Continue reading →

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Checking the Goodness of Fit of the Poisson Distribution in R for Alpha Decay by Americium-241

Checking the Goodness of Fit of the Poisson Distribution in R for Alpha Decay by Americium-241

Introduction Today, I will discuss the alpha decay of americium-241 and use R to model the number of emissions from a real data set with the Poisson distribution.  I was especially intrigued in learning about the use of Am-241 in smoke detectors, and I will elaborate on this clever application.  I will then use the Pearson chi-squared

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Predicting Dichotomous Outcomes I

April 14, 2013
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Predicting Dichotomous Outcomes I

We are trying to predict a dependent dichotomous variable (male/female, yes/no, like/dislike,etc) with independent “predictor” variables. Let’s say we want to determine whether or not an employee will quit based on the percentage of their tenure spent traveling. We assemble the data from HR and erroneously employ simple linear regression to model the relationship, a

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