Testing of Two Samples
VARIOUS methods, parametric and non-parametric, are used for examining the significance of the difference between two given samples. The most common of these is the parametric one, the t -test 1 , which is based on the assumption that the samples are drawn from a normal population. There is Pitman&#...
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| Veröffentlicht in: | Nature (London) 1953-09, Vol.172 (4377), p.553-553 |
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| container_title | Nature (London) |
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| creator | KRISHNA IYER, P. V |
| description | VARIOUS methods, parametric and non-parametric, are used for examining the significance of the difference between two given samples. The most common of these is the parametric one, the
t
-test
1
, which is based on the assumption that the samples are drawn from a normal population. There is Pitman's
2
w
-test which has been built up by considering all the possible samples that can be drawn by pooling together the two samples. Besides these, Wald and Wolfowitz
3
have used the run theory for deciding the significance of the difference between two samples. This method has been extended for
k
samples by myself
4
. Recently, tests have been constructed by Wallis
5
, Kruskall
6
and Rijkoort
7
by using rank numbers for each of the samples. |
| doi_str_mv | 10.1038/172553a0 |
| format | Article |
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t
-test
1
, which is based on the assumption that the samples are drawn from a normal population. There is Pitman's
2
w
-test which has been built up by considering all the possible samples that can be drawn by pooling together the two samples. Besides these, Wald and Wolfowitz
3
have used the run theory for deciding the significance of the difference between two samples. This method has been extended for
k
samples by myself
4
. Recently, tests have been constructed by Wallis
5
, Kruskall
6
and Rijkoort
7
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t
-test
1
, which is based on the assumption that the samples are drawn from a normal population. There is Pitman's
2
w
-test which has been built up by considering all the possible samples that can be drawn by pooling together the two samples. Besides these, Wald and Wolfowitz
3
have used the run theory for deciding the significance of the difference between two samples. This method has been extended for
k
samples by myself
4
. Recently, tests have been constructed by Wallis
5
, Kruskall
6
and Rijkoort
7
by using rank numbers for each of the samples.</description><subject>Humanities and Social Sciences</subject><subject>letter</subject><subject>multidisciplinary</subject><subject>Science</subject><subject>Science (multidisciplinary)</subject><issn>0028-0836</issn><issn>1476-4687</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1953</creationdate><recordtype>article</recordtype><recordid>eNptz0tLAzEUBeAgCo5VcOVSZqmL0XuTm8cspfiCggvHdUgzSWlpZ0rSIv57R8bixtXZfBzOYewS4Q5BmHvUXErh4IgVSFpVpIw-ZgUANxUYoU7ZWc4rAJCoqWBXTci7Zbco-1g2n3357jbbdcjn7CS6dQ4XvzlhH0-PzfSlmr09v04fZpXHmqBCkiKCJiW0j6YNkbfOtyA5YdRDmihQchNwLsnUykvwSEKDDJwTr-diwm7GXp_6nFOIdpuWG5e-LIL9-WMPfwZ6O9I8kG4Rkl31-9QN6_6z16Pt3G6fwl_pAXwDnhRQxA</recordid><startdate>19530919</startdate><enddate>19530919</enddate><creator>KRISHNA IYER, P. V</creator><general>Nature Publishing Group UK</general><scope>AAYXX</scope><scope>CITATION</scope></search><sort><creationdate>19530919</creationdate><title>Testing of Two Samples</title><author>KRISHNA IYER, P. V</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c1940-1453f074637cf8def2dacd05241f7d058f31528e1b54896c50c143705e22429b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1953</creationdate><topic>Humanities and Social Sciences</topic><topic>letter</topic><topic>multidisciplinary</topic><topic>Science</topic><topic>Science (multidisciplinary)</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>KRISHNA IYER, P. V</creatorcontrib><collection>CrossRef</collection><jtitle>Nature (London)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>KRISHNA IYER, P. V</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Testing of Two Samples</atitle><jtitle>Nature (London)</jtitle><stitle>Nature</stitle><date>1953-09-19</date><risdate>1953</risdate><volume>172</volume><issue>4377</issue><spage>553</spage><epage>553</epage><pages>553-553</pages><issn>0028-0836</issn><eissn>1476-4687</eissn><abstract>VARIOUS methods, parametric and non-parametric, are used for examining the significance of the difference between two given samples. The most common of these is the parametric one, the
t
-test
1
, which is based on the assumption that the samples are drawn from a normal population. There is Pitman's
2
w
-test which has been built up by considering all the possible samples that can be drawn by pooling together the two samples. Besides these, Wald and Wolfowitz
3
have used the run theory for deciding the significance of the difference between two samples. This method has been extended for
k
samples by myself
4
. Recently, tests have been constructed by Wallis
5
, Kruskall
6
and Rijkoort
7
by using rank numbers for each of the samples.</abstract><cop>London</cop><pub>Nature Publishing Group UK</pub><doi>10.1038/172553a0</doi><tpages>1</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 0028-0836 |
| ispartof | Nature (London), 1953-09, Vol.172 (4377), p.553-553 |
| issn | 0028-0836 1476-4687 |
| language | eng |
| recordid | cdi_crossref_primary_10_1038_172553a0 |
| source | Nature; SpringerNature Journals |
| subjects | Humanities and Social Sciences letter multidisciplinary Science Science (multidisciplinary) |
| title | Testing of Two Samples |
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