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Coconut (song)
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"Coconut"
Single by Nilsson
from the album Nilsson Schmilsson
B-side
"The Moonbeam Song"
Released
June 1972 (1972)
Format
7" single
Recorded
1971 (1971)
Genre
Calypso
Length
3:52
Label
RCA Victor
Songwriter(s)
Harry Nilsson
Producer(s)
Richard Perry
Nilsson singles chronology
"Jump into the Fire"
(1972) "Coconut"
(1972) "You're Breakin' My Heart"
(1972)
"Jump into the Fire"
(1972) "Coconut"
(1972) "You're Breakin' My Heart"
(1972)
"Coconut" is a novelty song written and first recorded by American singer-songwriter Harry Nilsson, released as the third single from his 1971 album, Nilsson Schmilsson. It was on the U.S. Billboard charts for 10 weeks, reaching #8,[1] and was ranked by Billboard as the #66 song for 1972. It charted minorly in the UK, reaching #42.[2] "Coconut" did best in Canada, where it peaked at #5.[3] It was used to great effect in the Quentin Tarantino movie "Reservoir Dogs".
In 1998, a cover version was released by Australian singer Dannii Minogue as a single, peaking at #62 on the ARIA singles chart.
Contents
[hide]
1 Lyrics
2 Music
3 Personnel
4 Chart history
4.1 Weekly charts
4.2 Year-end charts
5 Dannii Minogue version
6 Other versions
7 References
8 External links
Lyrics[edit]
The lyrics feature four characters (the narrator, the brother, the sister, and the doctor), three of whom (narrator, sister, and doctor) are sung in different voices by Nilsson[citation needed]. The song describes a story in which a girl has a stomachache and calls her doctor who prescribes her a drink. With the help of her brother, they concoct a beverage consisting of lime and coconut. When the sister calls the doctor late at night, the doctor (annoyed at being awakened by such a complaint) laughs her off and recommends that she "put the lime in the coconut and drink 'em both together"—then call him in the morning.
Music[edit]
There are no chord changes in the song: an arpeggiated C7th accompanies the song.
Personnel[edit]
According to the 1971 LP credits:[4]
Harry Nilsson – vocals
Caleb Quaye – guitar
Ian Duck – acoustic guitar
Herbie Flowers – bass
Jim Gordon – drums, percussion
Roger Pope – drums
Chart history[edit]
Weekly charts[edit]
Chart (1972)
Peak
position
Canada RPM Top Singles[5] 5
UK (OCC) 42
US Billboard Hot 100[6] 8
US Cash Box Top 100[7] 12
Year-end charts[edit]
Chart (1972)
Rank
Canada[8] 55
US Billboard Hot 100[9] 66
US Cash Box[10] 87
Dannii Minogue version[edit]
"Coconut"
Single by Dannii Minogue
from the album Girl
B-side
"Everybody Changes Underwater"
"Heaven Can Wait"
"Someone New"
Released
November 16, 1998 (1998-11-16)
Format
CD single
Recorded
1994-1995
Genre
Dance-pop
techno-pop
Length
4:50
Label
WEA
Songwriter(s)
Harry Nilsson
Producer(s)
Flexifinger
(Original vocal production: DNA)
Dannii Minogue singles chronology
"Disremembrance"
(1998) "Coconut"
(1998) "Everlasting Night"
(1999)
"Disremembrance"
(1998) "Coconut"
(1998) "Everlasting Night"
(1999)
Dannii Minogue recorded the song in 1994 with UK dance producers DNA. When Minogue parted ways with Mushroom Records in 1995 and signed to Eternal Records in 1996, she had the track remixed by producers Flexifinger.
The track was originally used as a hidden bonus track on her third album Girl. It was subsequently released in Australia on November 16, 1998 as the fourth and final single from that album, peaking at #62 on the ARIA singles chart upon its debut, on the chart dated week commencing 23 November 1998.[11]
In 2009, the original version of "Coconut" was made available on the compilation The 1995 Sessions.
Other versions[edit]
Other cover versions of the song have been recorded by the Baha Men, Fred Schneider (on the "Everybody Sings Nilsson" tribute album), Lazlo Bane (under the title "Lime in the Coconut")[12], Sprung Monkey, P.M. Dawn, and, according to a Nilsson website, the Alice Cooper Band.[citation needed]
Flip Wilson (in his role of Geraldine Jones) covered this song in a fourth season episode of his variety show along with Harry Belafonte.
Kermit the Frog and other Muppet characters covered the song in a sketch on The Muppet Show (as part of episode 4.10, with guest Kenny Rogers). The scene showed Kermit in a hospital bed, having hurt his flipper after slipping on some oil on the floor in the theater, joining hospital staff singing the song as the room developed a jungle theme.[13]
The song was also used in commercials for Coca-Cola with Lime.[14]These ads are set in a Coke factory and a corporate boardroom and feature various people incorrectly singing the line as "you put the lime in the Coke, you nut!"
Fred Schneider performed the song on Late Night with Conan O'Brien[citation needed] after the release of the 1995 "Everybody Sings Nilsson" tribute album, for which the song was the lead single. He was joined on the show by the track's producer Richard Barone of The Bongos on lead guitar.
The Baha Men (portraying the "Ha-Ha Men") covered the song in the ChalkZone episode "The Smooch".
References[edit]
Jump up ^ Whitburn, Joel (2004). Billboard Top 40 Hits (8th ed.). p. 458. ISBN 0-8230-7499-4.
Jump up ^ UK Official Charts, 27 September 1969
Jump up ^ RPM Top Singles, September 9, 1972
Jump up ^ Nilsson Schmilsson (CD booklet: reproduced 1971 LP sleeve). Harry Nilsson. BMG Entertainment. 2000.
Jump up ^ "Item Display - RPM - Library and Archives Canada". Collectionscanada.gc.ca. Missing or empty |url= (help); |access-date= requires |url= (help)
Jump up ^ Joel Whitburn's Top Pop Singles 1955-1990 - ISBN 0-89820-089-X
Jump up ^ Cash Box Top 100 Singles, September 2, 1972
Jump up ^ "Best of 1972 songs and music, on". Musicandyears.com. 12 November 2010. Archived from the original on 16 September 2011. Retrieved 13 July 2017.
Jump up ^ Musicoutfitters.com
Jump up ^ Cash Box Year-End Charts: Top 100 Pop Singles, December 30, 1972
Jump up ^ "The ARIA Australian Top 100 Singles Chart: Week Commencing 23 Nov 1998". Australian Record Industry Association Ltd. Archived from the original on 2015-10-11. Retrieved 2015-10-11.
Jump up ^ "Lazlo Bane's Guilty Pleasures". cdbaby.com. Retrieved 2017-01-10.
Jump up ^ Coates, Tyler (January 7, 2015). "10 Essential Musical Moments From 'The Muppet Show'". Decider. Retrieved July 25, 2015.
Jump up ^ https://www.youtube.com/watch?v=cB4V860YojE
External links[edit]
Metrolyrics.com
[show]
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Harry Nilsson
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"Coconut"
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Related articles
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[show]
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Dannii Minogue
Discography
Studio albums
Dannii / Party Jam / Love and Kisses
Get into You
Girl
Neon Nights
Club Disco
Singles
"Love and Kisses"
"Success"
"Jump to the Beat"
"Baby Love"
"I Don't Wanna Take This Pain"
"Show You the Way to Go"
"Love's on Every Corner"
"This Is It"
"This is the Way"
"Get into You"
"Rescue Me"
"Boogie Woogie"
"All I Wanna Do"
"Everything I Wanted"
"Disremembrance"
"Coconut"
"Everlasting Night"
"Who Do You Love Now?"
"Put the Needle on It"
"I Begin to Wonder"
"Don't Wanna Lose This Feeling"
"Come and Get It"
"You Won't Forget About Me"
"Perfection"
"So Under Pressure"
"I Can't Sleep at Night"
"He's the Greatest Dancer"
"Touch Me Like That"
"Summer of Love"
"100 Degrees"
"Holding On"
"Galaxy"
Compilations
U.K. Remixes
The Singles
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The Hits & Beyond
Unleashed
The Early Years
The 1995 Sessions
This Is It: The Very Best Of
Video albums
Love and Kisses: Video Collection
Get into You: Video Collection
The Videos
Dannii Minogue: The Video Collection
Books
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Related articles
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Terry Ronald
Ian Masterson
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Categories:
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Yaadon Ki Baaraat
From Wikipedia, the free encyclopedia
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Yaadon Ki Baaraat
Directed by
Nasir Hussain
Produced by
Nasir Hussain
Written by
Salim-Javed
Nasir Hussain
Starring
Dharmendra
Zeenat Aman
Tariq Khan
Neetu Singh
Vijay Arora
Ajit Khan
Aamir Khan
Music by
R. D. Burman
Cinematography
Munir Khan
Edited by
Babu Lavande
Gurudutt Shirali
Distributed by
Nasir Hussain Films
United Producers
Release date
November 2, 1973 (India)
Running time
168 minutes
Country
India
Language
Hindi-Urdu[1]
Box office
₹5.5 crore ($7.1 million)
Yaadon Ki Baaraat (English: Procession of Memories) is a 1973 Indian Bollywood film, directed by Nasir Hussain and written by Salim-Javed (Salim Khan and Javed Akhtar). It featured an ensemble cast, starring Dharmendra, Zeenat Aman, Tariq Khan, Neetu Singh, Vijay Arora, Ajit Khan and Aamir Khan.
The film was influential in the history of Indian cinema. It was the first masala film, combining elements of the action, drama, romance, musical, crime and thriller genres.[2][3] The masala went on to become the most popular genre of Indian cinema,[4] and Yaadon Ki Baaraat has thus been identified as "the first" quintessentially "Bollywood film."[3] It also launched the careers of several actors, as the commercial breakthrough Hindi film for Zeenat Aman and Neetu Singh, who became leading actresses of the 1970s,[5][6] and as the debut film for Nasir Hussain's nephews Tariq Khan and Aamir Khan, the latter a child actor who grew up to be one of the biggest movie stars as an adult.[7]
It is still remembered fondly for its Hindi soundtrack, composed by music director R.D. Burman. The track "Chura Liya Hai", sung by Mohammed Rafi and Asha Bhosle, is particularly well-known. The film was later remade in Tamil as Naalai Namadhe, in Telugu as Annadammula Anubandham, and in Malayalam as Himam.[8]
Contents
[hide]
1 Plot
2 Cast
3 Production
4 Soundtrack
5 Reception
5.1 Box office
5.2 Accolades
6 Notes
7 References
8 External links
Plot[edit]
The film popularized the now familiar Bollywood theme of siblings separated by fate.[9] Gangland killers assassinate an honest man who defied them, killing his wife as well. The couple's three sons flee the massacre and lose contact with each other. They grow up in entirely different circumstances and are re-united only when one of the sons, sings the song that their mother taught them at their father's birthday at the hotel.
Shankar (Dharmendra), Vijay (Vijay Arora), and Ratan (Tariq Khan) are three brothers. On their father's birthday, their mother taught them a song titled Yaadon Ki Baaraat which they held dearly to their hearts. As fate may have it, one day, the boys' father witnessed a robbery by Shakaal and his henchmen. To protect their identity, Shakaal decided to kill the boys' father before he could go to the police. So one night, he and his men storm into the boys' father's room and kill both their mother and father. Shankar and Vijay witness the act and flee. They make their way to a passing train, where Shankar is separated from Vijay.
Several years pass by and the boys have grown up. Shankar is haunted by the memory of his parents' murder and is now joined by his friend Usman on a crime spree around the city. Vijay was adopted by the groundskeeper to a wealthy man, and he falls in love with the rich man's daughter Sunita (Zeenat Aman), and Ratan, was raised by the boys' maid, and changed his name to Monto. With his new identity, Monto started a band and does gigs at hotels for a living and is also in love with a co-singer (Neetu Singh).
The brothers meet several times, yet do not recognize each other. However, when they finally do, they cannot contact each other. Shankar gets caught by his boss, who is the real murderer of his parents. As the movie progresses, Shankar finds out the truth and leaves Shakal to die, while his foot gets caught in the changing lines of railway tracks. Shaakal is killed by the coming train and the brothers unite.
Cast[edit]
Dharmendra as Shankar
Zeenat Aman as Sunita
Ajit Khan as Shakaal
Vijay Arora as Vijay
Tariq Khan as Ratan/Monto
Aamir Khan (Master Aamir) as Young Ratan
Neetu Singh as Dancer (song 'Le Kar Hum Deewana Dil')
Ashu as Mother of Shankar/Vijay/Monto
Satyen Kappu as Jack
Jalal Agha as Salim
Archana
Master Rajesh
Master Salsh
Master Ravi
Imtiaz Khan as Roopesh
Ahmed Ali
Ravinder Kapoor as Usman Bhai Butliwala
Sham Kumar
M. B. Shetty as Martin
Anamika as Jack's Daughter
Ram Avtar & Moolchand as Two Businessmen
Ghafoor
Nawab
Bihar
Jagdish Raj
Bannerji
Sanjana
Ashoo as Mr. Verma
Sofia
Pompi
Mona
Kamal
Production[edit]
Nasir Hussain's nephew Aamir Khan who went on to become one of the successful actors in Bollywood made his acting debut as child artist at the age of eight with this film appearing in the title song.[10][11]
Soundtrack[edit]
Yaadon Ki Baaraat
Soundtrack album by R. D. Burman
Released
1973
Genre
Film soundtrack
Label
HMV
Producer
R. D. Burman (composer)
Majrooh Sultanpuri (lyrics)
The music and soundtrack of the film was by R. D. Burman, with lyrics by Majrooh Sultanpuri. The opening lines of the hit song, Chura Liya Hai Tumne have slight resemblances to the English song, If It's Tuesday, This Must Be Belgium from the soundtrack of the 1969 film of the same name.[12] Apart from the title song, the other best remembered numbers are "Lekar Hum Deewana Dil" and "Meri Soni Meri Tamanna".[13][14]
Track listing
#
Song
Singer(s)
Length
1 "Yaadon Ki Baaraat Nikli Hai" Lata Mangeshkar, Padmini Kolhapure & Sushma Shrestha 3:51
2 "Yaadon Ki Baarat Nikli Hai" Mohammed Rafi & Kishore Kumar 3:24
3 "Chura Liya Hai Tumne Jo Dil Ko" Mohammed Rafi & Asha Bhosle 4:49
4 "Lekar Hum Deewana Dil" Asha Bhosle & Kishore Kumar 5:58
5 "Aap Ke Kamre Mein Koi Rehta Hain" Kishore Kumar, Asha Bhosle & R. D. Burman 8:46
6 "O Meri Soni Meri Tamanna" Asha Bhosle & Kishore Kumar 4:31
Reception[edit]
Box office[edit]
The film became a box office hit. It was one of 1973's top five highest-grossing films in India, grossing ₹5.5 crore.[15] This was equivalent to $7.1 million in 1973,[n 1] and is equivalent to US$39 million or ₹255 crore[17] in 2016.
Accolades[edit]
21st Filmfare Awards
Best Actor – Dharmendra – Nominated
Best Music Director – R. D. Burman – Nominated
Notes[edit]
Jump up ^ 7.742 Indian rupees per US dollar in 1973[16]
References[edit]
Jump up ^ Lal, Vinay; Nandy, Ashis (2006). Fingerprinting Popular Culture: The Mythic and the Iconic in Indian Cinema. Oxford University Press. p. 77. ISBN 0195679180.
Jump up ^ Kaushik Bhaumik, An Insightful Reading of Our Many Indian Identities, The Wire, 12/03/2016
^ Jump up to: a b Chaudhuri, Diptakirti (2015-10-01). Written by Salim-Javed: The Story of Hindi Cinema’s Greatest Screenwriters. Penguin UK. p. 58. ISBN 9789352140084.
Jump up ^ Masala v. Genre - The Hindu
Jump up ^ Dinesh Raheja (12 November 2002). "The A to Z of Zeenat Aman". Rediff.com. Retrieved 2011-01-14.
Jump up ^ "Neetu Singh's TOI Archives". The Times of India. Retrieved 6 July 2013.
Jump up ^ Cain, Rob (3 October 2017). "Aamir Khan's 'Secret Superstar' Could Be India's Next ₹1,000 Crore/$152M Box Office Hit". Forbes.
Jump up ^ "Life & Style / Metroplus : Where has all the magic gone?". Retrieved 2012-11-03. . The Hindu (2012-07-20). Retrieved on 2012-11-03.
Jump up ^ "How film-maker Nasir Husain started the trend for Bollywood masala films". Hindustan Times. 30 March 2017.
Jump up ^ http://www.rediff.com/movies/slide-show/slide-show-1-the-47-faces-of-aamir-khan/20120314.htm#1
Jump up ^ http://www.rediff.com/movies/slide-show/slide-show-1-most-ambitious-project-of-aamirs-career/20120314.htm
Jump up ^ "RD Burman and the X factor". THe Hindu. 27 April 2011. Retrieved 7 May 2013.
Jump up ^ Rachel Dwyer, British Film Institute One hundred Bollywood films 1844570983 - 2005 - Page 247 "Apart from the title song, the other best remembered numbers are 'Lekar Hum Deewana Dil', again partly for the picturisation on the pin-up girl, Neetu Singh, and Asha and Kishore Kumar's duet, 'Meri Soni Meri Tamanna'. "
Jump up ^ Ganesh Anantharaman Bollywood Melodies: A History of the Hindi Film Song 0143063405 2008 Page 109 "With 150 films behind him, Majrooh could still write something as youthful as 'Raat Kali Ek Khwab Mein Aayi' (Kishore, Buddha Mil Gaya), 'Lekar Hum Deewana Dil' (Kishore—Asha, Yaadon Ki Baaraat) and 'Yeh Ladka Haaye Allah Kaisa Hain Deewana' (Hum Kisise Kum Naheen)"
Jump up ^ "Boxofficeindia.com". Boxofficeindia.com. Retrieved 2012-03-16.
Jump up ^ http://fx.sauder.ubc.ca/etc/USDpages.pdf#page=3
Jump up ^ 67.175856 INR per USD in 2016
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Psychometrics
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Not to be confused with psychrometrics, the measurement of the heat and water vapor properties of air.
For other uses of this term and similar terms, see Psychometry (disambiguation).
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Psychometrics is a field of study concerned with the theory and technique of psychological measurement. As defined by National Council on Measurement in Education (NCME), psychometrics refers to psychological measurement. Generally, it refers to the field in psychology and education that is devoted to testing, measurement, assessment, and related activities.[1]
The field is concerned with the objective measurement of skills and knowledge, abilities, attitudes, personality traits, and educational achievement. Some psychometric researchers focus on the construction and validation of assessment instruments such as questionnaires, tests, raters' judgments, and personality tests. Others focus on research relating to measurement theory (e.g., item response theory; intraclass correlation).
Practitioners are described as psychometricians. Psychometricians usually possess a specific qualification, and most are psychologists with advanced graduate training. In addition to traditional academic institutions, many psychometricians work for the government or in human resources departments. Others specialize as learning and development professionals.
Contents
[hide]
1 Historical foundation
1.1 Victorian stream
1.2 German stream
1.3 20th century
2 Definition of measurement in the social sciences
3 Instruments and procedures
4 Theoretical approaches
4.1 Key concepts
5 Standards of quality
5.1 Testing standards
5.2 Evaluation standards
6 Non-human: animals and machines
7 See also
8 References
8.1 Bibliography
8.2 Notes
9 Further reading
10 External links
Historical foundation[edit]
Psychological testing has come from two streams of thought: the first, from Darwin, Galton, and Cattell on the measurement of individual differences, and the second, from Herbart, Weber, Fechner, and Wundt and their psychophysical measurements of a similar construct. The second set of individuals and their research is what has led to the development of experimental psychology, and standardized testing.[2]
Victorian stream[edit]
Charles Darwin was the inspiration behind Sir Francis Galton who led to the creation of psychometrics. In 1859, Darwin published his book "The Origin of Species", which pertained to individual differences in animals. This book discussed how individual members in a species differ and how they possess characteristics that are more adaptive and successful or less adaptive and less successful. Those who are adaptive and successful are the ones that survive and give way to the next generation, who would be just as or more adaptive and successful. This idea, studied previously in animals, led to Galton's interest and study of human beings and how they differ one from another, and more importantly, how to measure those differences.
Galton wrote a book entitled "Hereditary Genius" about different characteristics that people possess and how those characteristics make them more "fit" than others. Today these differences, such as sensory and motor functioning (reaction time, visual acuity, and physical strength) are important domains of scientific psychology. Much of the early theoretical and applied work in psychometrics was undertaken in an attempt to measure intelligence. Galton, often referred to as "the father of psychometrics," devised and included mental tests among his anthropometric measures. James McKeen Cattell, who is considered a pioneer of psychometrics went on to extend Galton's work. Cattell also coined the term mental test, and is responsible for the research and knowledge which ultimately led to the development of modern tests. (Kaplan & Saccuzzo, 2010)
German stream[edit]
The origin of psychometrics also has connections to the related field of psychophysics. Around the same time that Darwin, Galton, and Cattell were making their discoveries, Herbart was also interested in "unlocking the mysteries of human consciousness" through the scientific method. (Kaplan & Saccuzzo, 2010) Herbart was responsible for creating mathematical models of the mind, which were influential in educational practices in years to come.
E.H. Weber built upon Herbart's work and tried to prove the existence of a psychological threshold, saying that a minimum stimulus was necessary to activate a sensory system. After Weber, G.T. Fechner expanded upon the knowledge he gleaned from Herbart and Weber, to devise the law that the strength of a sensation grows as the logarithm of the stimulus intensity. A follower of Weber and Fechner, Wilhelm Wundt is credited with founding the science of psychology. It is Wundt's influence that paved the way for others to develop psychological testing.[2]
20th century[edit]
The psychometrician L. L. Thurstone, founder and first president of the Psychometric Society in 1936, developed and applied a theoretical approach to measurement referred to as the law of comparative judgment, an approach that has close connections to the psychophysical theory of Ernst Heinrich Weber and Gustav Fechner. In addition, Spearman and Thurstone both made important contributions to the theory and application of factor analysis, a statistical method developed and used extensively in psychometrics.[citation needed] In the late 1950s, Leopold Szondi made an historical and epistemological assessment of the impact of statistical thinking onto psychology during previous few decades: "in the last decades, the specifically psychological thinking has been almost completely suppressed and removed, and replaced by a statistical thinking. Precisely here we see the cancer of testology and testomania of today."[3]
More recently, psychometric theory has been applied in the measurement of personality, attitudes, and beliefs, and academic achievement. Measurement of these unobservable phenomena is difficult, and much of the research and accumulated science in this discipline has been developed in an attempt to properly define and quantify such phenomena. Critics, including practitioners in the physical sciences and social activists, have argued that such definition and quantification is impossibly difficult, and that such measurements are often misused, such as with psychometric personality tests used in employment procedures:
"For example, an employer wanting someone for a role requiring consistent attention to repetitive detail will probably not want to give that job to someone who is very creative and gets bored easily."[4]
Figures who made significant contributions to psychometrics include Karl Pearson, Henry F. Kaiser, Carl Brigham, L. L. Thurstone, Anne Anastasi, Georg Rasch, Eugene Galanter, Johnson O'Connor, Frederic M. Lord, Ledyard R Tucker, Arthur Jensen, and David Andrich.
Definition of measurement in the social sciences[edit]
The definition of measurement in the social sciences has a long history. A currently widespread definition, proposed by Stanley Smith Stevens (1946), is that measurement is "the assignment of numerals to objects or events according to some rule." This definition was introduced in the paper in which Stevens proposed four levels of measurement. Although widely adopted, this definition differs in important respects from the more classical definition of measurement adopted in the physical sciences, namely that scientific measurement entails "the estimation or discovery of the ratio of some magnitude of a quantitative attribute to a unit of the same attribute" (p. 358)[5]
Indeed, Stevens's definition of measurement was put forward in response to the British Ferguson Committee, whose chair, A. Ferguson, was a physicist. The committee was appointed in 1932 by the British Association for the Advancement of Science to investigate the possibility of quantitatively estimating sensory events. Although its chair and other members were physicists, the committee also included several psychologists. The committee's report highlighted the importance of the definition of measurement. While Stevens's response was to propose a new definition, which has had considerable influence in the field, this was by no means the only response to the report. Another, notably different, response was to accept the classical definition, as reflected in the following statement:
Measurement in psychology and physics are in no sense different. Physicists can measure when they can find the operations by which they may meet the necessary criteria; psychologists have but to do the same. They need not worry about the mysterious differences between the meaning of measurement in the two sciences. (Reese, 1943, p. 49)
These divergent responses are reflected in alternative approaches to measurement. For example, methods based on covariance matrices are typically employed on the premise that numbers, such as raw scores derived from assessments, are measurements. Such approaches implicitly entail Stevens's definition of measurement, which requires only that numbers are assigned according to some rule. The main research task, then, is generally considered to be the discovery of associations between scores, and of factors posited to underlie such associations.[citation needed]
On the other hand, when measurement models such as the Rasch model are employed, numbers are not assigned based on a rule. Instead, in keeping with Reese's statement above, specific criteria for measurement are stated, and the goal is to construct procedures or operations that provide data that meet the relevant criteria. Measurements are estimated based on the models, and tests are conducted to ascertain whether the relevant criteria have been met.[citation needed]
Instruments and procedures[edit]
The first[citation needed]psychometric instruments were designed to measure the concept of intelligence.[6] One historical approach involved the Stanford-Binet IQ test, developed originally by the French psychologist Alfred Binet. Intelligence tests are useful tools for various purposes. An alternative conception of intelligence is that cognitive capacities within individuals are a manifestation of a general component, or general intelligence factor, as well as cognitive capacity specific to a given domain.[citation needed]
Psychometrics is applied widely[citation needed] in educational assessment to measure abilities in domains such as reading, writing, and mathematics. The main approaches in applying tests in these domains have been classical test theory and the more recent Item Response Theory and Rasch measurement models. These latter approaches permit joint scaling of persons and assessment items, which provides a basis for mapping of developmental continua by allowing descriptions of the skills displayed at various points along a continuum.[citation needed]
Another major focus in psychometrics has been on personality testing. There have been a range of theoretical approaches to conceptualizing and measuring personality. Some of the better known instruments include the Minnesota Multiphasic Personality Inventory, the Five-Factor Model (or "Big 5") and tools such as Personality and Preference Inventory and the Myers-Briggs Type Indicator. Attitudes have also been studied extensively using psychometric approaches.[citation needed] A common method in the measurement of attitudes is the use of the Likert scale. An alternative method involves the application of unfolding measurement models, the most general being the Hyperbolic Cosine Model (Andrich & Luo, 1993).[7]
Theoretical approaches[edit]
Psychometricians have developed a number of different measurement theories. These include classical test theory (CTT) and item response theory (IRT).[8][9] An approach which seems mathematically to be similar to IRT but also quite distinctive, in terms of its origins and features, is represented by the Rasch model for measurement. The development of the Rasch model, and the broader class of models to which it belongs, was explicitly founded on requirements of measurement in the physical sciences.[10]
Psychometricians have also developed methods for working with large matrices of correlations and covariances. Techniques in this general tradition include: factor analysis,[11] a method of determining the underlying dimensions of data; multidimensional scaling,[12] a method for finding a simple representation for data with a large number of latent dimensions; and data clustering, an approach to finding objects that are like each other. All these multivariate descriptive methods try to distill large amounts of data into simpler structures. More recently, structural equation modeling[13] and path analysis represent more sophisticated approaches to working with large covariance matrices. These methods allow statistically sophisticated models to be fitted to data and tested to determine if they are adequate fits.
One of the main deficiencies in various factor analyses is a lack of consensus in cutting points for determining the number of latent factors. A usual procedure is to stop factoring when eigenvalues drop below one because the original sphere shrinks. The lack of the cutting points concerns other multivariate methods, also.[citation needed]
Key concepts[edit]
Key concepts in classical test theory are reliability and validity. A reliable measure is one that measures a construct consistently across time, individuals, and situations. A valid measure is one that measures what it is intended to measure. Reliability is necessary, but not sufficient, for validity.
Both reliability and validity can be assessed statistically. Consistency over repeated measures of the same test can be assessed with the Pearson correlation coefficient, and is often called test-retest reliability.[14] Similarly, the equivalence of different versions of the same measure can be indexed by a Pearson correlation, and is called equivalent forms reliability or a similar term.[14]
Internal consistency, which addresses the homogeneity of a single test form, may be assessed by correlating performance on two halves of a test, which is termed split-half reliability; the value of this Pearson product-moment correlation coefficient for two half-tests is adjusted with the Spearman–Brown prediction formula to correspond to the correlation between two full-length tests.[14] Perhaps the most commonly used index of reliability is Cronbach's α, which is equivalent to the mean of all possible split-half coefficients. Other approaches include the intra-class correlation, which is the ratio of variance of measurements of a given target to the variance of all targets.
There are a number of different forms of validity. Criterion-related validity can be assessed by correlating a measure with a criterion measure theoretically expected to be related. When the criterion measure is collected at the same time as the measure being validated the goal is to establish concurrent validity; when the criterion is collected later the goal is to establish predictive validity. A measure has construct validity if it is related to measures of other constructs as required by theory. Content validity is a demonstration that the items of a test do an adequate job of covering the domain being measured. In a personnel selection example, test content is based on a defined statement or set of statements of knowledge, skill, ability, or other characteristics obtained from a job analysis.
Item response theory models the relationship between latent traits and responses to test items. Among other advantages, IRT provides a basis for obtaining an estimate of the location of a test-taker on a given latent trait as well as the standard error of measurement of that location. For example, a university student's knowledge of history can be deduced from his or her score on a university test and then be compared reliably with a high school student's knowledge deduced from a less difficult test. Scores derived by classical test theory do not have this characteristic, and assessment of actual ability (rather than ability relative to other test-takers) must be assessed by comparing scores to those of a "norm group" randomly selected from the population. In fact, all measures derived from classical test theory are dependent on the sample tested, while, in principle, those derived from item response theory are not.
Many psychometricians are also concerned with finding and eliminating test bias from their psychological tests. Test bias is a form of systematic (i.e., non-random) error which leads to examinees from one demographic group having an unwarranted advantage over examinees from another demographic group.[15] According to leading experts, test bias may cause differences in average scores across demographic groups, but differences in group scores are not sufficient evidence that test bias is actually present because the test could be measuring real differences among groups.[16][17] Psychometricians use sophisticated scientific methods to search for test bias and eliminate it. Research shows that it is usually impossible for people reading a test item to accurately determine whether it is biased or not.[18]
Standards of quality[edit]
The considerations of validity and reliability typically are viewed as essential elements for determining the quality of any test. However, professional and practitioner associations frequently have placed these concerns within broader contexts when developing standards and making overall judgments about the quality of any test as a whole within a given context. A consideration of concern in many applied research settings is whether or not the metric of a given psychological inventory is meaningful or arbitrary.[19]
Testing standards[edit]
In 2014, the American Educational Research Association (AERA), American Psychological Association (APA), and National Council on Measurement in Education (NCME) published a revision of the Standards for Educational and Psychological Testing,[20] which describes standards for test development, evaluation, and use. The Standards cover essential topics in testing including validity, reliability/errors of measurement, and fairness in testing. The book also establishes standards related to testing operations including test design and development, scores, scales, norms, score linking, cut scores, test administration, scoring, reporting, score interpretation, test documentation, and rights and responsibilities of test takers and test users. Finally, the Standards cover topics related to testing applications, including psychological testing and assessment, workplace testing and credentialing, educational testing and assessment, and testing in program evaluation and public policy.
Evaluation standards[edit]
In the field of evaluation, and in particular educational evaluation, the Joint Committee on Standards for Educational Evaluation[21] has published three sets of standards for evaluations. The Personnel Evaluation Standards[22] was published in 1988, The Program Evaluation Standards (2nd edition)[23] was published in 1994, and The Student Evaluation Standards[24] was published in 2003.
Each publication presents and elaborates a set of standards for use in a variety of educational settings. The standards provide guidelines for designing, implementing, assessing and improving the identified form of evaluation.[25] Each of the standards has been placed in one of four fundamental categories to promote educational evaluations that are proper, useful, feasible, and accurate. In these sets of standards, validity and reliability considerations are covered under the accuracy topic. For example, the student accuracy standards help ensure that student evaluations will provide sound, accurate, and credible information about student learning and performance.
Non-human: animals and machines[edit]
Psychometrics addresses human abilities, attitudes, traits and educational evolution. Notably, the study of behavior, mental processes and abilities of non-human animals is usually addressed by comparative psychology, or with a continuum between non-human animals and the rest of animals by evolutionary psychology. Nonetheless there are some advocators for a more gradual transition between the approach taken for humans and the approach taken for (non-human) animals.[26][27][28] [29]
The evaluation of abilities, traits and learning evolution of machines has been mostly unrelated to the case of humans and non-human animals, with specific approaches in the area of artificial intelligence. A more integrated approach, under the name of universal psychometrics, has also been proposed.[30]
See also[edit]
Classical test theory
Concept inventory
Cronbach's alpha
Data mining
Educational assessment
Educational psychology
Item response theory
List of psychometric software
List of schools for psychometrics
Operationalisation
Quantitative psychology
Psychometric Society
Rasch model
Scale (social sciences)
School counselor
School psychology
Standardized test
References[edit]
Bibliography[edit]
Andrich, D. & Luo, G. (1993). "A hyperbolic cosine model for unfolding dichotomous single-stimulus responses" (PDF). Applied Psychological Measurement. 17 (3): 253–276. doi:10.1177/014662169301700307.
Michell, J. (1999). Measurement in Psychology. Cambridge: Cambridge University Press. DOI: 10.1017/CBO9780511490040
Rasch, G. (1960/1980). Probabilistic models for some intelligence and attainment tests. Copenhagen, Danish Institute for Educational Research), expanded edition (1980) with foreword and afterword by B.D. Wright. Chicago: The University of Chicago Press.
Reese, T.W. (1943). "The application of the theory of physical measurement to the measurement of psychological magnitudes, with three experimental examples". Psychological Monographs. 55: 1–89.
Stevens, S. S. (1946). "On the theory of scales of measurement". Science. 103 (2684): 677–80. PMID 17750512. doi:10.1126/science.103.2684.677.
Thurstone, L.L. (1927). "A law of comparative judgement". Psychological Review. 34 (4): 278–286. doi:10.1037/h0070288.
Thurstone, L.L. (1929). The Measurement of Psychological Value. In T.V. Smith and W.K. Wright (Eds.), Essays in Philosophy by Seventeen Doctors of Philosophy of the University of Chicago. Chicago: Open Court.
Thurstone, L.L. (1959). The Measurement of Values. Chicago: The University of Chicago Press.
S.F. Blinkhorn (1997). "Past imperfect, future conditional: fifty years of test theory". Br. J. Math. Statist. Psychol. 50 (2): 175–185. doi:10.1111/j.2044-8317.1997.tb01139.x.
Notes[edit]
Jump up ^ National Council on Measurement in Education http://www.ncme.org/ncme/NCME/Resource_Center/Glossary/NCME/Resource_Center/Glossary1.aspx?hkey=4bb87415-44dc-4088-9ed9-e8515326a061#anchorP
^ Jump up to: a b Kaplan, R.M., & Saccuzzo, D.P. (2010). Psychological Testing: Principles, Applications, and Issues. (8th ed.). Belmont, CA: Wadsworth, Cengage Learning.
Jump up ^ Leopold Szondi (1960) Das zweite Buch: Lehrbuch der Experimentellen Triebdiagnostik. Huber, Bern und Stuttgart, 2nd edition. Ch.27, From the Spanish translation, B)II Las condiciones estadisticas, p.396. Quotation:
el pensamiento psicologico especifico, en las ultima decadas, fue suprimido y eliminado casi totalmente, siendo sustituido por un pensamiento estadistico. Precisamente aqui vemos el cáncer de la testología y testomania de hoy.
Jump up ^ Psychometric Assessments. Psychometric Assessments . University of Melbourne.
Jump up ^ Michell, Joel (August 1997). "Quantitative science and the definition of measurement in psychology". British Journal of Psychology. 88 (3): 355–383. doi:10.1111/j.2044-8295.1997.tb02641.x.
Jump up ^ Different psychometric test
Jump up ^ Andrich, D. & Luo, G. (1993). A hyperbolic cosine latent trait model for unfolding dichotomous single-stimulus responses. Applied Psychological Measurement, 17, 253-276.
Jump up ^ Embretson, S.E., & Reise, S.P. (2000). Item Response Theory for Psychologists. Mahwah, NJ: Erlbaum.
Jump up ^ Hambleton, R.K., & Swaminathan, H. (1985). Item Response Theory: Principles and Applications. Boston: Kluwer-Nijhoff.
Jump up ^ Rasch, G. (1960/1980). Probabilistic models for some intelligence and attainment tests. Copenhagen, Danish Institute for Educational Research, expanded edition (1980) with foreword and afterword by B.D. Wright. Chicago: The University of Chicago Press.
Jump up ^ Thompson, B.R. (2004). Exploratory and Confirmatory Factor Analysis: Understanding Concepts and Applications. American Psychological Association.
Jump up ^ Davison, M.L. (1992). Multidimensional Scaling. Krieger.
Jump up ^ Kaplan, D. (2008). Structural Equation Modeling: Foundations and Extensions, 2nd ed. Sage.
^ Jump up to: a b c Reliability definitions at the University of Connecticut
Jump up ^ Warne, Russell T.; Yoon, Myeongsun; Price, Chris J. "Exploring the various interpretations of “test bias”". Cultural Diversity and Ethnic Minority Psychology. 20: 570–582. doi:10.1037/a0036503. Retrieved 23 February 2017.
Jump up ^ Reynolds, C. R. (2000). Why is psychometric research on bias in mental testing so often ignored? Psychology, Public Policy, and Law, 6, 144-150. doi:10.1037/1076-8971.6.1.144
Jump up ^ Warne, Russell T.; Yoon, Myeongsun; Price, Chris J. "Exploring the various interpretations of “test bias”". Cultural Diversity and Ethnic Minority Psychology. 20: 570–582. doi:10.1037/a0036503. Retrieved 23 February 2017.
Jump up ^ Reschly, D. J. (1980) Psychological evidence in the Larry P. opinion: A case of right problem-wrong solution? School Psychology Review, 9, 123-125.
Jump up ^ Blanton, H., & Jaccard, J. (2006). Arbitrary metrics in psychology. American Psychologist, 61(1), 27-41.
Jump up ^ AERA, APA & NCME. (2014). Standards for Educational and Psychological Testing. Washington, DC: American Educational Research Association
Jump up ^ Joint Committee on Standards for Educational Evaluation
Jump up ^ Joint Committee on Standards for Educational Evaluation. (1988). The Personnel Evaluation Standards: How to Assess Systems for Evaluating Educators. Newbury Park, CA: Sage Publications.
Jump up ^ Joint Committee on Standards for Educational Evaluation. (1994). The Program Evaluation Standards, 2nd Edition. Newbury Park, CA: Sage Publications.
Jump up ^ Committee on Standards for Educational Evaluation. (2003). The Student Evaluation Standards: How to Improve Evaluations of Students. Newbury Park, CA: Corwin Press.
Jump up ^ [ E. Cabrera-Nguyen. "Author guidelines for reporting scale development and validation results in the Journal of the Society for Social Work and Research]". academia.edu.
Jump up ^ Humphreys, L.G. (1987). "Psychometrics considerations in the evaluation of intraspecies differences in intelligence". Behav Brain Sci. 10: 668–669. doi:10.1017/s0140525x0005514x.
Jump up ^ Eysenck, H.J. (1987). "The several meanings of intelligence". Behav Brain Sci. 10: 663. doi:10.1017/s0140525x00055060.
Jump up ^ Locurto, C. & Scanlon, C (1987). "Individual differences and spatial learning factor in two strains of mice". Behav Brain Sci. 112: 344–352.
Jump up ^ King, James E & Figueredo, Aurelio Jose (1997). "The five-factor model plus dominance in chimpanzee personality". Journal of Research in Personality. 31 (2): 257–271. doi:10.1006/jrpe.1997.2179.
Jump up ^ J. Hernández-Orallo; D.L. Dowe; M.V. Hernández-Lloreda (2013). "Universal Psychometrics: Measuring Cognitive Abilities in the Machine Kingdom". Cognitive Systems Research. hdl:10251/50244.
Further reading[edit]
Robert F. DeVellis (2016). Scale Development: Theory and Applications. SAGE Publications. ISBN 978-1-5063-4158-3.
Borsboom, Denny (2005). Measuring the Mind: Conceptual Issues in Contemporary Psychometrics. Cambridge: Cambridge University Press. ISBN 978-0-521-84463-5. Lay summary (28 June 2010).
Leslie A. Miller; Robert L. Lovler (2015). Foundations of Psychological Testing: A Practical Approach. SAGE Publications. ISBN 978-1-4833-6927-3.
Roderick P. McDonald (2013). Test Theory: A Unified Treatment. Psychology Press. ISBN 978-1-135-67530-1.
Paul Kline (2000). The Handbook of Psychological Testing. Psychology Press. ISBN 978-0-415-21158-1.
Rush AJ Jr; First MB; Blacker D (2008). Handbook of Psychiatric Measures. American Psychiatric Publishing. ISBN 978-1-58562-218-4. OCLC 85885343.
Ann C Silverlake (2016). Comprehending Test Manuals: A Guide and Workbook. Taylor & Francis. ISBN 978-1-351-97086-0.
External links[edit]
Wikiversity has learning resources about Psychometrics
Look up psychometrics in Wiktionary, the free dictionary.
APA Standards for Educational and Psychological Testing
International Personality Item Pool
Joint Committee on Standards for Educational Evaluation
The Psychometrics Centre, University of Cambridge
Psychometric Society and Psychometrika homepage
London Psychometric Laboratory

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View the content page [ctrl-alt-c]
c

values: portal navigation p-navigation p-navigation-label

values: Guidance on how to use and edit Wikipedia

values: About the project, what you can do, where to find things

values: A list of recent changes in the wiki [ctrl-alt-r]

values: portal navigation p-interaction p-interaction-label

values: List of all English Wikipedia pages containing links to this page [ctrl-alt-j]

values: Recent changes in pages linked from this page [ctrl-alt-k]

values:
/wiki/Wikipedia:File_Upload_Wizard
Upload files [ctrl-alt-u]
u

values: A list of all special pages [ctrl-alt-q]

values: Permanent link to this revision of the page

values: Link to connected data repository item [ctrl-alt-g]

values: Printable version of this page [ctrl-alt-p]

values: portal navigation p-wikibase-otherprojects p-wikibase-otherprojects-label

values:
uls-settings-trigger
Language settings
0
button
true

values: القياس النفسي – Arabic

values: Психометрия – Bulgarian

values: روان‌سنجی – Persian

values: 심리측정학 – Korean

values: मनोमिति – Hindi

values: בחינה פסיכומטרית – Hebrew

values: Психометрия – Russian

values: Психометрија – Serbian

values: Психометрія – Ukrainian

values: /static/images/wikimedia-button-1.5x.png 1.5x, /static/images/wikimedia-button-2x.png 2x

values: /static/images/poweredby_mediawiki_132x47.png 1.5x, /static/images/poweredby_mediawiki_176x62.png 2x

values:
suggestions
display: none; font-size: 13px;

values: mediawiki ltr sitedir-ltr mw-hide-empty-elt ns-0 ns-subject page-Psychometrics rootpage-Psychometrics vector-experimental-print-styles vector-nav-directionality skin-vector action-view