Publications by Marvanessa Dinorog
Item #1 Final Term Exam Stat 54
library(graphics) library(ggplot2) Warning: package 'ggplot2' was built under R version 4.2.2 A researcher conducts a study to evaluate whether the distribution of the length of time it takes migraine patients to respond to a 100 mg. dose of an intravenously administered drug is normal, with a mean response time of 90 seconds and a standard de...
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Item #1 Final Term Exam Stat 54
library(graphics) library(ggplot2) Warning: package 'ggplot2' was built under R version 4.2.2 library(readxl) Kolmogorov <- read_excel("D:/MARV BS MATH/4th year, 2nd sem/Nonparametric Statistics/Kolmogorov.xlsx") Kolmogorov # A tibble: 30 × 2 Patient Scores <dbl> <dbl> 1 1 21 2 2 32 3 3 38 4 ...
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Additional Activity for Factor Analysis
DATA places <- read.table("D:/MARV BS MATH/4th year, 2nd sem/Multivariate/places.txt", header=FALSE, sep = '') paged_table(places) Describing the Data We look at the dataset before we run any analysis. a <- describe(places) paged_table(a) We use the dim function to retrieve the dimension of the dataset. dim(places) [1] 329 10 Cleaning Data I...
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Canonical Correlation Analysis
library(ggplot2) library(GGally) Registered S3 method overwritten by 'GGally': method from +.gg ggplot2 library(CCA) Loading required package: fda Loading required package: splines Loading required package: fds Loading required package: rainbow Loading required package: MASS Loading required package: pcaPP Loading required package: RCur...
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Multivariate Analysis of Variance (MANOVA)
MANOVA in R: Implementation As with most of the things in R, performing a MANOVA statistical test boils down to a single function call. But we’ll need a dataset first. The Iris dataset is well-known among the data science crowd, and it is built into R: paged_table(head(iris)) It doesn’t matter if you use the same dataset as us, as long as o...
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Discriminant Analysis
Cluster Analysis in R Getting Data mydata <- read.csv("D:/MARV BS MATH/4th year, 2nd sem/Multivariate/Discriminant data.txt", header=T) str(mydata) 'data.frame': 22 obs. of 9 variables: $ Company : chr "Arizona " "Boston " "Central " "Commonwealth" ... $ Fixed_charge: num 1.06 0.89 1.43 1.02 1.49 1.32 1.22 1.1 1.34 1.12 ... $ RoR ...
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Logistic Regression
Logistic Regression 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 on the campaign, the amount of time spent campaigning negatively and ...
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Friedman Test
Friedman Test in R Data Preparation We’ll use the self esteem score dataset measured over three time points. The data is available in the datarium package. data("selfesteem", package = "datarium") paged_table(head(selfesteem, 3)) Gather columns t1, t2 and t3 into long format. Convert id and time variables into factor (or grouping) variables:...
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Exploratory Factor Analysis in R
Exploratory Factor Analysis in R Data Overview Fetching data from the server We first need to fetch sample data from the server. This is a raw data set, so each row row represents a person’s survery. # Dataset url <- "https://raw.githubusercontent.com/housecricket/data/main/efa/sample1.csv" data_survey <- read.csv(url, sep = ",") paged_table(...
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JOLINA THESIS ANALYSIS
Null Hypothesis: The true mean difference between S. aureus and S. marcescens with the given concentration is equal to zero. Alternative Hypothesis: The true mean difference between S. aureus and S. marcescens with the given concentration is not equal to zero. shapiro.test(PLANT$SAMean128) Shapiro-Wilk normality test data: PLANT$SAMean...
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