On 09/15/2014 10:57 AM, eliza botto wrote:
Dear useRs of R,
I have two datasets (TT and SS) and i wanted to to see if my data is uniformly
distributed or not?I tested it through chi-square test and results are given at the end
of it.Now apparently P-value has a significant importance but I cant interpret the
results and why it says that "In chisq.test(TT) : Chi-squared approximation may be
incorrect"
###############################################################
dput(TT)
structure(list(clc5 = c(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.26, 0.14, 0, 0.44,
0.26, 0, 0, 0, 0, 0, 0, 0.11, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.17, 0.16,
0.56, 0, 1.49, 0, 0.64, 0.79, 0.66, 0, 0, 0.17, 0, 0, 0, 0, 0.56, 0, 0, 0, 0,
0, 0, 0, 0, 0, 0, 0, 0.43, 0.41, 0, 0.5, 0.44, 0, 0, 0, 0, 0.09, 0.46, 0, 0.27,
0.45, 0.15, 0.31, 0.16, 0.44, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.07, 0, 0, 0, 0,
0, 0.06, 0, 0.09, 0.07, 0, 0, 7.89, 0, 0.22, 0.29, 0.33, 0.27, 0, 0.36, 0.41,
0, 0, 0, 0, 0.55, 0.81, 0, 0.09, 0.13, 0.28, 0, 0, 0), quota_massima = c(1167L,
1167L, 4572L, 3179L, 3141L, 585L, 585L, 876L, 876L, 1678L, 2667L, 1369L, 1369L,
1369L, 1381L, 1381L, 1381L, 1381L, 2284L, 410L, 2109L, 2507L, 2579L, 2507L,
1436L, 3234L, 3234L, 3234L, 3234L, 2792L, 2569L, 2569L, 2569L, 1669L, 4743L,
4743L, 4743L, 3403L, 3197L, 3267L, 3583L, 3583L, 3583L, 2584L, 2584L, 2579L,
1241L, 1241L, 4174L, 3006L, 3197L, 2366L, 2618L, 2670L, 4487L, 3196L, 3196L,
2107L, 2107L, 2427L, 1814L, 2622L, 1268L, 1268L, 1268!
L,!
3885L, 3885L, 3092L, 3234L, 2625L, 2625L, 3760L, 4743L, 3707L, 3760L, 4743L, 3760L, 3885L, 3760L, 4743L,
2951L, 782L, 2957L, 3343L, 2697L, 2697L, 3915L, 2277L, 1678L, 1678L, 3197L, 2957L, 2957L, 2957L, 4530L,
4530L, 4530L, 2131L, 3618L, 3618L, 3335L, 2512L, 2390L, 1616L, 3526L, 3197L, 3197L, 2625L, 2622L, 3197L,
3197L, 2622L, 2622L, 2622L, 368L, 4572L, 3953L, 863L, 3716L, 3716L, 3716L, 2697L, 2697L, 1358L)), .Names =
c("clc5", "quota_massima"), class = "data.frame", row.names = c(NA, -124L))
chisq.test(TT)
Pearson's Chi-squared test
data: TT
X-squared = 411.5517, df = 123, p-value < 2.2e-16
Warning message:
In chisq.test(TT) : Chi-squared approximation may be incorrect
#######################################################################
dput(SS)
structure(list(NDVIanno = c(0.57, 0.536, 0.082, 0.262, 0.209, 0.539, 0.536,
0.543, 0.588, 0.599, 0.397, 0.63, 0.616, 0.644, 0.579, 0.597, 0.617, 0.622,
0.548, 0.528, 0.541, 0.436, 0.509, 0.467, 0.534, 0.412, 0.324, 0.299, 0.41,
0.462, 0.427, 0.456, 0.508, 0.581, 0.242, 0.291, 0.324, 0.28, 0.291, 0.305,
0.365, 0.338, 0.399, 0.516, 0.357, 0.558, 0.605, 0.638, 0.191, 0.377, 0.325,
0.574, 0.458, 0.426, 0.188, 0.412, 0.464, 0.568, 0.582, 0.494, 0.598, 0.451,
0.577, 0.572, 0.602, 0.321, 0.38, 0.413, 0.427, 0.55, 0.437, 0.481, 0.425,
0.234, 0.466, 0.464, 0.491, 0.463, 0.489, 0.435, 0.267, 0.564, 0.256, 0.156,
0.476, 0.498, 0.122, 0.508, 0.582, 0.615, 0.409, 0.356, 0.284, 0.285, 0.444,
0.303, 0.478, 0.557, 0.345, 0.408, 0.347, 0.498, 0.534, 0.576, 0.361, 0.495,
0.502, 0.553, 0.519, 0.504, 0.53, 0.547, 0.559, 0.505, 0.557, 0.377, 0.36,
0.613, 0.452, 0.397, 0.277, 0.42, 0.443, 0.62), delta_z = c(211L, 171L, 925L,
534L, 498L, 50L, 53L, 331L, 135L, 456L, 850L, 288L, 286L, 233L, 342L, !
27!
4L, 184L, 198L, 312L, 67L, 476L, 676L, 349L, 873L, 65L, 963L, 553L, 474L, 948L, 1082L, 616L, 704L, 814L,
450L, 865L, 987L, 1265L, 720L, 565L, 652L, 941L, 822L, 1239L, 929L, 477L, 361L, 199L, 203L, 642L, 788L, 818L,
450L, 703L, 760L, 711L, 1015L, 1351L, 195L, 511L, 617L, 296L, 604L, 381L, 389L, 287L, 1043L, 1465L, 963L,
1125L, 582L, 662L, 1424L, 1762L, 575L, 1477L, 1364L, 1236L, 1483L, 1201L, 1644L, 498L, 142L, 510L, 482L,
811L, 788L, 466L, 626L, 461L, 350L, 1177L, 826L, 575L, 568L, 916L, 767L, 1017L, 532L, 1047L, 1370L, 902L,
686L, 703L, 440L, 1016L, 1148L, 1089L, 753L, 650L, 1065L, 568L, 712L, 762L, 636L, 79L, 1092L, 955L, 158L,
1524L, 1145L, 673L, 513L, 596L, 239L)), .Names = c("NDVIanno", "delta_z"), class =
"data.frame", row.names = c(NA, -124L))
chisq.test(SS)
Pearson's Chi-squared test
data: SS
X-squared = 72.8115, df = 123, p-value = 0.9999
Warning message:
In chisq.test(SS) : Chi-squared approximation may be incorrect
#####################################################################################
Kindly guide me through like you always did :)
thanks in advance,
Eliza
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______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
You are using a Chi-squared test on a 124x2 matrix of values (not all
integers) and many are zeros. The expected frequencies for many cells
are very small (near zero, less than 1) hence the warning message. More
importantly, does this application of the Chi-squared test make sense?
What am I missing?
Rick
--
Richard A. Bilonick, PhD
Assistant Professor
Dept. of Ophthalmology, School of Medicine
Dept. of Biostatistics, Graduate School of Public Health
Dept. of Orthodontics, School of Dental Medicine
University of Pittsburgh
Principal Investigator for the Pittsburgh Aerosol Research
and Inhalation Epidemiology Study (PARIES)
412 647 5756
______________________________________________
R-help@r-project.org mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
