similar to: Recommendations regarding textbooks

I would like to buy a basic statistics book (experimental design, sampling, ANOVA, regression, etc.) with examples in R. Or download it in PDF or html format. I went to the CRAN contributed documentation, but there were only R textbooks, that is, textbooks where R is the focus, not the statistics. And I would like to find the opposite. Other text I am trying to find is multivariate data

Hello, I'm looking for a textbook that can explain some of the math behind the intro-to-intermediate stuff like ANOVA, multiple regression, non- parametric tests, etc. A little background: I took an intro stats course last year and would like to further my education. Being as that was the highest (and only) stats class the local community college offers, it looks like I'm on

Could somebody recommend some good nonparametric statistical inference textbooks for a beginner? And what are pros and cons of each book? Nonparametric statistical methods by Hollander seems to be more difficult for a beginner, but is great as a reference, right? Are there any books that are easier to learn than Hollander's? Also, I see some books in the wiki page. I don't find the

Dear R experts, I would like to explore if and to what extent bootstrapping and permutation statistics can help me for my research (functional brain imaging). I am looking for an introductory textbook, rather legible. I have statistical knowledge, but I am definitely no statistical or mathematical guru. Do you have suggestions for a useful textbook? Thanks a lot, Peter

Hi All, I'm preparing to co-teach a class on applied MCMC using R as the computational engine in the spring. As a consequence, I'm starting to look at MCMC textbooks. Please send along your recommendations! I will collate the responses and post a summary, so please reply to me directly. Thanks, -G

I'd like to estimate an ordinal logistic regression with a random effect for a grouping variable. I do not find a pre-packaged algorithm for this. I've found methods glmmML (package: glmmML) and lmer (package: lme4) both work fine with dichotomous dependent variables. I'd like a model similar to polr (package: MASS) or lrm (package: Design) that allows random effects. I was

R-helpers: I'm sure this question has been asked and answered through the ages, but given there are some new textbooks out there, I wanted to re-pose it. For a course that will cover the application of R for general computing and spatial modeling, what textbook would be best to introduce computing with R to *undergrads*? I understand Bivand and Pebesma's book is fine for spatial work,

Hi everyone! I've recently begun to learn R for my job as the IT department suffers from lack of funding for new software. I was talking to the guy in charge of Requisitions and have found out the budget for books is in great shape. So, I'm curious what books people know of that have R examples and are good for: 1.) Uni and Multivariate Time Series Analysis/Forecasting 2.) GLMs (at

Here's a skeletal example. Embellish as needed: p <- 5 n <- 300 set.seed(1) dat <- cbind(rnorm(n), matrix(runif(n * p), n, p)) write.table(dat, file="c:/temp/big.txt", row=FALSE, col=FALSE) xtx <- matrix(0, p + 1, p + 1) xty <- numeric(p + 1) f <- file("c:/temp/big.txt", open="r") for (i in 1:3) { x <- matrix(scan(f, nlines=100), 100,

Please forgive a statistics question. I know that a simple bivariate linear regression, y=f(x) or in R parlance lm(y~x) can be solved using the variance-covariance matrix: beta(x)=covariance(x,y)/variance(x). I also know that a linear regression with multiple independent variables, for example y=f(x,z) can also be solved using the variance-covariance matrix, but I don't know how to do this.

I'm looking for a histogram variant in which data points are plotted as labelled rectangles 'piled up' to form a histogram. I've posted an example at https://www.dropbox.com/s/ozi8bhdn5kqaufm/labelled_histogram.png?dl=0 It seems to have a long pedigree, as I see it (as in this example) in documents going back beyond the '80s. But I've not seen it in recent textbooks. So it

Hello: Could you please suggest the best way to become an "advanced" R programmer. I went through "R for dummies" by de Vries and Meys and I can see two ways to proceed: 1) Get a more advanced textbook. E.g. could you recommend Gentleman, "R for Bioinformatics"? 2) Because textbooks are limited and become obsolete fast, I can focus on learning state-of-the-art

Dear mailing list members, I am a beginner of this community. I would like to analyze data in a .rdata file. I ran the following code, but the object "d" remained empty. d <- load("~/docdis/input/ch2/WV6_Data_R_v_2016_01_01.rdata") I would like to know how to convert this file format into .csv or .txt. I suppose this question is very basic, but I could not find solutions

Dear all, I have the following output generated by linear regression. Since there is only one regression intercept and one slope for one set of data, what is the meaning of std. error for intercept and that of slope? Thanks in advance. Sincerely, Minghua > data(thuesen) > attach(thuesen) > lm(short.velocity~blood.glucose) Call: lm(formula = short.velocity ~ blood.glucose)

Dear Lists, I got the chance to review Bob Muenchen's book - R for SAS and SPSS users. While my detailed review is online at www.decisionstats.com, the book is a welcome addition in R Textbooks for beginners and an especially nice one for people who have experience in SAS and /or SPSS languages. AT 50 USD, it's reasonably priced for all geographies (;) , and quite handy as a refernce book

Please, is possible (with rsync) re-create files timestamps? I mean something like choosing a "-T" in the program mirror- from it's man page e.g. there: http://sunsite.univie.ac.at/textbooks/mirror/mirror.html#Flags "Do not do any file transfers just force the time-stamps of any local files to be reset to be the same as the remote files. Normally only used when initialising a

I asked: > In this discussion of seq(), can anyone explain to > me _why_ seq(to=n) and seq(length=3) have different > types? Martin Maechler <maechler@stat.math.ethz.ch> replied: well, the explantion isn't hard: look at seq.default :-) That's the "efficient cause", I was after the "final cause". That is, I wasn't asking "what is it

The solve function in r-patched has been changed so that it applies a tolerance when using Lapack routines to calculate the inverse of a matrix or to solve a system of linear equations. A tolerance has always been used with the Linpack routines but not with the Lapack routines in versions 1.7.x and 1.8.0. (You can use the optional argument tol = 0 to override this check for computational

Hi Everyone, I have some data that predicts both a nominal and ordinal response variable. I was wondering what packages in R would help me analyze the data? I was also curious if anyone could recomend me some textbooks that would help with the analysis of such data? I have the 5th edition of "Applied Multivariate Statistical Analysis" by Richard A. Johnson and Dean W. Wichern

Hi! I'm doing one and two sample nonparametric tests for the median using wilcox test. For a one-sample test I use: > wilcox.test(x, mu =50 (or whatever), y=NULL,correct=TRUE) For two-sample test I use: > wilcox.test(x,y,correct=TRUE) The problem is when I try to duplicate problems from textbooks, I get p-values that are much different from the examples from the literature. They are