354 search results for "Anova"

R for Publication by Page Piccinini: Lesson 4 – Multiple Regression

June 13, 2016
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R for Publication by Page Piccinini: Lesson 4 – Multiple Regression

Introduction Today we’ll see what happens when you have not one, but two variables in your model. We will also continue to use some old and new dplyr calls, as well as another parameter for our ggplot2 figure. I’ll be taking for granted some of the set-up steps from Lesson 1, so if you haven’t done Lesson 4: Multiple...

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Introduction to R for Data Science :: Session 7 [Multiple Linear Regression Model in R  + Categorical Predictors, Partial and Part Correlation]

June 9, 2016
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Introduction to R for Data Science :: Session 7 [Multiple Linear Regression Model in R  + Categorical Predictors, Partial and Part Correlation]

Welcome to Introduction to R for Data Science Session 7: Multiple Regression + Dummy Coding, Partial and Part Correlations [Multiple Linear Regression in R. Dummy coding: various ways to do it in R. Factors. Inspecting the multiple regression model: regression coefficients and their interpretation, confidence intervals, predictions. Introducing {lattice} plots + ggplot2. Assumptions: multicolinearity and testing it from the...

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R profiling

June 5, 2016
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R profiling

Profiling in R R has a built in performance and memory profiling facility: Rprof. Type  into your console to learn more. The way the profiler works is as follows: you start the profiler by calling Rprof, providing a filename where the profiling data should be stored you call the R functions that you want to analyse you The post

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Absence of evidence is not evidence of absence: Testing for equivalence

May 20, 2016
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Absence of evidence is not evidence of absence: Testing for equivalence

When you find p > 0.05, you did not observe surprising data, assuming there is no true effect. You can often read in the literature how p > 0.05 is interpreted as ‘no effect’ but due to a lack of power the data might not be surprising if there was...

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Bike Rental Demand Estimation with Microsoft R Server

May 10, 2016
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Bike Rental Demand Estimation with Microsoft R Server

by Katherine Zhao, Hong Lu, Zhongmou Li, Data Scientists at Microsoft Bicycle rental has become popular as a convenient and environmentally friendly transportation option. Accurate estimation of bike demand at different locations and different times would help bicycle-sharing systems better meet rental demand and allocate bikes to locations. In this blog post, we walk through how to use Microsoft...

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Introduction to R for Data Science :: Session 1

April 30, 2016
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Introduction to R for Data Science :: Session 1

Welcome to Introduction to R for Data Science Session 1! The course is co-organized by Data Science Serbia and Startit. You will find all course material (R scripts, data sets, SlideShare presentations, readings) on these pages. Lecturers dipl. ing Branko Kovač, Data Analyst at CUBE, Data Science Mentor at Springboard, 

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The five element ninjas approach to teaching design matrices

April 25, 2016
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The five element ninjas approach to teaching design matrices

Design matrices unite seemingly disparate statistical methods, including linear regression, ANOVA, multiple regression, ANCOVA, and generalized linear modeling. As part of a hierarchical Bayesian modeling course that we offered this semester, we wanted our students to learn about design matrices to facilitate model specification and parameter interpretation. Naively, I thought that I could spend a few minutes in class reviewing matrix...

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Missing Value Treatment

April 25, 2016
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Missing Value Treatment

Missing values in data is a common phenomenon in real world problems. Knowing how to handle missing values effectively is a required step to reduce bias and to produce powerful models. Lets explore various options of how to deal with missing values and how to implement them. Data prep and pattern Lets use the BostonHousing Related Post

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Additive modelling global temperature time series: revisited

March 25, 2016
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Additive modelling global temperature time series: revisited

Quite some time ago, back in 2011, I wrote a post that used an additive model to fit a smooth trend to the then-current Hadley Centre/CRU global temperature time series data set. Since then the media and scientific papers have been full of reports of record warm temperatures in the past couple of years, of controversies (imagined) regarding...

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Football by the numbers

March 24, 2016
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Salvino A. Salvaggio In this blog I publish data analysis cases based on the R statistical language. No statistical or mathematical theory here, no discussions of the R language, no software tutorials, but only concrete case studies using existing R...

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