352 search results for "Anova"

One-way Analysis of Variance (ANOVA)

February 3, 2010
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One-way Analysis of Variance (ANOVA)

Analysis of Variance (ANOVA) is a commonly used statistical technique for investigating data by comparing the means of subsets of the data. The base case is the one-way ANOVA which is an extension of two-sample t test for independent groups covering situations where there are more than two groups being compared. In one-way ANOVA the data

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R Tutorial Series: ANOVA Tables

January 8, 2010
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R Tutorial Series: ANOVA Tables

The commonly applied analysis of variance procedure, or ANOVA, is a breeze to conduct in R. This tutorial will explore how R can be used to perform ANOVA to analyze a single regression model and to compare multiple models.Tutorial FilesBefore we begin,...

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Two-way analysis of variance: two-way ANOVA in R

August 7, 2009
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The one-way analysis of variance is a useful technique to verify if the means of more groups are equals. But this analysis may not be very useful for more complex problems. For example, it may be necessary to take into account two factors of variability to determine if the averages between the groups depend on the group classification...

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Two-way analysis of variance: two-way ANOVA in R

August 7, 2009
By

The one-way analysis of variance is a useful technique to verify if the means of more groups are equals. But this analysis may not be very useful for more complex problems. For example, it may be necessary to take into account two factors of variability to determine if the averages between the groups depend on the group classification...

Read more »

Analysis of variance: ANOVA, for multiple comparisons

July 30, 2009
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Analysis of variance: ANOVA, for multiple comparisonsThe ANOVA model can be used to compare the mean of several groups with each other, using a parametric method (assuming that the groups follow a Gaussian distribution).Proceed with the following example:The manager of a supermarket chain wants to see if the consumption in kilowatts of 4 stores between them are equal. He...

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Analysis of variance: ANOVA, for multiple comparisons

July 30, 2009
By

Analysis of variance: ANOVA, for multiple comparisonsThe ANOVA model can be used to compare the mean of several groups with each other, using a parametric method (assuming that the groups follow a Gaussian distribution).Proceed with the following example:The manager of a supermarket chain wants to see if the consumption in kilowatts of 4 stores between them are equal. He...

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Repeated Measures ANOVA using R

March 9, 2009
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Repeated Measures ANOVA using R

While so-called “between-subjects” ANOVA is absolutely straightforward in R, performing repeated measures (within-subjects) ANOVA is not so obvious. I have come across at least three different ways of performing repeated measures ANOVA in R. Which method you use depends on … Continue reading →

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Analysis of Variance (ANOVA) using R

February 5, 2009
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Analysis of Variance (ANOVA) using R

I found some useful websites showing examples of how to use R for various sorts of ANOVA (between, within, mixed designs, etc): Using R for Psychological Research Quick-R for SAS/SPSS/Stata users enjoy

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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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