similar to: how to find critical values of t in R

Is this how a t hypothesis test is done when I don't have the actual data, but just the summarized statistics: > #Homework 9.2.6 [1] > n<-31 > xbar<-3.10 > s_x<-1.469 > m<-57 > ybar<-2.43 > s_y<-1.35 > s_pooled<- (((n-1)*s_x^2) + ((m-1)*s_y^2)) / (n + m - 2) > s_pooled [1] 1.939521 > t_obs <- (xbar - ybar) / (s_pooled * (sqrt(1/n + 1/m)))

Hi, Does anyone know how one could format numbers using 1000 separator in R? For example, format 1000 as 1,000 and 100000 as 100,000, etc. Thanks, -- Tom [[alternative HTML version deleted]]

I'm trying to replicate some of the examples from my textbook in R (my text uses Minitab). In this problem, I'm trying to construct a 95% confidence interval for these distance measurements [1]: > # Case Study 7.4.1, p. 483 > x <- scan() 1: 62 52 68 23 34 45 27 42 83 56 40 12: Read 11 items > alpha<-.95 > mean(x) + qt(c((1-alpha)/2, 1-((1-alpha)/2)), df=length(x)-1) *

Hi, I just started with R and I found that there are many options to rearrange the data to do mixed models. I want to use the reshape function. I have 2 between subject variables and one within. I was able to change the data structure but still - the result of the aov functions are calculating everything as a within subject. the table looks like this: SerialNo breed treatment distance_1

Hello! I am using R 2.5.1 on a Apple Power Book G4 with Mac OS X 10.4.10 and I am still R beginner. I try to calculate a t.test() using this code: TTest75<-t.test(Fem75, Mal75, alternative= "two.sided", paired= TRUE) This works properly, but I have two variables with a lot of missing data and therefore get the error message: TTest66<-t.test(Fem66, Mal66, alternative=

I was experimenting yesterday with a binomial make.link option for estimating student t binary response models, tentatively called gossit, and I noticed eventually that the R qt function doesn't like df < 1. Vaguely recalling that Splus didn't seem to mind such weirdness, I checked on our soon to be defunct Splus6.2 and sure enough, it produced plausible answers instead of R's

Hi, how can I extract the t-values after running a pairwise.t.test? The output just list the p-values. Many thanks for your help. Cheers Guido ____________________________________ Guido J. Parra School of Tropical Environment Studies and Geography James Cook University Townsville Queensland 4811 Phone: 61 7 47815824 Fax: 61 7 47814020 Mobile: 0437630843 e-mail:

Hi, Does anyone know if the RMSE is one of the values provided by the lm model, or do we have to calculate it by hand from the residuals? Thanks, -- Tom [[alternative HTML version deleted]]

What would be the R formulae for a two-sided test? I have a formula for a one-sided test: powertest <- function(a,m0,m1,n,s){ t1 = -qnorm(1-a) num = abs(m0-m1) * sqrt(n) t2 = num/s pow = pnorm(t1 + t2) } Would you pls let me know if you know of? Thank you, ej

Dear list members I have a doubt on how p-values for t-statistics are calculated in the summary of Linear Models. Here goes an example: x <- rnorm(100,50,10) y <- rnorm(100,0,5) fit1<-lm(y~x) summary(fit1) summary(fit1)$coef[2] # b summary(fit1)$coef[4] # Std. Error summary(fit1)$coef[6] # t-statistic summary(fit1)$coef[8] # Pr(>|t| summary(fit1)$df [2] # degrees of freedom #

Dear R-User, I'm trying to visualize the results of the power calculation with the function power.t.test(). Therefore I want to plot the related t-distributions and shade the surfaces indicatingt the type I error, the type II error and the power. For sample sizes greater 30 I got results which are very satisfying. For small sample sizes I got stuck and did'nt find a mistake. To

Dear R list, I would like to illustrate the origin of the Student t distribution using R. So, if (sample.mean - pop.mean) / standard.error(sample.mean) has t distribution with (sample.size - 1) degree free, what is wrong with the simulation below? I think that the theoretical curve should agree with the relative frequencies of the t values calculated: #== begin options===== # parameters

Dear R-community My ODE problems looks as follows: (1) dA/dt = u*A - v*B (2) dB/dt = v*B - u*A where u is a constant, and v=k*t (k=constant, t=time) Does anybody knows a good function/procedure of solving? Should one involve the equation (3) dv/dt = k? Thanks for your support. -- Dominik Heinzmann Master of Science in Mathematics, EPFL Ph.D. student in Biostatistics Institute of Mathematics

When I do t.test on two distributions (see example below), it outputs numerous data about the t.test. What I'd like to do is individually capture some of this data and assign it to other variables. However, I am unable to find anything in the help section. In the example below, the t value is -4.0441 and the p-value is 0.006771 How can I assign these values to two variables, let's

Hi, I have two sets of data that I would like to put into a data frame. But since they have different length, I am not sure how to do this. Here is an example of my data: data set one: date growth 1/1/2007 10 1/2/2007 10.2 1/3/2007 10.4 1/4/2007 10.6 data set two: date growth 1/1/2007 22 1/2/2007 22.5 1/4/2007 22.4 I would like to combine the two data sets and

Hi, I've attached two files with the sources for a function to implement the finite difference method for solving a particular differential equation. One of them works correctly, the other gives wrong results or returns an error, depending on the version of R. The difference between them is that in the 'broken' version in line 42 I check if the items in the two-dimensional array

Hello, every one, Using the qt() function in R, I got a different Student t-value with the Student t table. e.g. the return value of function qt(0.95,9) is 1.833, while in table it is 2.262. I do not know why the difference exists. I guess it may be a bug in R. -- Íõ»¯Èå ²©Ê¿Ñо¿Éú ±±¾©Ê¦·¶´óѧ¾°¹ÛÉú̬Óë¿É³ÖÐøÐÔ¿ÆѧÑо¿ÖÐÐÄ ±±¾©Êк£µíÇøнֿÚÍâ´ó½Ö19ºÅ±±¾©Ê¦·¶´óѧÉúÃü¿ÆѧѧԺ 100875 Huaru

Is there any automatic mechanism for extracting a likelihood or test statistic distribution (PDF or CDF) from an object of class "htest" or from another object of a general class encoding a hypothesis test result? I would like to have a function that takes "x", an object of class "htest", as its only argument and that returns the likelihood or test statistic

Hi I had observed the following problem in R (also C, Matlab, and Python). sprintf('%1.2g\n', 3.15) give 3.1 instead of 3.2 whereas an input of 3.75 gives 3.8. Java's System.out.printf is ok though. > round(3.75,1) [1] 3.8 > round(3.15,1) [1] 3.1 Similar outcome with sprintf in R. However, the right answer should be 3.2 Regards Teckpor [[alternative HTML version

Number of subjects = 25 Mean of Sample = 77 Standard Deviation (s) = 12 sem = 2.4 df = 24 The claim is that population mean is less than 80 * > 80 So our H0 (null hupotheis) is * > 80 > qt(.95,24) [1] 1.710882 > qt(0.05, 24) [1] -1.710882 tstat = -1.25 on t24 falls between 1.711 (.95,24) and *1.711 (.005,24) How Could I sketch t curve for the above data where my * would be at the