Hi Thomas, I'm not an expert - so I might use incorrect terminology, but hopefully you'll get the picture!
Assuming that you've got your data in a .CSV file, you'd first read in your data, where the first three lines might look like... x,y 0,2.205954909440447 1,8.150580118785099 # load the info into a data.frame called mydata mydata <- read.csv("mycsvfile.csv",header=TRUE) # now "attach" to this data.frame, so that the internal attach(mydata) # now do the regression and store it in the object "myregr" myregr <- lm(y~x) # print out the info from myregr myregr # to get more info from myregr use the summary() method... summary(myregr) There is an enormous quantity of documentation available, though it takes a little while to learn to use it properly and get the full effectiveness from it... I strongly recommend that you read the "Posting Guide" http://www.R-project.org/posting-guide.html which will help you. For more information, have a look at the introduction to R; which is a tad terse in places - so read it slowly :-) Have a look also at the other documentation http://www.r-project.org/other-docs.html In particular I'd recommend John Maindonalds online book at http://cran.r-project.org/other-docs.html cheers! Sean On 28/08/05, Thomas Baruchel <[EMAIL PROTECTED]> wrote: > On Sun, Aug 28, 2005 at 09:48:15AM +0200, Thomas Baruchel wrote: > > Is R the right choice ? Please, could you step by step show me > > how you would do on this example (data below) in order to let me > > I forgot my data :-( > > 0 2.205954909440447 > 1 8.150580118785099 > 2 15.851323727378597 > 3 22.442795956953574 > 4 29.358579800271354 > 5 36.46060528847214 > 6 43.7516923268591 > 7 51.223688311610026 > 8 58.86610205087116 > 9 66.66821956399055 > 10 74.61990268453171 > 11 82.71184423952718 > 12 90.93560520053082 > 13 99.28356700194489 > 14 107.74885489906521 > 15 116.3252559311549 > 16 125.00714110112291 > 17 133.78939523822717 > 18 142.6673553086964 > 19 151.63675679510055 > 20 160.69368733376777 > 21 169.834546691509 > 22 179.05601219606618 > 23 188.35500882314003 > 24 197.72868324657364 > 25 207.17438125936408 > 26 216.68962806440814 > 27 226.2721110130965 > 28 235.9196644372003 > 29 245.63025627606442 > 30 255.40197624835042 > 31 265.23302535689197 > 32 275.12170654792556 > 33 285.06641637317705 > 34 295.0656375259694 > 35 305.1179321414606 > 36 315.2219357669857 > 37 325.3763519217964 > 38 335.5799471767038 > 39 345.8315466936063 > 40 356.13003017290697 > 41 366.4743281636434 > 42 376.8634186969678 > 43 387.2963242085816 > 44 397.77210871999046 > 45 408.2898752521091 > 46 418.8487634479048 > 47 429.44794738349896 > 48 440.08663354951693 > 49 450.76405898653184 > 50 461.479489560246 > 51 472.2322183636179 > 52 483.02156423451737 > 53 493.84687037869463 > 54 504.707503088911 > 55 515.6028505520102 > 56 526.5323217365377 > 57 537.4953453542455 > 58 548.4913688894654 > 59 559.5198576909147 > 60 570.5802941210067 > 61 581.6721767581994 > 62 592.7950196483222 > 63 603.9483516011882 > 64 615.1317155291274 > 65 626.3446678243708 > 66 637.5867777724806 > 67 648.8576269992603 > 68 660.1568089487967 > 69 671.4839283904737 > 70 682.838600952985 > 71 694.2204526835204 > 72 705.6291196304554 > 73 717.0642474479981 > 74 728.5254910213728 > 75 740.0125141112243 > 76 751.5249890160294 > 77 763.062596251391 > 78 774.6250242451752 > 79 786.2119690475241 > 80 797.8231340548524 > 81 809.4582297469931 > 82 821.1169734367211 > 83 832.7990890309349 > 84 844.5043068028273 > 85 856.2323631744205 > > Regards, > > -- > Thomas Baruchel > > ______________________________________________ > R-help@stat.math.ethz.ch mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html > ______________________________________________ R-help@stat.math.ethz.ch mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html