http://commres.net/ 2026-04-15T14:37:35+00:00 http://commres.net/ http://commres.net/_media/wiki/logo.png text/html 2019-09-17T22:58:40+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/analysis_of_covariance?rev=1568761120&do=diff Analysis of Covariance with lm function > library(Cars93) > lm.model4 <- lm(Cars93$MPG.city ~ Cars93$EngineSize + Cars93$Price + Cars93$DriveTrain) > summary(lm.model4) Call: lm(formula = Cars93$MPG.city ~ Cars93$EngineSize + Cars93$Price + Cars93$DriveTrain) Residuals: Min 1Q Median 3Q Max -8.3153 -2.1589 -0.3703 1.3227 16.5032 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 31.3617 1.6298 19.242 < 2e-1… text/html 2022-11-07T15:20:10+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/ancova?rev=1667834410&do=diff Analysis of Covariance ANCOVA text/html 2024-04-16T23:30:30+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/anova?rev=1713310230&do=diff ANOVA in R # # 3 샘플 종류 추출 # A, B, C 학년에 따라서 욕하는 정도가 달라질것이라는 # 가설 set.seed(201) rnorm2 <- function(n,mean,sd){ mean+sd*scale(rnorm(n)) } A <- rnorm2(16, 26, sqrt(600/15)) B <- rnorm2(16, 24, sqrt(750/15)) C <- rnorm2(16, 19, sqrt(900/15)) A <- c(A) B <- c(B) C <- c(C) # 평균구하기 mean(A) mean(B) mean(C) # 3 샘플을 합치기 # 두번재 컬럼 = group A, B, C 가 되도록 comb3 <- stack(list(a=A, b=B, c=C)) comb3 colnames(comb3)[1] <- "values" colnames(comb3)[2] <- "group" comb3 # 전체구성원을 하나로 보고 분산값을 구해본다 # ms.tot = ss… text/html 2019-09-17T22:59:32+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/apply?rev=1568761172&do=diff <https://www.guru99.com/r-apply-sapply-tapply.html> statistics r r_function apply text/html 2019-09-17T23:00:25+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/baseball_data?rev=1568761225&do=diff <http://score.sports.media.daum.net/record/baseball/kbo/brnk.daum> <http://www.koreabaseball.com/Record/Player/HitterBasic/Basic1.aspx> #Part 2 - 도전 미션 3-1 -소스코드 setwd("c:\\r_temp") data <- read.csv("baseball_performance.csv", header=T) head(data,25) data$forward_rate <- (data$출루율/data$연봉)*100 bp <- barplot(data$forward_rate, main=paste("연봉대비 출루율"), col=rainbow(25), cex.names=0.7, las=2, names.arg=data$선수명, ylim=c(0,50)) title(ylab="연봉대비출루율", col.lab="re… text/html 2019-09-25T01:32:27+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/basics?rev=1569375147&do=diff Print > pi [1] 3.141593 > sqrt(2) [1] 1.414214 When you enter expressions like that, R evaluates the expression and then implicitly calls the print function. So the previous example is identical to this: > print(pi) [1] 3.141593 > print(sqrt(2)) [1] 1.414214 $$ r = \frac {\text{covariance (x, y)}} {sd(x) * sd(y)} $$ text/html 2020-12-01T07:09:43+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/broken_character_when_importing_csv?rev=1606806583&do=diff read.csv("http://commres.net/wiki/_media/elemapi2.csv", fileEncoding="UTF-8-BOM") fileEncoding=“UTF-8-BOM” 을 붙일것 text/html 2025-12-02T23:00:22+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/chi-square_test?rev=1764716422&do=diff chi square test eg. 1 chi square test eg. 2 chi square test eg. 3 statistics r chi-square_test text/html 2019-11-21T05:35:27+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/concor?rev=1574314527&do=diff CONCOR in R <http://homepage.ntu.edu.tw/~wenthung/R_Network/Lab5.html> #REPLICATE BREIGER ET AL. (1975) #INSTALL CONCOR devtools::install_github("aslez/concoR") #LIBRARIES library(concoR) library(sna) #LOAD DATA data(bank_wiring) bank_wiring #CHECK INITIAL CORRELATIONS (TABLE III) m0 <- cor(do.call(rbind, bank_wiring)) round(m0, 2) #IDENTIFY BLOCKS USING A 4-BLOCK MODEL (TABLE IV) blks <- concor_hca(bank_wiring, p = 2) blks #CHECK FIT USING SNA (TABLE V) #code below fails unless glabels … text/html 2018-12-26T06:19:48+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/correlation?rev=1545805188&do=diff Correlation cor(data.frame, method=c("pearson", "kendall", "spearman")) cor.test(data$acol, data$bcol, method=c("pearson", "kendall", "spearman")) data("mtcars") my_data <- mtcars[, c(1,2,3,4,5,6,7)] head(my_data) mpg cyl disp hp drat wt qsec Mazda RX4 21.0 6 160 110 3.90 2.620 16.46 Mazda RX4 Wag 21.0 6 160 110 3.90 2.875 17.02 Datsun 710 22.8 4 108 93 3.85 2.320 18.61 Hornet 4 Drive 21.4 6 258 110 3.08 3.215 19.44 Hornet Sportab… text/html 2025-12-06T11:40:58+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/data?rev=1765021258&do=diff : Motivating example Suppose you are a researcher studying the effects of student background on academic achievement. The lab recently finished collecting and uploading the dataset (worland5.csv) of students each with 9 observed variables: Motivation, Harmony, Stability, Negative Parental Psychology, SES, Verbal IQ, Reading, Arithmetic and Spelling. The principal investigator hypothesizes three latent constructs Adjustment, Risk, Achievement measured with its corresponding to the following codeb… text/html 2019-09-19T09:16:51+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/data_structures?rev=1568884611&do=diff DATA Vectors * 벡터 * Vectors are homogeneous: All elements of a vector must have the same type. * Vectors can be indexed by position: v[2] refers to the second element of v. * Vectors can be indexed by multiple positions, returning a subvector: v text/html 2019-09-19T09:23:05+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/data_transformations?rev=1568884985&do=diff > v <- c(40,2,83,28,58) > f <- factor(c("A","C","C","B","C")) Splitting a Vector into Groups > library(MASS) Warning message: 패키지 ‘MASS’는 R 버전 3.2.5에서 작성되었습니다 > split(Cars93$MPG.city, Cars93$Origin) # Origin별로 MPG.city를 나눠라 $USA [1] 22 19 16 19 16 16 25 25 19 21 18 15 [13] 17 17 20 23 20 29 23 22 17 21 18 29 [25] 20 31 23 22 22 24 15 21 18 17 18 23 [37] 19 24 23 18 19 23 31 23 19 19 19 28 $`non-USA` [1] 25 18 20 19 22 46 30 24 42 24 29 22 [13] 26 20 17 18 18 29 28 26 18 17 20 19 [25] 29 1… text/html 2017-12-20T23:00:06+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/deleting_columns_in_data_frame_by_names?rev=1513810806&do=diff > read.csv("http://commres.net/wiki/_media/r/efa.csv", header = T) > str(efa) 'data.frame': 90 obs. of 14 variables: $ Price : int 4 3 4 4 5 4 3 4 5 4 ... $ Safety : int 4 5 4 4 5 4 4 3 4 4 ... $ Exterior_Looks : int 5 3 3 4 4 5 3 4 5 3 ... $ Space_comfort : int 4 3 4 3 4 3 4 4 4 3 ... $ Technology : int 3 4 5 3 5 4 3 5 3 5 ... $ After_Sales_Service: int 4 4 5 4 4 5 5 4 5 4 ... $ Resale_Value : int 5 3 5 5 5 3 3 5 5 5 ... $ Fuel_Typ… text/html 2016-12-14T01:27:25+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/document_classification?rev=1481678845&do=diff Document Classification text/html 2025-09-10T22:32:00+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/drawing_sampling_distribution_plot?rev=1757543520&do=diff rm(list=ls()) rnorm2 <- function(n,mean,sd){ mean+sd*scale(rnorm(n)) } n.p <- 10000 m.p <- 100 sd.p <- 10 p1 <- rnorm2(n.p, m.p, sd.p) m.p1 <- mean(p1) sd.p1 <- sd(p1) p2 <- rnorm2(n.p, m.p+5, sd.p) m.p2 <- mean(p2) sd.p2 <- sd(p2) n.s <- 100 se.z <- c(sqrt(var(p1)/n.s)) x_values <- seq(mean(p1)-5*se.z, mean(p1)+15*se.z, length.out = 500) # Calculate the probability # density for a normal distribution y_values <- dnorm(x_values, mean… text/html 2025-06-10T23:37:35+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/dummy_variable?rev=1749598655&do=diff Dummy variables in Multiple Regression datavar <- read.csv("http://commres.net/wiki/_media/r/elemapi2.csv", fileEncoding="UTF-8-BOM") 위는 미국 초등학교 학생의 API 결과와 학교에 대한 (측정단위) 정보를 포함하는 데이터이다. 변인의 정보는 아래와 같다. text/html 2023-06-05T13:01:05+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/dummy_variables_with_significant_interaction?rev=1685970065&do=diff Regression with two categorical variables (IVs): Two way anova <https://advstats.psychstat.org/book/mregression/catpredictor.php#example-4-regression-with-one-categorical-and-one-continuous-predictors-ancova> college <- read.csv("http://commres.net/wiki/_media/r/college.csv") attach(college) str(college) head(college) salary <- salary / 1000 public<-factor(public, c(0,1), labels=c('Private', 'Public')) location<-factor(location, c(1,2,3,4), labels=c('S', 'MW','NE', 'W')) m1 <- lm(salary~pu… text/html 2017-11-23T09:12:34+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/extracting_variable_names_and_lables?rev=1511428354&do=diff z <- gzcon(url("http://commres.net/wiki/_media/r/states.rds")) data <- read.RDS(z) head(data, 8) > head(data,8) X state region pop area density metro waste energy miles toxic green house 1 1 Alabama South 4041000 52423 77.08 67.4 1.11 393 10.5 27.86 29.25 30 2 2 Alaska West 550000 570374 0.96 41.1 0.91 991 7.2 37.41 NA 0 3 3 Arizona West 3665000 113642 32.25 79.0 0.79 258 9.7 19.65 18.37 13 4 4 Arkansas South … text/html 2026-04-14T23:36:51+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/factorial_anova?rev=1776209811&do=diff Two-way ANOVA Factorial ANOVA 라고도 부른다. rm(list=ls(all=TRUE)) ################################################# # two-way anova # subject = factor(paste('sub', 1:30, sep='')) ################################################# n.a.group <- 3 # a treatment 숫자 e.g: drug a1, a2, a3 n.b.group <- 2 # b 그룹 숫자 e.g.: exercise no(b1), yes(b2) n.sub <- 30 # 총 샘플 숫자 n.sub/n.a.group # 데이터 생성 set.seed(9) a <- gl(n.a.group, n.sub/n.a.group, n.sub, labels=c('drg1', 'drg2', 'drg3'… text/html 2022-05-05T05:47:05+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/factor_analysis?rev=1651729625&do=diff see factor analysis data file: data file: text/html 2016-05-22T21:55:40+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/florentine?rev=1463954140&do=diff Florentine family study ergm package에 포함된 데이터이다. library(ergm) data() data(florentine) florentine {ergm} R Documentation Florentine Family Marriage and Business Ties Data as a “network“ object Description This is a data set of marriage and business ties among Renaissance Florentine families. The data is originally from Padgett (1994) via UCINET and stored as a network object. text/html 2016-09-09T01:05:26+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/ftest?rev=1473383126&do=diff A: 175, 168, 168, 190, 156, 181, 182, 175, 174, 179 B: 120, 180, 125, 188, 130, 190, 110, 185, 112, 188 a = c(175, 168, 168, 190, 156, 181, 182, 175, 174, 179) b = c(120, 180, 125, 188, 130, 190, 110, 185, 112, 188) var.test(b,a) F test to compare two variances data: b and a F = 14.6431, num df = 9, denom df = 9, p-value = 0.0004636 alternative hypothesis: true ratio of variances is not equal to 1 95 percent confidence interval: 3.637133 58.952936 sample estimates: ratio of variance… text/html 2019-10-10T22:56:39+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/general_statistics?rev=1570748199&do=diff Null Hypotheses, Alternative Hypotheses, and p-Values 9.1. Summarizing Your Data library(MASS) # to include Cars93 data > summary(Cars93$Manufacturer) Acura Audi BMW Buick 2 2 1 4 Cadillac Chevrolet Chrylser Chrysler 2 8 1 2 Dodge Eagle Ford Geo 6 2 8 2 … text/html 2020-05-05T07:46:27+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/generating_a_random_data_set_with_certain_correlations?rev=1588664787&do=diff Generating a random data set with certain correlations n.d <- 60 r12 <- .82 mu <- c(4, 2) n.var <- length(mu) stddev <- c(1, 1) corMat <- matrix(c(1, r12, r12, 1), ncol = n.var) corMat covMat <- stddev %*% t(stddev) * corMat covMat set.seed(10) library(MASS) d1 <- mvrnorm(n = n.d, mu = mu, Sigma = covMat, empirical = TRUE) d1 <- data.frame(d1) colnames(d1) <- c("x", "y") colMeans(d1) cor(d1) pairs(d1) d1 plot(d1, main="covariance and correlation between x… text/html 2025-12-20T00:34:06+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/geom?rev=1766190846&do=diff Understanding R's Definition In R, the syntax for the geometric cumulative distribution function is * pgeom(q, prob, lower.tail = TRUE)  * q : The number of failures before the first success occurs. * prob : The probability of success in a single trial $(p)$ text/html 2025-12-20T03:23:03+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/geom_function_in_r?rev=1766200983&do=diff dgeom dgeom(x, p) # x = number of q (failure) # p = probability of success pgeom 시리얼 박스 중 20%가 공짜장난감이 포함되어 있다고 한다. 첫번째 장남감을 얻기 위해서 4 박스 미만의 시리얼 박스를 여는 확률은? text/html 2021-03-02T00:48:52+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/getting_started?rev=1614646132&do=diff Installation, base Windows * Open <http://www.r-project.org/> in your browser. * Click on “CRAN”. You’ll see a list of mirror sites, organized by country. * Select a site near you. * Click on “Windows” under “Download and Install R”. * Click on “base”. text/html 2017-06-07T08:53:15+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/googlevis?rev=1496825595&do=diff Worldbank data e.g. library(googleVis) demo(googleVis) Sys.setlocale(category = "LC_ALL", locale = "us") install.packages("googleVis") library(googleVis) demo(WorldBank) ## Sys.setlocale("LC_CTYPE", "en_US.UTF-8") ## comment out if encoding problem occurs Sys.setlocale(category = "LC_ALL", locale = "us") ## SOURCE: http://lamages.blogspot.co.uk/2011/09/accessing-and-plotting-world-bank-data.html ## This demo shows how country level data can be accessed from the World Bank via their API a… text/html 2017-11-27T01:27:21+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/graphics?rev=1511746041&do=diff Notes on Graphics Functions It is important to understand the distinction between high-level and low-level graphics functions. A high-level graphics function starts a new graph. It initializes the graphics window (creating it if necessary); sets the scale; maybe draws some adornments, such as a title and labels; and renders the graphic. Examples include: text/html 2025-09-13T13:04:50+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/hypothesis_testing?rev=1757768690&do=diff Hypothesis testing rm(list=ls()) rnorm2 <- function(n,mean,sd){ mean+sd*scale(rnorm(n)) } set.seed(101) n.p <- 10000 m.p <- 100 sd.p <- 10 p1 <- rnorm2(n.p, m.p, sd.p) m.p1 <- mean(p1) sd.p1 <- sd(p1) p2 <- rnorm2(n.p, m.p+3, sd.p) m.p2 <- mean(p2) sd.p2 <- sd(p2) n.s <- 36 se.z1 <- c(sqrt(var(p1)/n.s)) se.z2 <- c(sqrt(var(p2)/n.s)) x.p1 <- seq(mean(p1)-5*se.z1, mean(p2)+5*se.z1, length.out = 500) x.p2 <- seq(mean(p2)-5*se.z1, mean(p2)+5*… text/html 2018-01-11T00:40:04+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/igraph?rev=1515631204&do=diff see <http://kateto.net/networks-r-igraph> igraph tutorial Examples for the igraph package nodes (vertex) edges (lines) * freight schedule * friendship * contact * relationship social network adjency matrix edge list - economical way to store data library(igraph) # df = data frame data g <- graph.edgelist(as.matrix(df), directed = FALSE) text/html 2019-09-20T01:32:09+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/input_output?rev=1568943129&do=diff A Philosophical Note on R input system Several of my Statistical Analysis System (SAS) friends are disappointed with the input facilities of R. They point out that SAS has an elaborate set of commands for reading and parsing input files in many formats. R does not, and this leads them to conclude that R is not ready for real work. After all, if it can’t read your data, what good is it? text/html 2015-11-05T05:49:27+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/lecture?rev=1446702567&do=diff Data R과 함께 인스톨된 public data들은 <http://127.0.0.1:13732/library/datasets/html/00Index.html> 에서 참조가 가능하다. Descriptive Statistics R 명령어 표본수 length(v) 평균 mean(v) 분산 var(v) 표준편차 sd(v) 표준오차 sd(v)/sqrt(length(v)) text/html 2019-06-13T01:15:43+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/linear_regression?rev=1560388543&do=diff Simple Linear Regression yi = β0 + β1xi + εi where β0 and β1 are the regression coefficients and the εi are the error terms. library(MASS) attach(Cars93) plot(MPG.city~EngineSize) mod <- lm(MPG.city ~ EngineSize) mod Call: lm(formula = MPG.city ~ EngineSize) Coefficients: (Intercept) EngineSize 32.627 -3.846 summary(mod) Call: lm(formula = MPG.city ~ EngineSize) Residuals: Min 1Q Median 3Q Max -10.6264 -2.7032 -0.5491 2.1428 17.219… text/html 2023-12-06T23:00:33+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/logistic_regression_analysis?rev=1701903633&do=diff e.g. 1 > Logit(Turnover ~ JS, data=td) Data Frame: mydata Response Variable: Turnover Predictor Variable 1: JS Number of cases (rows) of data: 99 Number of cases retained for analysis: 98 BASIC ANALYSIS -- Estimated Model of Turnover for the Logit of Reference Group Membership Estimate Std Err z-value p-value Lower 95% Upper 95% (Intercept) -1.8554 0.6883 -2.695 0.007 -3.2044 -0.5063 JS 0.4378 0.1958 2.236 0.02… text/html 2017-11-13T01:33:38+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/lowbwt_dataset?rev=1510536818&do=diff see <https://notendur.hi.is/birgirhr/lowbwt.txt> ******************************** * low birth weight * ******************************** * These data come from Appendix 1 of Hosmer and Lemeshow (1989), and were collected at Baystate Medical Center, Springfield MA, during 1986. * Low birth weight is an outcome that has been of concern to physicians for years. This is due to the fact that infant mortality rates and birth defect rates are very high for low birth weight babies. A wo… text/html 2023-10-18T23:23:54+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/multiple_regression?rev=1697671434&do=diff Multiple Regression [data file] University of New Mexico enrollment data (for 30 years) ROLL: # of enrollment UNEM: enemployment level HGRAD: # of High school graduates INC: income level # data import > datavar <- read.csv("http://commres.net/wiki/_media/r/dataset_hlr.csv") > str(datavar) 'data.frame': 29 obs. of 5 variables: $ YEAR : int 1 2 3 4 5 6 7 8 9 10 ... $ ROLL : int 5501 5945 6629 7556 8716 9369 9920 10167 11084 12504 ... $ UNEM : num 8.1 7 7.3 7.5 7 6.4 6.5 6.4 6.3 7.7 ..… text/html 2019-09-20T01:19:50+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/navigating?rev=1568942390&do=diff Working Directory Getting > getwd() [1] "/home/paul/research" > setwd("Bayes") > getwd() [1] "/home/paul/research/Bayes" setwd("c:/r_data") getwd() Saving Workspace > save.image() Command History > history() # Default 25 > history(100) # Show 100 most recent lines of history > history(Inf) # Show entire saved history text/html 2016-12-14T00:32:24+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/neural_network?rev=1481675544&do=diff Neural Network > install.packages("nnet") > library(nnet) > m <- nnet(Species ~ ., data=iris, size=3) # weights: 27 initial value 191.494035 iter 10 value 65.618496 iter 20 value 40.493306 iter 30 value 8.542349 iter 40 value 6.034377 iter 50 value 6.000246 iter 60 value 5.998411 iter 70 value 5.983894 iter 80 value 5.972932 iter 90 value 5.968740 iter 100 value 5.965371 final value 5.965371 stopped after 100 iterations > round(predict(m, newdata=iris),2) setosa versicolor vir… text/html 2022-04-28T01:26:00+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/oneway_anova?rev=1651109160&do=diff Oneway ANOVA data see <https://github.com/hkimscil/ms/blob/main/anova.R> (온도조건)x1 50.5 52.1 51.9 52.4 50.6 51.4 51.2 52.2 51.5 50.8 (온도조건)x2 47.5 47.7 46.6 47.1 47.2 47.8 45.2 47.4 45.0 47.9 (온도조건)x3 46.0 47.1 45.6 47.1 text/html 2018-12-14T03:33:30+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/partial_and_semipartial_correlation?rev=1544758410&do=diff Not usable yet. > sat <- c(500, 550, 450, 400, 600, 650, 700, 550, 650, 550) > hsgpa <- c(3, 3.2, 2.8, 2.5, 3.2, 3.8, 3.9, 3.8, 3.5, 3.1) > fgpa <- c(2.8, 3, 2.8, 2.2, 3.3, 3.3, 3.5, 3.7, 3.4, 2.9) > dat <- data.frame(sat,hsgpa,fgpa) > dat sat hsgpa fgpa 1 500 3.0 2.8 2 550 3.2 3.0 3 450 2.8 2.8 4 400 2.5 2.2 5 600 3.2 3.3 6 650 3.8 3.3 7 700 3.9 3.5 8 550 3.8 3.7 9 650 3.5 3.4 10 550 3.1 2.9 > text/html 2025-11-30T23:22:51+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/path_analysis?rev=1764544971&do=diff Path Analysis Introduction Regressions vs. Path Analysis (or SEM) * Intention = a1 + b1(Attitude) + b2(Norms) + b3(Control) * Behavior = a2 + b4(Intention) * When in a combined situation, we use * Path Analysis or SEM Model Identification$p(p+1)/2$$\chi^2$$\text{CFI}$$\text{TLI}$$\text{RMSEA}$$\text{SRMR}$$p \ge .05$$p \ge .90$$p \ge .95$$p \le .08$$p \le .08$ text/html 2026-04-14T23:24:53+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/probability?rev=1776209093&do=diff Normal distribution functions Function Purpose dnorm Normal density pnorm Normal distribution function qnorm Normal quantile function rnorm Normal random variates Table 8-1. Discrete distributions Discrete distribution R name $ f(x) = \frac{1}{\sigma \sqrt{2\pi}} e^{\frac{-(x-\mu)^2}{2\sigma^2}} $$t = \frac{Z}{\sqrt{\frac{V}{m}}}$$$n!/r!(n − r)!$$ text/html 2025-10-12T22:57:28+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/regression?rev=1760309848&do=diff Simple Regression in R ########################### # regression sum up ########################### rm(list = ls()) rnorm2 <- function(n,mean,sd){ mean+sd*scale(rnorm(n)) } set.seed(101) n.s <- 36 m.x <- 100 df.x <- m.x - 1 ssq.x <- 100 x <- rnorm2(n.s, m.x, sqrt(9900/df.x)) y <- 5*x + rnorm2(n.s, 0, 36) df <- data.frame(x,y) mod.r <- lm(y ~ x, data = df) summary(mod.r) sp.xy <- sum((x-mean(x))*(y-mean(y))) df.tot <- length(y) - 1 cov.xy <- sp.xy / df.tot cov.xy cov(x,y) cor.xy <- cov.xy … text/html 2018-12-15T16:24:56+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/regression_diagnostics?rev=1544891096&do=diff Regression Diagnostics # Assume that we are fitting a multiple linear regression # on the MTCARS data library(car) fit <- lm(mpg~disp+hp+wt+drat, data=mtcars) Outliers # Assessing Outliers outlierTest(fit) # Bonferonni p-value for most extreme obs qqPlot(fit, main="QQ Plot") #qq plot for studentized resid leveragePlots(fit) # leverage plots text/html 2020-06-03T15:53:32+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/repeated_measures_anova?rev=1591199612&do=diff Repeated measures ANOVA e.g. 1 demo1 <- read.csv("https://stats.idre.ucla.edu/stat/data/demo1.csv") ## Convert variables to factor demo1 <- within(demo1, { group <- factor(group) time <- factor(time) id <- factor(id) }) demo1 par(cex = .6) with(demo1, interaction.plot(time, group, pulse, ylim = c(5, 20), lty= c(1, 12), lwd = 3, ylab = "mean of pulse", xlab = "time", trace.label = "group")) demo1.aov <- aov(pulse ~ group * time + Error(id), data = demo1) summary(demo1.aov) text/html 2025-05-11T23:25:22+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/repeated_measure_anova?rev=1747005922&do=diff E.g. 1 ################################################### ################################################### ################################################### # data df <- data.frame(patient=rep(1:5, each=4), drug=rep(1:4, times=5), response=c(30, 28, 16, 34, 14, 18, 10, 22, 24, 20, 18, 30, 38, 34, 20, 44, 26, 28, 14, 30)) #view data df write… text/html 2017-06-07T22:26:29+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/sampling?rev=1496874389&do=diff r function: sample Usage sample(x, size, replace = FALSE, prob = NULL) sample.int(n, size = n, replace = FALSE, prob = NULL, useHash = (!replace && is.null(prob) && size <= n/2 && n > 1e7)) Arguments * x : either a vector of one or more elements from which to choose, or a positive integer. See ‘Details.’ text/html 2026-03-24T10:17:11+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/sampling_distribution?rev=1774347431&do=diff R script output 설명없는 full R script와 output은 r script and output 이미 우리는 샘플평균들 집합의 평균과 분산값이 무엇이 되는가를 수학적으로 알아보았다. mean and variance of the sample mean. > rm(list=ls()) > rnorm2 <- function(n,mean,sd){ + mean+sd*scale(rnorm(n)) + } > > ss <- function(x) { + sum((x-mean(x))^2) + } > $ \dfrac {(\text{score} - \text{m.p1})} {\text{sd.p1}} $$ (100-100) / 10 = 0 $\begin{eqnarray*} \overline{X} \sim \displaystyle \text{N} \left(\mu, \dfrac{\sigma^{2}}{n} \right) \end{eqnarray*}\begin{eqnarray… text/html 2018-11-26T00:59:22+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/semipartial?rev=1543193962&do=diff <https://rpubs.com/KwonPublishing/249631> n.sample <- 10000 rho <- 0.05 dat <- mvrnorm(n.sample, c(0,0), matrix(c(1,rho,rho,1),2)) C1 <- dat[,1] C2 <- dat[,2] X <- rnorm(n.sample) + C1 + C2 Y <- rnorm(n.sample) + 0.5*C1 + C2 + X dat <- data.frame(Y, X, C1, C2) plot(dat, col=rgb(0,0,0,alpha=min(1, 1000/n.sample))) $$ r_{12.3} = \cfrac { \text r^{}_{12} - r^{}_{13}r^{}_{23}} { \sqrt{1-r^{2}_{13}} \sqrt{1-r^{2}_{23}} } $$$$ r_{12.3} = \cfrac { \text .88 - (.87)(.72)} { \sqrt{1-.87^{2}} \sqr… text/html 2024-11-14T00:02:02+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/social_network_analysis?rev=1731542522&do=diff Data Hawthorne study # install.packages(c("igraph", "tidyverse")) library(igraph) library(tidyverse) sd <- read.csv("http://commres.net/wiki/_media/r/davis.women.club.csv") head(sd) g <- graph.data.frame(sd, directed=FALSE) bipartite.mapping(g) plot(g) V(g)$color <- ifelse(V(g)$type, "lightblue", "salmon") V(g)$shape <- ifelse(V(g)$type, "circle", "square") E(g)$color <- "lightgray" plot(g, vertex.label.cex = 1.2, vertex.label.color = "black") text/html 2023-11-22T23:50:36+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/social_network_analysis_tutorial?rev=1700697036&do=diff T1. install.packages("igraph") see <https://igraph.org/r/doc/index.html> Dataset "source","target","weight" "C-3PO","R2-D2",17 "LUKE","R2-D2",13 "OBI-WAN","R2-D2",6 "LEIA","R2-D2",5 "HAN","R2-D2",5 "CHEWBACCA","R2-D2",3 "DODONNA","R2-D2",1 "CHEWBACCA","OBI-WAN",7 "C-3PO","CHEWBACCA",5 "CHEWBACCA","LUKE",16 "CHEWBACCA","HAN",19 "CHEWBACCA","LEIA",11 "CHEWBACCA","DARTH VADER",1 "CHEWBACCA","DODONNA",1 "CAMIE","LUKE",2 "BIGGS","CAMIE",2 "BIGGS","LUKE",4 "DARTH VADER","LEIA",1 "BERU","LUKE",3 "B… text/html 2019-01-16T05:11:55+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/song_lyrics?rev=1547615515&do=diff <https://www.r-bloggers.com/data-wonderland-christmas-songs-from-the-viewpoint-of-a-data-scientist/?utm_content=buffere0e72&utm_medium=social&utm_source=twitter.com&utm_campaign=buffer> Lyric Analysis with NLP & Machine Learning with R Tidy Sentiment Analysis in R Machine Learning and NLP using R: Topic Modeling and Music Classification Lyric Analysis: Predictive Analytics using Machine Learning with R text/html 2017-09-14T00:12:36+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/standard_error?rev=1505347956&do=diff Standard deviation: plot(seq(-3.2,3.2,length=50),dnorm(seq(-3,3,length=50),0,1),type="l",xlab="",ylab="",ylim=c(0,0.5)) segments(x0 = c(-3,3),y0 = c(-1,-1),x1 = c(-3,3),y1=c(1,1)) text(x=0,y=0.45,labels = expression("99.7% of the data within 3" ~ sigma)) arrows(x0=c(-2,2),y0=c(0.45,0.45),x1=c(-3,3),y1=c(0.45,0.45)) segments(x0 = c(-2,2),y0 = c(-1,-1),x1 = c(-2,2),y1=c(0.4,0.4)) text(x=0,y=0.3,labels = expression("95% of the data within 2" ~ sigma)) arrows(x0=c(-1.5,1.5),y0=c(0.3,0.3),x1=c(-2… text/html 2016-09-23T01:37:30+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/starting?rev=1474594650&do=diff Setting working directory > getwd > setwd Saving Workspace > save.image() Command History > history() Saving the Result of the Previous Command > x <- .Last.value # Capture the result now > x [1] 147.6549 text/html 2024-04-14T23:52:49+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/t-test?rev=1713138769&do=diff One sample t-test against population parameter mu and sigma > rnorm2 <- function(n,mean,sd) { mean+sd*scale(rnorm(n)) } > potato_sample <- rnorm2(25, 194,20) > mean(potato_sample) [1] 194 > sqrt(var(potato_sample)) [,1] [1,] 20 > t.test(potato_sample, mu=200) One Sample t-test data: potato_sample t = -1.5, df = 24, p-value = 0.1467 alternative hypothesis: true mean is not equal to 200 95 percent confidence interval: 185.7444 202.2556 sample estimates: mean of x 194 > … text/html 2018-10-18T23:39:06+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/twoway_anova?rev=1539905946&do=diff data sample: Twoway ANOVA recap of oneway ANOVA # One Way Anova (Completely Randomized Design) fit <- aov(y ~ A, data=mydataframe) Twoway ANOVA without interaction # Randomized Block Design (B is the blocking factor) fit <- aov(y ~ A + B, data=mydataframe) text/html 2025-04-30T00:00:05+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/twoway_repeated_measure_anova?rev=1745971205&do=diff see * <https://www.r-bloggers.com/2025/02/two-way-repeated-measures-anova-in-r/> * <https://www.r-bloggers.com/2015/08/two-way-anova-with-repeated-measures/> * <https://agroninfotech.blogspot.com/2020/06/two-way-repeated-measures-analysis-in-r.html> * <https://stackoverflow.com/questions/37497948/aov-error-term-in-r-whats-the-difference-bw-errorid-and-errorid-timevar> * <https://stats.stackexchange.com/questions/60108/how-to-write-the-error-term-in-repeated-measures-anova-in-r-errorsu… text/html 2026-04-07T23:02:31+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/two_sample_t-test?rev=1775602951&do=diff Independent sample t-test 의 standard error 값을 구하는 방법이 얼른 머리에 들어오지 않으면, see mean and variance of the sample mean: 샘플평균들의 집합이 가지는 평균과 분산 (CLT) sa statistical review: 분산의 계산 두 샘플을 취해서 평균을 구한 후 (mean of A, mean of B), 그 차이를 기록하는 것을 무한히 하여 그 분포를 구하는 것은 아래와 같이 정리, 이해할 수 있다. \begin{eqnarray} E \left[ \overline{X} - \overline{Y} \right] & = & E \left[ \overline{X} \right] - E \left[ \overline{Y} \right] & = & {\mu_{X}} - {\mu_{Y}} \\ V \left[ \overline{X} - \overline{Y} \right] & = & V \left[ \overli… text/html 2025-09-28T23:27:17+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/types_of_error?rev=1759102037&do=diff Type of Error see hypothesis testing in r space and hypothesis testing Type I Error ########################################### # type 1 error ########################################### rm(list=ls()) rnorm2 <- function(n,mean,sd){ mean+sd*scale(rnorm(n)) } # m.treated.s.but.not.work from p1 # = 104.022, red dot line # type 1 error set.seed(1292) n.p <- 10000 m.p <- 100 sd.p <- 10 p1 <- rnorm2(n.p, m.p, sd.p) m.p1 <- mean(p1) sd.p1 <- sd(p1) p2 <- rnorm2(n.p, m.p+5, sd.p) m.p2 <… text/html 2017-06-30T16:31:46+00:00 Anonymous (anonymous@undisclosed.example.com) http://commres.net/r/utf-8?rev=1498840306&do=diff <http://semanticweb.cs.vu.nl/R/sparql_hollywood/sparql_hollywood.html>