search for: faiz7r

Hi all, I want to make a contingency table in R. I want to tabulate two variables, one as the independent and second as the dependent variable. The IV has two categories, namely, birth complications, and no birth complications. The frequency of birth complication category is fifty, and the frequency of no birth complication category is 34. The categories and frequencies of DV follows.

...om/questions/5963269/how-to-make-a-great-r-reproducible-example [2] http://adv-r.had.co.nz/Reproducibility.html [3] https://cran.r-project.org/web/packages/reprex/index.html (read the vignette) -- Sent from my phone. Please excuse my brevity. On February 22, 2018 8:09:49 PM PST, faiz rasool <faiz7r at gmail.com> wrote: >Dear list members, > >I want to save residuals above or less than a certain value to an R >object. I have performed a multiple linear regression, and now I want >to find out which cases have a residual of above + 2.5 and ? 2.5. > >Below I provide the R...

Dear list members, I want to save residuals above or less than a certain value to an R object. I have performed a multiple linear regression, and now I want to find out which cases have a residual of above + 2.5 and ? 2.5. Below I provide the R commands I have used. Reg<-lm(a~b+c+d+e+f) # perform multiple regression with a as the dependent variable. Residuals<-residuals(reg) # store

I am trying to perform goodness of fit test using R. I am using this website http://wiener.math.csi.cuny.edu/Statistics/R/simpleR/stat013.html for help. However, I am unable to carry out the test successfully. My code follows. It is taken from the website just mentioned. freq=c(22,21,22,27,22,36) # frequencies obtained after rolling the dice 150 times. prob=c(1,1,1,1,1,1)/6 # specify expected

Dear list, I am slightly confused about how I can do the following in R. I want to perform robust multiple regression. I?ve used the Boot function in CAR package to find confidence intervals and standard errors. Inadition to these, I want to find the robust estimates for the F test and r-square. Finally, I would like to know the significance levels of bootstrap results. Below I explain

Dear list, I have the following how-to-do it in R, questions. Suppose I have ten independent variables, and one dependent variable. I want to find the Pearson correlation of all the IVs with the DV, but not the correlation between the IVs. What I know so far, about R, that I have to type the cor () function ten times, each time requesting for a correlation between one IV and the DV. I was

Hi all, I would like to read the results of the commands type in the terminal window in Microsoft Word. As a blind user my options are somewhat limited and are time consuming if I want to see the results of the commands that I have type earlier. for example if my first two commands were x<-c(1,2,3,4,5) mean(x) and I have typed ten more commands after the first two commands it is not easy

Hi For first question, maybe I am completely wrong but cor(swiss[,-1], swiss[,1]) should give you what you want in one step. Second question Without an example it is hard to say but maybe aggregate is the way forward. > aggregate(iris[,1:4], list(iris$Species), function (x) c(mean=mean(x), sd=sd(x))) Group.1 Sepal.Length.mean Sepal.Length.sd Sepal.Width.mean Sepal.Width.sd 1

Dear list members, I'd like to find the value of r-square change at each step of a regression model. I know that I can use anova () to compare to models, but, if I want to find out that how much exactly r-square has change from one model to the next, how can I find that? Regards, and thanks for any help. Faiz