Publications by Kyle Kenneth B. Ruaya
PRINCESS MERCADO GROUP STATISTICAL ANALYSIS
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...
11984 sym Python (12167 sym/71 pcs) 28 img
DANE MAGALUNA GROUP STATISTICAL ANALYSIS
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...
9183 sym Python (13043 sym/65 pcs) 21 img
STAT 56 - Final Exam
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...
13637 sym R (27150 sym/83 pcs) 2 img
Nonparametric Statistics (STAT 54) - Final Examination
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...
6071 sym R (14962 sym/110 pcs) 7 img
Stat 56 - Additional Activity for Factor Analysis
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 ...
1185 sym Python (4579 sym/24 pcs) 4 img
STAT 56 - Midterm Examination
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...
1657 sym 5 img
Publish Document
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...
5905 sym 3 img
STAT 56 - Activity 2 (PCA)
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...
1980 sym 2 img
STAT 54 - MIDTERM EXAM Part 2
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....
4120 sym
STAT 56 - Discriminant Analysis
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....
1861 sym R (5448 sym/35 pcs) 13 img