Publications by Kyle Kenneth B. Ruaya
STAT 56 - Multivariate Analysis of Variance (MANOVA)
The Theory of MANOVA in R MANOVA stands for Multivariate ANOVA or Multivariate Analysis Of Variance. It’s an extension of regular ANOVA. The general idea is the same, but the MANOVA test has to include at least two dependent variables to analyze differences between multiple groups (factors) of the independent variable. If you only have a sing...
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STAT 56 - Cluster Analysis
Data Preparation # Load and scale the dataset data("USArrests") df <- scale(USArrests) head(df) ## Murder Assault UrbanPop Rape ## Alabama 1.24256408 0.7828393 -0.5209066 -0.003416473 ## Alaska 0.50786248 1.1068225 -1.2117642 2.484202941 ## Arizona 0.07163341 1.4788032 0.9989801 1.042878388 ## Arkansas...
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STAT 54 - Friedman Test
Prerequisites library(tidyverse) ## ── Attaching packages ─────────────────────────────────────── tidyverse 1.3.2 ── ## ✔ ggplot2 3.4.0 ✔ purrr 0.3.5 ## ✔ tibble 3.1.8 ✔ dplyr 1.0.10 ## ✔ tidyr 1.2.1 ✔ stringr 1.4.1 ## ✔ r...
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STAT 54 - Logistic Regression
library(aod) ## Warning: package 'aod' was built under R version 4.2.3 library(ggplot2) Examples Example 1. Suppose that we are interested in the factors that influence whether a political candidate wins an election. The outcome (response) variable is binary (0/1); win or lose. The predictor variables of interest are the amount of money spent o...
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STAT 56 - Factor Analysis in R
library(psych) ## Warning: package 'psych' was built under R version 4.2.3 library(corrplot) ## corrplot 0.92 loaded library("psych") library(ggplot2) ## ## Attaching package: 'ggplot2' ## The following objects are masked from 'package:psych': ## ## %+%, alpha library(car) ## Loading required package: carData ## ## Attaching package: 'c...
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RUAYA - Activity 1 (Multivariate Analysis)
Using R for Multivariate Analysis Reading Multivariate Analysis Data into R wine <- read.table("http://archive.ics.uci.edu/ml/machine-learning-databases/wine/wine.data", sep=",") wine Plotting Multivariate Data A Matrix Scatterplot a<-wine[2:6] paged_table(a) scatterplotMatrix(wine[2:6]) A Scatterplot with the Data Points Labelled...
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Exercise 2
Data ## # A tibble: 27 × 5 ## PhaseInterval Temperature `Adlay with wash` `Adlay with milk` Adlay with mi…¹ ## <chr> <chr> <dbl> <dbl> <dbl> ## 1 3- day 25°C 759 220 819 ## 2 3- day 25°C 736 ...
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Exercise 3
ICT Training Data First, create before and after as objects containing the scores of ICT training. before <- c(12.2, 14.6, 13.4, 11.2, 12.7, 10.4, 15.8, 13.9, 9.5, 14.2) after <- c(13.5, 15.2, 13.6, 12.8, 13.7, 11.3, 16.5, 13.4, 8.7, 14.6) Now create a data matrix using data.frame() function. Use objects before and after as created earlier to ...
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Exercise 4
Two sample equality of variances in R 1 F-test in R The F test statistic can be obtained by calculating the ratio of the two variances F=VAR(A)/VAR(B). Before doing the F test, we need to check one of the major assumptions is data should be normally distributed. Normality distribution can be assessed based on the Shapiro test or visually usi...
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Exercise 5
One way ANOVA Example in R One way ANOVA Example in R, the one-way analysis of variance (ANOVA), also known as one-factor ANOVA, is an extension of the independent two-sample t-test for comparing means when more than two groups are present. The data is divided into numerous groups using one single grouping variable in one-way ANOVA (also call...
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