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Topic: Spearman's hypothesis

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Upstream: Upstream: Issues: Bell Curve: South Africa All the studies on which Jensen based his analysis were carried out in the United States; therefore, it has not been demonstrated that Spearman's hypothesis holds true for other Black-White populations. With regard to Spearman's hypothesis, it was found that, although the mean White-Indian differences were about one standard deviation, these differences did not support the hypothesis. Spearman (1927) first noted this Black-White difference and suggested that the magnitude of the difference is positively related to the degree to which tests measure general intellectual ability (g), that is, the more highly correlated a test is with g, the greater the Black-White difference. www.mugu.com /cgi-bin/Upstream/People/Lynn/lynn-iq-sa.html

Charles Spearman English Psychologist Pioneer of Factor Analysis Known for Spearman’s Rank Correlation Coefficient Questia.com Online Library Spearman's Hypothesis and Test Score Differences Between Whites, Indians, and Blacks in South Africa, in Journal of General Psychology ...More on Psychometric g and "Spearmans Hypothesis" Arthur R. Jensen...Berkeley What I have labeled " Spearmans hypothesis" was indeed only a "minor...does not belittle its... Spearman's G = Anderson's Act?: Reflections on the Locus of Generality in Human Cognition, in Journal of the Learning Sciences www.questia.com /popularSearches/charles_spearman.jsp   (498 words)

The effect of the size of the rock pools on the diversity of animals in the rock pool. Since the calculated value of spearman's rank correlation coefficient is less than the critical value we can accept the null hypothesis and reject the experimental hypothesis. Spearman Rank Correlation Coefficient is a value, between -1 and 1, which is used to see how 2 sets of ranks correlate. Spearmans Coefficient = 1 - 6 D2 The values of diversity of each rock pool (calculations shown) and the volume of each rock pool were summarized in the results table in the following page. www.coursework.info /i/58191.html   (577 words)

Jensen, Arthur R. (1999) The G Factor: the Science of Mental Ability, Psycoloquy: 10,#23 Intelligence G Factor (1) Spearman's hypothesis has also been studied using elementary cognitive tasks (ECTs) that measure the time it takes a person to process information presented in tasks which are so simple that all persons in the study sample are able to perform them correctly in only one or two seconds. Spearman thought of g metaphorically as "mental energy" that could be applied to any and every kind of mental task, and likened group factors and specificity to specialized "engines" for the performance of certain types of tasks. Charles Spearman (1927) suggested that the different relative magnitudes of the W-B differences on various tests are a function of each test's g loading. psycprints.ecs.soton.ac.uk /archive/00000658   (577 words)

sthypo.html AB Tests C. Spearman's (1927) hypothesis that Black-White differences on a set of cognitive tests are positively associated with the tests' g loadings (the general intellectual ability) in a South African sample. Reasons and examples are given to argue that affirmation of a scientific hypothesis must be based primarily on substantive evidence that is independent of a hypothesis test. Significant p -values for the hypothesis tests indicate that Ss' rating of instructors was dependent on the 4 factors investigated. www.uic.edu /classes/comm/comm201/sthypo.html   (4136 words)

Discovery of site in brain linked to I.Q. Whenever high-g questions were worked on, the same small region of the brain was activated in each person, just as Spearman's hypothesis predicts. This led Psychologist Charles Spearman to propose way back in 1904 that there must be some general factor of intelligence that the tests were measuring. The idea was that analytical thinking requires a large set of separate information handling abilities from different parts of the brain, some spatial, some verbal, many involved with the speed with which particular groups of nerve cells can process information. www.txtwriter.com /onscience/Articles/brainIQ.html   (4136 words)

Statistical methods The Spearman Rank Correlation Coefficient is used to discover the strength of a link between two sets of data. When using Spearman Rank the data is best presented as a table. The hypothesis must be written in a clear and concise way so that other people can easily understand the aims of the investigation. www.zephryus.demon.co.uk /geography/resources/fieldwork/stats/spear.html   (993 words)

Kevin Kelly -- The Technium Clearly this began more than a century ago with Galton, then was further developed by Pearson, Neyman, Fisher, Spearman, and others in the first three decades of the twentieth century. But it really only became practicable with computers, and the past fifty years have seen the first systematic use of the main techniques used to establish cause and effect in this fields: Multiple regression (and its special case Analysis of Variance), path analysis, time-series analysis, and so on. www.kk.org /thetechnium/index.php   (993 words)

To find out how channel characteristics such as width, depth, area, efficiency, gradient and bedload change downstream As the correlation coefficient in very similar to 1 (0.953), this rejects the null hypothesis, which means statistically there is a positive correlation. A spearmans rank correlation test is one which can be calculated using the ranks assigned to sample members as data. In support of my results the Spearmans Rank Correlation Coefficient can also show the that there is a strong positive correlation. www.coursework.info /i/12026.html   (902 words)

Encyclopedia: Statistics These inferences may take the form of answers to essentially yes/no questions (hypothesis testing), estimates of numerical characteristics (estimation), prediction of future observations, descriptions of association (correlation), or modeling of relationships (regression). In probability theory and statistics, correlation, also called correlation coefficient, is a numeric measure of the strength of linear relationship between two random variables. Patterns in the data are modeled to draw inferences about the larger population, using inferential statistics to account for randomness and uncertainty in the observations. www.nationmaster.com /encyclopedia/statistics   (1061 words)

NMath Stats User's Guide - 3.9 Covariance, Correlation, and Autocorrelation Spearman's rho differs from Pearson's correlation only in that the computation is done after the values in the data set are converted to ranks (Section 3.5). Spearmans() calculates the Spearman rank correlation coefficient, commonly known as Spearman's rho. Fisher() calculates the Fisher transformation at a given value, which can be used to perform hypothesis testing on the correlation coefficient. www.centerspace.net /doc/NMath/Stats/user/stats10.html   (267 words)

DSE TMA03a hypothesis which implies that the variable of extroversion is negatively correlated with the variable of altruism. was then utilised in a Spearmans rank correlation coefficient to investigate the link between personality types and altruism. 'there will be no significant correlation between extroversion questionnaire scores and altruism questionnaire scores'. hometown.aol.co.uk /john51richards/DSE202_TMa03a.html   (1046 words)

Spearmans Rank Correlation Coefficient in Coursework The spearman value is used when a graph is not roughly linear or elliptical (as opposed to PMCC when it is roughly linear or elliptical.) It can be used to show if there is or isn't correlation between two sets of values, eg: age of a car and price. This will show that you should accept H0 or H1, which ever is this case and then you can talk about this shows hows there is rank correltion or isn't what ever you stated in your hypothesis'. The value r or the correlation co-efficient will give you a value for how strongly the ranks of the two data sets x and y, you are looking at, correlate with each other. www.thestudentroom.co.uk /t23096.html   (765 words)

data.html These correlations may have been due to chance however and so you need to statistically test them, I suggest using standard deviation and especially spearmans rank correlation coefficient with a 95% level of confidence. You are now in a position to answer your hypothesis. You will have anomalous points and at first there may appear to be no correlation but when you start to consider if there were any changes in geology correlations may become apparent. www.personal.leeds.ac.uk /~geo3rss/data.html   (470 words)

Some Standart Hypothesis Tests Alternative measures of association are Spearmans's rank correlation coeffcient or Kendall's tau coefficient. If the assumed association is linear a test can be based on Pearson's correlation coefficient r. A famous example is Pearson's application of the test to Gregor Mendels genetic experiments. www.math.uprm.edu /~wrolke/esma5015/hyp2.htm   (1371 words)

Download WebCab Probability and Stat J2SE Ed at WinSW We cover linear (Spearmans, t-test, z-transform) and rank (Spearmans, Kendalls) correlation, linear regression and conditional means. Offers functionality from Basic Statistics, Discrete Probability, Standard Probability Distributions, Hypothesis Testing, Correlation and Linear Regression. Correlation and Regression Module Allows the user to investigate relationships between two variables. www.winsw.com /download/16289.html   (249 words)

MathsNet: A Level Statistics S3 Module Below is part of a table concerning tests of the hypothesis that a population correlation coefficient, Spearman's Coefficient, The values in the table are the minimum values which need to be reached by a sample correlation coefficient in order to be significant at the level shown, on a one-tailed test. Choose values for Sample level, Level and Type of test, and use the tables to find the critical value. www.mathsnet.net /asa2/2004/s35stables.html   (81 words)

J. Philippe Rushton's review of The g Factor - Stalking the Wild Taboo Jensen also applied Spearman’s hypothesis to East Asian-White comparisons using these same reaction time measures. From the study just mentioned, however, Jensen’s prediction is clear: One should find the reverse of Spearman’s hypothesis for Black-White differences. Arthur Jensen’s name is listed in a number of dictionaries as an "ism!" The Random House and Webster’s Unabridged Dictionaries contain the following entry: www.lrainc.com /swtaboo/stalkers/jpr_tgf.html   (81 words)

WINKS Statistics Software - Pearson's Correlation Tutorial A low p-value for this test (less than 0.05 for example) means that there is evidence to reject the null hypothesis in favor of the alternative hypothesis, or that there is a statistically significant relationship between the two variables. Related topics: Spearman's Correlation Coefficient is the non-parametric counterpart to r. Variables used : HP and WEIGHT Number of cases used: 38 Pearson's r (Correlations Coefficient) = 0.9172 R-Square = 0.8413 Test of hypothesis to determine significance of relationship: H(null): Slope = 0 or H(null): r = 0 (Pearson's) t = 13.81425 with 36 d.f. www.texasoft.com /winkpear.html   (81 words)

Contingency table analysis For a 2x2 table, the Pearson chi-square test tends to be more conservative than the exact (Fisher's) test, and the likelihood-ratio chi-square tends to be less conservative than the exact test (and thus more likely to erroneously reject the null hypothesis). The exact assumptions and null hypothesis for the Pearson chi-square test for independence depend on the sampling scheme used, although the calculated statistic is the same in each case. Among measures of association for two-way contingency tables, Kendall's Tau B, Tau C, Spearman's rho, and Gamma assume that both the row and column variables have ordered categories (such as disease severity categories). www.thebestisbarelygoodenough.com /StatGuide/conting_anal.htm   (81 words)

WINKS Statistics Software - Pearson's Correlation Tutorial A low p-value for this test (less than 0.05 for example) means that there is evidence to reject the null hypothesis in favor of the alternative hypothesis, or that there is a statistically significant relationship between the two variables. Related topics: Spearman's Correlation Coefficient is the non-parametric counterpart to r. (called the coefficient of determination or r squared) can be interpreted as the proportion of variance in Y that is contained in X. Tests: The statistical significance of r is tested using a t-test. www.texasoft.com /winkpear.html   (570 words)

WINKS Statistics Software - Pearson's Correlation Tutorial Related topics: Spearman's Correlation Coefficient is the non-parametric counterpart to r. A low p-value for this test (less than 0.05 for example) means that there is evidence to reject the null hypothesis in favor of the alternative hypothesis, or that there is a statistically significant relationship between the two variables. Regression and Correlation - The Correlation Matrix procedure produces a matrix of correlations for a number of pairs of variables at a time, and includes the p-value for the test or significance of r. www.texasoft.com /winkpear.html   (570 words)

Factor Analysis Factor analysis was invented nearly 100 years ago by psychologist Charles Spearman, who hypothesized that the enormous variety of tests of mental ability--measures of mathematical skill, vocabulary, other verbal skills, artistic skills, logical reasoning ability, etc.--could all be explained by one underlying "factor" of general intelligence that he called g. That is, you accept at least tentatively the simplest hypothesis (i.e., involving the fewest factors) that is not clearly contradicted by the set of observed correlations. Matrix R55 is exactly consistent with the hypothesis of a single common factor g whose correlations with the 5 observed variables are respectively.9,.8,.7,.6, and.5. comp9.psych.cornell.edu /Darlington/factor.htm   (570 words)

TOQ-Kevin Lamb - Nyborg BR-Vol 3 No 3 Jensen’s theoretical concept of intelligence shifted from his Level I-Level II abilities to Spearman’s general factor of intelligence after re-reading Spearman’s work, especially his 1927 classic The Abilities of Man.  Conceptually the g factor provided a better, more comprehensive explanation for the racial differences in intelligence. Rushton elaborates on the evolution of his own research, taking up the gauntlet and discovering additional physical and behavioral correlates that further confirm the genetic hypothesis of the black-white gap. Although a review of behavioral genetic research on g was published in Science in 1963 (Erlenmeyer-Kimling and Jarvik 1963), it was Arthur Jensen’s Harvard Educational Review monograph (Jensen 1969) that made it no longer possible to avoid the issue in the social and behavioral sciences. www.theoccidentalquarterly.com /vol3no3/kl-nyborg.html   (570 words)

Rushton, J. Philippe (1999) The "Jensen Effect" and G Vector Analysis, Psycoloquy: 10,#44 Intelligence G Factor (3) Rushton, J. (1998) The "Jensen Effect" and the "Spearman-Jensen hypothesis" of Black- White IQ differences. Jensen's method of correlated vectors is the jewel in the crown of his 30-year research on the nature of Spearman's g. Rushton, J. (1999) Secular gains in IQ not related to the g factor and inbreeding depression unlike Black-White differences: A reply to Flynn. psycprints.ecs.soton.ac.uk /archive/00000679   (2423 words)

TOQ-Harrison Kane/Chris brand-Factor Analysis-Vol 3 No 1 It was manifest to Spearman that g did not account for all the variance in students’ scores.  Therefore, he posited a two-factor theory of intelligence.  That is, each variable may be described as involving two factors, g and a factor specific to the variable.  (Figure 1 depicts the Spearman-Holzinger model of intelligence. The null hypothesis that all scores were uncorrelated with each other was rejected, indicating the presence of an underlying general factor that could account for a substantial part of the variance in test scores. Rushton, J. P., and Skuy, M. (2000), Performance on Raven’s matrices by African and White university students in South Africa. theoccidentalquarterly.com /vol3no1/hk-factor.html   (4520 words)

Statistical methods The Spearman Rank Correlation Coefficient is used to discover the strength of a link between two sets of data. The hypothesis must be written in a clear and concise way so that other people can easily understand the aims of the investigation. Ranking is achieved by giving the ranking '1' to the biggest number in a column,'2' to the second biggest value and so on. www.zephryus.demon.co.uk /geography/resources/fieldwork/stats/spear.html   (993 words)

Page's trend test In statistics, the Page test for multiple comparisons between ordered alternatives is a generalisation of the test of the statistical significance of a correlation performed using Spearman's rank correlation coefficient. As such it is more powerful than a test such as the Friedman test that uses the data in similar ways, but tests for the alternative hypothesis that the central tendencies of the observations under the n conditions are different, without specifying their order. A test of the significance of the trend between conditions in this situation was developed by Page (1963). www.worldhistory.com /wiki/P/Page%27s-trend-test.htm   (993 words)

2003-012 The motor dysfunction of each of the four extremities correlated much more strongly with the severity of pyramidal tract damage assessed on the respective MRI reconstruction (range of correlation coefficients, 0.647 to 0.922) than with the total volume of white matter (range of correlation coefficients, - 0.458 to - 0.212; Spearman). The purpose of the present study was to test this hypothesis. The severity of pyramidal tract damage was assessed on semicoronal MRI reconstructions along anatomical landmarks of somatotopy in the precentral gyrus and the internal capsule; for comparison, the overall volume of cerebral white matter (determined by automated volumetry) served as a global measure of lesion severity. www.medizin.uni-tuebingen.de /nrad/sektion/2003-012.htm   (207 words)

PCP and the Cognitive Revolution One concrete example was research on aptitude testing and analysis stemming from Spearman's (1904) development of correlational statistics in order to analyse Galton's (1870) data on the inheritance of intelligence. This hypothesis was tested by taking an existing dataset in the literature (Cendrowska, 1987), and creating degraded versions of it by introducing random errors and irrelevant constructs with random ratings. This cyclic process of knowledge acquisition and testing through application was an attempt to replicate an essential feature of expertise, that the expert is not just a repository of knowledge but someone who uses that knowledge to be "open to experience" (Gadamer, 1972). repgrid.com /reports/PSYCH/SIM/index.html   (207 words)

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