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Cuzick–edwards Test
In statistics, the Cuzick–Edwards test[1] is a significance test whose aim is to detect the possible clustering of sub-populations within a clustered or non-uniformly-spread overall population. Possible applications of the test include examining the spatial clustering of childhood leukemia and lymphoma within the general population, given that the general population is spatially clustered. The test is based on:using control locations within the general population as the basis of a second or "control" sub-population in addition to the original "case" sub-population; using "nearest-neighbour" analyses to form statistics based on either:the number of other "cases" among the neighbours of each case; the number "cases" which are nearer to each given case than the k-th nearest "control" for that case.An example application of this test was to spatial clustering of leukaemias and lymphomas among young people in New Zealand.[2] See also[edit]Clustering (demographi
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Statistics
Statistics
Statistics
is a branch of mathematics dealing with the collection, analysis, interpretation, presentation, and organization of data.[1][2] In applying statistics to, for example, a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model process to be studied. Populations can be diverse topics such as "all people living in a country" or "every atom composing a crystal". Statistics
Statistics
deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments.[1] See glossary of probability and statistics. When census data cannot be collected, statisticians collect data by developing specific experiment designs and survey samples. Representative sampling assures that inferences and conclusions can reasonably extend from the sample to the population as a whole
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Significance Test
A statistical hypothesis, sometimes called confirmatory data analysis, is a hypothesis that is testable on the basis of observing a process that is modeled via a set of random variables.[1] A statistical hypothesis test is a method of statistical inference. Commonly, two statistical data sets are compared, or a data set obtained by sampling is compared against a synthetic data set from an idealized model. A hypothesis is proposed for the statistical relationship between the two data sets, and this is compared as an alternative to an idealized null hypothesis that proposes no relationship between two data sets. The comparison is deemed statistically significant if the relationship between the data sets would be an unlikely realization of the null hypothesis according to a threshold probability—the significance level
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Leukemia
Leukemia, also spelled leukaemia, is a group of cancers that usually begin in the bone marrow and result in high numbers of abnormal white blood cells.[8] These white blood cells are not fully developed and are called blasts or leukemia cells.[2] Symptoms may include bleeding and bruising problems, feeling tired, fever, and an increased risk of infections.[2] These symptoms occur due to a lack of normal blood cells.[2] Diagnosis is typically made by blood tests or bone marrow biopsy.[2] The exact cause of leukemia is unknown.[4] A combination of genetic factors and environmental (non-inherited) factors are believed to play a role.[4] Risk factors include smoking, ionizing radiation, some chemicals (such as benzene), prior chemotherapy, and Down syndrome.[4][3] People with a family history of leukemia are also at higher risk.[3] There are four main types of leukemia — acute lymphoblastic leukemia (ALL), acute myeloid leukemia (AML), chronic lymphocytic leukemia (CLL) and chronic myelo
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Lymphoma
Lymphoma
Lymphoma
is a group of blood cancers that develop from lymphocytes (a type of white blood cell).[7] The name often refers to just the cancerous versions rather than all such tumors.[7] Signs and symptoms may include enlarged lymph nodes, fever, drenching sweats, unintended weight loss, itching, and constantly feeling tired.[1][2] The enlarged lymph nodes are usually painless.[1] The sweats are most common at night.[1][2] There are dozens of subtypes of lymphomas.[8] The two main categories of lymphomas are Hodgkin's lymphomas (HL) and the non-Hodgkin lymphomas (NHL).[9] The
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Jack Cuzick
Jack Martin Cuzick[2] CBE, FRS (born 11 August 1948) is a British academic, director of the Wolfson Institute of Preventive Medicine in London and head of the Centre for Cancer Prevention
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International Standard Serial Number
An International Standard Serial Number
International Standard Serial Number
(ISSN) is an eight-digit serial number used to uniquely identify a serial publication.[1] The ISSN is especially helpful in distinguishing between serials with the same title. ISSN are used in ordering, cataloging, interlibrary loans, and other practices in connection with serial literature.[2] The ISSN system was first drafted as an International Organization for Standardization (ISO) international standard in 1971 and published as ISO 3297 in 1975.[3] ISO subcommittee TC 46/SC 9 is responsible for maintaining the standard. When a serial with the same content is published in more than one media type, a different ISSN is assigned to each media type. For example, many serials are published both in print and electronic media
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JSTOR
JSTOR
JSTOR
(/ˈdʒeɪstɔːr/ JAY-stor;[3] short for Journal Storage) is a digital library founded in 1995. Originally containing digitized back issues of academic journals, it now also includes books and primary sources, and current issues of journals.[4] It provides full-text searches of almost 2,000 journals.[5] As of 2013, more than 8,000 institutions in more than 160 countries had access to JSTOR;[5] most access is by subscription, but some older public domain content is freely available to anyone.[6] JSTOR's revenue was $69 million in 2014.[7]Contents1 History 2 Content 3 Access3.1 Aaron Swartz
Aaron Swartz
incident 3.2 Limitations 3.3 Increasing public access4 Use 5 See also 6 References 7 Further reading 8 External linksHistory[edit] William G
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International Standard Book Number
"ISBN" redirects here. For other uses, see ISBN (other).International Standard Book
Book
NumberA 13-digit ISBN, 978-3-16-148410-0, as represented by an EAN-13 bar codeAcronym ISBNIntroduced 1970; 48 years ago (1970)Managing organisation International ISBN AgencyNo. of digits 13 (formerly 10)Check digit Weighted sumExample 978-3-16-148410-0Website www.isbn-international.orgThe International Standard Book
Book
Number (ISBN) is a unique[a][b] numeric commercial book identifier. Publishers purchase ISBNs from an affiliate of the International ISBN Agency.[1] An ISBN is assigned to each edition and variation (except reprintings) of a book. For example, an e-book, a paperback and a hardcover edition of the same book would each have a different ISBN. The ISBN is 13 digits long if assigned on or after 1 January 2007, and 10 digits long if assigned before 2007
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Special
Special
Special
or specials may refer to:Contents1 Music 2 Film and television 3 Other uses 4 See alsoMusic[edit] Special
Special
(album), a 1992 album by Vesta Williams "Special" (Garbage song), 1998 "Special
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Clustering (demographics)
In demographics, clustering is the gathering of various populations based on ethnicity, economics, or religion. In countries that hold equality important, clustering occurs between groups because of polarizing factors such as religion, wealth or ethnocentrism. Clustering is often considered an enriching part of free cultures in which one can visit a Chinatown or a French quarter for restaurant choices. Other sociologists assert that clustering of like minded individuals leads to political polarity and intolerance of contrary opinions, as the United States has allegedly been trending since the 1950s.[1] References[edit]^ Bill Bishop, Robert G
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Cuzick–edwards Test
In statistics, the Cuzick–Edwards test[1] is a significance test whose aim is to detect the possible clustering of sub-populations within a clustered or non-uniformly-spread overall population. Possible applications of the test include examining the spatial clustering of childhood leukemia and lymphoma within the general population, given that the general population is spatially clustered. The test is based on:using control locations within the general population as the basis of a second or "control" sub-population in addition to the original "case" sub-population; using "nearest-neighbour" analyses to form statistics based on either:the number of other "cases" among the neighbours of each case; the number "cases" which are nearer to each given case than the k-th nearest "control" for that case.An example application of this test was to spatial clustering of leukaemias and lymphomas among young people in New Zealand.[2] See also[edit]Clustering (demographi
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