Publications by Kyle Kenneth B. Ruaya

PRINCESS MERCADO GROUP STATISTICAL ANALYSIS

11.02.2024

Data 1. What is the demographic profile of the respondents in terms of: Attaching package: 'dplyr' The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union Sex Strand Daily Allowance The tables above provide the distributions of re...

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DANE MAGALUNA GROUP STATISTICAL ANALYSIS

10.02.2024

Data 1. What is the demographic profile of the respondents in terms of: Attaching package: 'dplyr' The following objects are masked from 'package:stats': filter, lag The following objects are masked from 'package:base': intersect, setdiff, setequal, union Sex Year Level Strand The tables above provides the distributions of respon...

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STAT 56 - Final Exam

29.05.2023

1 CLUSTER ANALYSIS Cluster Analysis in R, when we do data analytics, there are two kinds of approaches, one is supervised and the other is unsupervised. Clustering is a method for finding subgroups of observations within a data set. When we are doing clustering, we need observations in the same group with similar patterns and observations in di...

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Nonparametric Statistics (STAT 54) - Final Examination

28.05.2023

1. Kolmogorov-Smirnov ken <- c(21, 32, 38, 40, 48, 55, 63, 66, 70, 75, 80, 84, 86, 90, 90, 93, 95, 98, 100, 105, 106, 108, 115, 118, 126, 128, 130, 142, 145, 155) ken ## [1] 21 32 38 40 48 55 63 66 70 75 80 84 86 90 90 93 95 98 100 ## [20] 105 106 108 115 118 126 128 130 142 145 155 Null Hypothesis: The data is normally distri...

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Stat 56 - Additional Activity for Factor Analysis

20.05.2023

DATA 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 In our data frame, we have a V10 variable in the last column. So, we can use -10 in the column index to remove the last column ...

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STAT 56 - Midterm Examination

19.05.2023

DATA 1. Provide the output of the standardized data (just the first 10 rows). 2. Provide the correlation matrix of the standardized data. top incisor bottom incisor top cannine bot cannine top premol top incisor 1.00000000 -0.07181198 0.6001764 0.7431854 0.5065222 bottom incisor -0.07181198 1.00000000 0.501983...

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Publish Document

19.05.2023

Description of the data For our analysis example, we are going to expand example 1 about investigating the associations between psychological measures and academic achievement measures. We have a data file, mmreg.dta, with 600 observations on eight variables. The psychological variables are locus_of_control, self_concept and motivation. The ac...

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STAT 56 - Activity 2 (PCA)

19.05.2023

Principal Components Analysis in R We will use the Places Rated Almanac data (Boyer and Savageau) which rates 329 communities according to nine criteria: Climate and Terrain, Housing, Health Care & Environment, Crime, Transportation, Education, The Arts, Recreation and Economics. Load the Data places <- read.table("D:/Stat 56/places.txt", heade...

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STAT 54 - MIDTERM EXAM Part 2

18.05.2023

DATA 1. What is the socio- demographic profile of the respondents in terms of: 1.1 Age 1.2 Sex 1.3 Number of years 1.4 Socio-economic status 2. What is the psychological well-being of the students raised by single parents in terms of: a. Autonomy b. Environmental Mastery c. Personal growth d. Positive relations e. Purpose in life f....

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STAT 56 - Discriminant Analysis

06.05.2023

Getting Data mydata <- read.csv("C:/Users/63966/Downloads/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....

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