search for: quartiles

Why am I getting a wrong result for quartiles? here is my code: > cbiomass = c(910, 1058, 929, 1103, 1056, 1022, 1255, 1121, 1111, 1192, > 1074, 1415) > summary(cbiomass) > IQR(cbiomass) The result R gives me is: For the summary > Min. 1st Qu. Median Mean 3rd Qu. Max. 910 1048 1088 1104 1139 1415...

Greetings R users, My goal is to generate quartile groups of each variable in my data set. I would like each experiment to have its designated group added as a subsequent column. I can accomplish this individually with the following code: brks <- with(data_variables, cut2(var2, g=4)) #I don't want the actual numbers, I need a numbered group data$test1=factor(brks,

I am using the describe function in prettyR. I would like to add the 25% 75% quartiles to the summary table how do I do this I have tried describe(x.f, num.desc=c("mean", "median", "sd", "min", "max", "skewness", "quantile(x.f, na.rm=T, probs=seq(0.25, 0.75))", "valid.n")) help -- Let's not spen...

Hi I need some help getting results from multiple linear models into a dataframe. Let me explain the problem. I have a dataframe with ejection fraction results measured over a number of quartiles and grouped by base_study. My dataframe (800 different base_studies) looks like > afvtprelvefs basestudy quartile ef ef_std entropy CBP0908020 1 21.6 0.53 3.27 CBP0908020 2 32.5 0.61 3.27 CBP0908020 3 30.8 0.63 3.27 C...

I have data that looks like lake,loglength,logweight 1,2.369215857,1.929418926 1,2.426511261,2.230448921 1,2.434568904,2.298853076 1,2.437750563,2.298853076 1,2.442479769,2.230448921 1,2.445604203,2.356025857 ... 102,2.722633923,3.310268367 102,2.781755375,3.502153893 102,2.836324116,3.683407299 102,2.802773725,3.583312152 102,2.790285164,3.546419267 102,2.806179974,3.599118565

Hi, I'm trying to create a qqplot with reference to a Weibull distribution including a reference line. This is my current code: lights.data <- scan("lights.dat") #Generate Weibull quantiles prob.grid <- ppoints(length(lights.data)) prob.quant <- qweibull(prob.grid , 1.5,4) #Draw QQ plot qqplot(prob.quant,lights.data) #add red reference line qqline(lights.data,col = 2)

Hello, I'm currently using a simple plot to visualize some mean values. I'm having ~200 datapoints on the x-axis, each has 10 records. I'm currently plotting only the mean value of each of the datapoints. What I need is a way to visualize the quartiles/error/whatever of these points. I thought about boxplots, but I have to many points on the xaxis - it would be impossible to see anything. I though that it would be nice to have a "hull" around each line, indicate the width of the quartiles, visualized by a different background. It's...

For boxplot(), is it possible to pass in a parameter to change the default way that the 1st and 3rd quartiles are computed? (specifically, I'd like to use type 6 described in the quantile function). Also, what are the options for how outliers are computed, and how can one change them? Thank you [[alternative HTML version deleted]]

When data contains both factor and numeric variables, how to get quartiles for all numeric variables? n <- 100 x1 <- runif(n) x2 <- runif(n) x3 <- x1 + x2 + runif(n)/10 x4 <- x1 + x2 + x3 + runif(n)/10 x5 <- factor(sample(c('a','b','c'),n,replace=TRUE)) x6 <- factor(1*(x5=='a' | x5=='c')) data1 <- cbind...

I've just started using R and am still a neophyte, but I found the following curious result. I'm using the current version of R (2.5.1 (2007-06-27) ). Why are the results for the third quartile different in the output from the summary and fivenum commands? For the following data set 457 514 530 530 538 560 687 745 745 778 786 790 792

Hi,everyone i need to calculate quartile values of a variable grouped by the other variable . same as in aggregate function(only median,mean or functions is possible-i think so) Could you please help me to achieve the same for other quartile values(5,10,25,75,90) as for median using aggregate. Thanks in advance. data : zip price 60000 567000 60001 478654 60004 485647 60001

Hi, all. I have a list: process <- c( 5 , 7 , 4 , 1 , 4 , 1) and I'd like to get each half (or each third or each quartile) of the list: process.firsthalf would be (5, 7, 4) and process.secondhalf would be (1, 4, 1). note that I'm not interested in the numeric quartiles (then I could use quantile or several other functions). what is the best way to get this kind of thing? for odd legnth lists, I don't particularly care if the first or the second half gets the extra. can write a function that does this for halfs, but I'm looking for a slightly more gene...

Hi, I have a simple question about quartiles in R, especially how they are calculated using the boxplot. Quartiles (.25 and .75) in boxplot are different from the summary function and also don't match with the 9 types in the quantile function. See attachment for details. Can you give me the details on how the boxplot function does calcu...

I think qqline does not do exactly what it is advertised to do ("`qqline' adds a line to a normal quantile-quantile plot which passes through the first and third quartiles."). Consider the graph: tmp <- qnorm(ppoints(10)) qqnorm(tmp) qqline(tmp) The line (which I expected go through all the points), has a slightly shallower slope than does the points plotted by qqnorm. I think the problem is that qqline bases its line on the relationship between the quart...

Hi every one, I am trying to generate a normally distributed random variable with the following descriptive statistics, min=1, max=99, variance=125, mean=38.32, 1st quartile=38, median=40, 3rd quartile=40, skewness=-0.274. I know the "rnorm" will allow me to simulate random numbers with mean 38.32 and Sd=11.18(sqrt(125)). But I need to have the above mentioned descriptive

Hi! My name is Martin and I have a problem concerning the boxplot function in R. I want my boxes to be limited by the 1st and 3rd quartile and NOT the 'hinges' values that are the default setting in R. Do anyone knows if there is any command that I could do to change this default setting? Sincerely Martin Olofsson

Hello, I have a doubt, but it is more statistic than just about R: How the people deal usually with negative percentile and quartile? In my concrete case, I want to know the distribution of an error, so the nearest it is to 0 the better (I think it would be optimun to have the nearest values to 0 in the lower percentiles). The best result would be making the percentile of the absolute value

...you to answer, Hemant. Read the ?quartile help page if your answer is "yes" or even "maybe". > > Or maybe you could normalise your values and use quartile method. Well, maybe not so much on that last one, Petr. Normalization should not affect the classification based on quartiles. It doesn't change the ordering of variables. -- David. > > Cheers > Petr > > From: Hemant Sain [mailto:hemantsain55 at gmail.com] > Sent: Friday, October 13, 2017 8:51 AM > To: PIKAL Petr <petr.pikal at precheza.cz> > Cc: r-help mailing list <r-help at r-p...

I'm trying to devide x into tertiles, but ends up with integer limits even x holds one decimal. The analysis is extremely sensitive to the limits and I like to keep them right. How can that be done? quartiles <- quantcut( x[x >= 0], q=seq(0,1, by=(1/3)) > table(quartiles) quartiles [180,344] (344,448] (448,644] 16467 16476 16452 [[alternative HTML version deleted]]

Hi all, I''ve got a simple contingency table produced with table(), and the upper and lower quartiles (quantile25 and quantile75) for the same dataset. Is there a function that tells me in which category does the value of the quartile falls into? for example: tabsp <- table(fam$I[fam$I>0]) 1 3 6 6 1 1 and for the cumulative frequency distribution tabcum <- cumsum(tabsp) 1 3 6 6 7 8...