Publications by JORIELYN S. MANLA
Cluster Analysis in R Simplified and Enhanced
Cluster Analysis in R Simplified and Enhanced Required packages library(factoextra) library(cluster) 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 -...
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Cluster Analysis in R
Getting Data mydata <- read.csv("E:/JORIELYN/MULTIVARIATE ANALYSIS/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 : num 9.2 10.3 15.4 11.2 8.8 13.5 12.2 9....
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Canonical Correlation Analysis
require(ggplot2) require(GGally) require(CCA) require(CCP) Example: A researcher has collected data on three psychological variables, four academic variables (standardized test scores) and gender for 600 college freshman. She is interested in how the set of psychological variables relates to the academic variables and gender. In particular,...
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Exercises from Units 1-8
Lesson 1: Measures of Central Tendency, Dispersion and Association Example 1-5: Women’s Health Survey (Descriptive Statistics) Variable n Mean StdDev Minimum Maximum calcium 737 624.04925 397.277540 7.44 2866.440 iron 737 11.12990 5.984191 0.00 58.668 protein 737 65.80344 30.575756 0.00 251.012 a...
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Problem Set #4
Simple Regression Running the regression model in RStudio Factor and dummy variable Multiple Regression Regression model with two way interaction Regression Diagnostics Simple Regression Introduction Regression analysis: is a statistical tool used to explain the relationship between a response (dependent, outcome) variable and one or more pr...
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Problem Set #4
Introduction Linear function Linear regression as a statistical model Decomposing the sum of squares and ANOVA Running the regression model in RStudio Factor and dummy variable Multiple Regression Regression model with two way interaction Regression Diagnostics Introduction Regression analysis: is a statistical tool used to explain the relat...
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Laboratory Exercise 5
Problem and Data set: The researcher is conducting an experiment to understand the joint effects of temperature and humidity on the growth of a specific plant species. The temperature has two levels: Low (20°C) and High (30°C), while humidity also has two levels: Low (40%) and High (80%). Each combination of temperature and humidity will be t...
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PROBLEM SET #8
Ideas of the required sample sizes of the following analysis: \(\bullet\) Simple Linear Regression \(\bullet\) Multiple Linear Regression \(\bullet\) Logistic Regression A sample is a subset of the population that enables us to make conclusions about the entire population. Gathering comprehensive information about the entire population is ...
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Problem Set #7
What is the minimum age? Answer: Min. 1st Qu. Median Mean 3rd Qu. Max. 30.00 43.00 50.00 49.27 57.00 60.00 Minimum age is: 30 In the variable “age”, group the “age” variable into two groups, with atmost 50 years and more than 50 years old. How many of them with at least 50 years old? Answer: Count of individ...
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Problem Set #3
Exercises Page 52 Page 58 Page 72 Page 80 Page 91 Page 100 Page 104 Page 115 Page 124 Page 52 fitfs <- lm(sheight ~ fheight, father.son) 1. Test whether the slope coefficient for the father.son data is different from zero (father as predictor, son as outcome). Hypothesis Testing \(H_0:\beta_1=0\) \(;\) \(H_A:\beta_1 \neq 0\) y= father.son$s...
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