Hi, Many thanks for your helpful comments and suggestions. The attached are the data in both log10 scale and original scale. It would be very grateful if you could suggest which version of test should be used. By the way, how to check whether the variation is additive (natural scale) or multiplicative (log scale) in R? How to check whether the distribution of the data is normal? PS, Can I confirm that do your suggestions mean that in order to check whether there is a difference between x and y in terms of mean I need check the distribution of x and that of y in both natual and log scales and to see which present normal distribution? and then perform a t test using the data scale which presents normal distribution? If both scales present normal distribution, then the t tests with both scales should give the similar results? Thanks again. Liu
Andrew Robinson <[EMAIL PROTECTED]> wrote: Hi Dimitris, you are describing a more stringent requirement than the t-test actually requires. It's the sampling distribution of the mean that should be normal, and this condition is addressed by the Central Limit Theorem. Whether or not the CLT can be invoked depends on numerous factors, including the distribution of the sample, and the size of the sample, neither of which we have any information about. Liu, the problem you describe is associated with the application of the test rather than the test itself. The difference between log- and natural- scaled data can often profitably be thought about by asking whether you would naturally assume that the variation is additive (natural scale) or multiplicative (log scale). Given the information that you've presented there's no way we can tell which version of the test is more reliable. I hope that this helps. Andrew On Wed, Sep 22, 2004 at 10:00:16AM +0200, Dimitris Rizopoulos wrote: > Hi Liu, > > before applying a t-test (or any test) you should first check if the > assumptions of the test are supported by your data, i.e., in a t-test > x and y must be normally distributed. > > I hope it helps. > > Best, > Dimitris > > ---- > Dimitris Rizopoulos > Ph.D. Student > Biostatistical Centre > School of Public Health > Catholic University of Leuven > > Address: Kapucijnenvoer 35, Leuven, Belgium > Tel: +32/16/396887 > Fax: +32/16/337015 > Web: http://www.med.kuleuven.ac.be/biostat/ > http://www.student.kuleuven.ac.be/~m0390867/dimitris.htm > > > ----- Original Message ----- > From: "kan Liu" > To: > Sent: Wednesday, September 22, 2004 9:52 AM > Subject: [R] t test problem? > > > >Hello, > > > >I got two sets of data > >x=(124738, 128233, 85901, 33806, ...) > >y=(25292, 21877, 45498, 63973, ....) > >When I did a t test, I got two tail p-value = 0.117, which is not > >significantly different. > > > >If I changed x, y to log scale, and re-do the t test, I got two tail > >p-value = 0.042, which is significantly different. > > > >Now I got confused which one is correct. Any help would be very > >appreciated. > > > >Thanks, > >Liu > > > >__________________________________________________ > > > > > > > >[[alternative HTML version deleted]] > > > >______________________________________________ > >[EMAIL PROTECTED] mailing list > >https://stat.ethz.ch/mailman/listinfo/r-help > >PLEASE do read the posting guide! > >http://www.R-project.org/posting-guide.html > > > > ______________________________________________ > [EMAIL PROTECTED] mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide! > http://www.R-project.org/posting-guide.html -- Andrew Robinson Ph: 208 885 7115 Department of Forest Resources Fa: 208 885 6226 University of Idaho E : [EMAIL PROTECTED] PO Box 441133 W : http://www.uidaho.edu/~andrewr Moscow ID 83843 Or: http://www.biometrics.uidaho.edu No statement above necessarily represents my employer's opinion. ---------------------------------
x y 37154 32211 114815 124738 100000 128233 100000 96383 100000 85901 371535 338065 100000 151008 56234 48978 34674 62087 758578 542001 14125 25645 26915 31696 100000 119950 72444 56105 63096 39084 100000 131522 33113 68077 37154 30409 26915 31842 70795 24322 93325 74989 100000 101859 43652 50119 120226 86497 100000 159956 100000 44668 100000 52602 100000 82794 57544 24774 30200 19055 100000 56624 100000 39719 53703 51286 70795 17258 66069 52000 87096 140605 58884 36141 63096 74645 44668 32359 100000 84140 15136 26915 43652 35075 794328 901571 20417 16218 147911 115345 57544 87498 100000 73621 14454 19953 100000 59429 72444 37670 199526 210378 38905 41020 79433 111944 100000 141254 100000 92045 23442 22751 18197 20606 316228 345144 83176 154170 48978 33806 100000 84723 100000 158855 20893 13552 141254 127350 67608 24774 10965 9290 17378 17742 120226 105925 23442 16943 56234 53211 66069 36392 38019 49774 75858 84140 42658 50466 56234 49204 12303 12474 120226 110154 131826 208449 104713 11508 70795 106905 218776 288403 91201 153109 338844 294442 177828 102329 501187 314051 85114 125026 851138 274789 25704 44875 38019 45709 281838 399025 28840 51050 151356 72444 218776 153815 213796 128825 194984 135831 288403 218776 380189 420727 114815 23281 75858 107895
x y 4.57 4.508 5.06 5.096 5 5.108 5 4.984 5 4.934 5.57 5.529 5 5.179 4.75 4.69 4.54 4.793 5.88 5.734 4.15 4.409 4.43 4.501 5 5.079 4.86 4.749 4.8 4.592 5 5.119 4.52 4.833 4.57 4.483 4.43 4.503 4.85 4.386 4.97 4.875 5 5.008 4.64 4.7 5.08 4.937 5 5.204 5 4.65 5 4.721 5 4.918 4.76 4.394 4.48 4.28 5 4.753 5 4.599 4.73 4.71 4.85 4.237 4.82 4.716 4.94 5.148 4.77 4.558 4.8 4.873 4.65 4.51 5 4.925 4.18 4.43 4.64 4.545 5.9 5.955 4.31 4.21 5.17 5.062 4.76 4.942 5 4.867 4.16 4.3 5 4.774 4.86 4.576 5.3 5.323 4.59 4.613 4.9 5.049 5 5.15 5 4.964 4.37 4.357 4.26 4.314 5.5 5.538 4.92 5.188 4.69 4.529 5 4.928 5 5.201 4.32 4.132 5.15 5.105 4.83 4.394 4.04 3.968 4.24 4.249 5.08 5.025 4.37 4.229 4.75 4.726 4.82 4.561 4.58 4.697 4.88 4.925 4.63 4.703 4.75 4.692 4.09 4.096 5.08 5.042 5.12 5.319 5.02 4.061 4.85 5.029 5.34 5.46 4.96 5.185 5.53 5.469 5.25 5.01 5.7 5.497 4.93 5.097 5.93 5.439 4.41 4.652 4.58 4.66 5.45 5.601 4.46 4.708 5.18 4.86 5.34 5.187 5.33 5.11 5.29 5.133 5.46 5.34 5.58 5.624 5.06 4.367 4.88 5.033
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