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Topic: Significance test

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	Fisher's exact test - Wikipedia, the free encyclopedia
		Fisher's exact test is a statistical significance test used in the analysis of categorical data where sample sizes are small.
		The test is used to examine the significance of the association between two variables in a 2 x 2 contingency table.
		Because the calculation of Fisher’s exact test involves permuting the observed cell frequencies it is referred to as a permutation test, one of a broad class of such tests.
	en.wikipedia.org /wiki/Fisher's_exact_test (842 words)

	Statistical significance - Wikipedia, the free encyclopedia
		Technically, in traditional frequentist statistical hypothesis testing, the significance level of a test is the maximum probability that the observed statistic would be observed under the null hypothesis that is considered consistent with chance variation, and therefore with the truth of null hypothesis.
		The significance of a result is also called its p-value; the smaller the p-value, the more significant the result is said to be.
		However a test at the 1% level is more likely to fail to reject a false null hypothesis (a Type II error) than a test at the 5% level, and so will have less statistical power.
	en.wikipedia.org /wiki/Significance_test (830 words)

	Statistical Significance
		In contrast the high significance level for type of vehicle (.001 or 99.9%) indicates there is almost certainly a true difference in purchases of Brand X by owners of different vehicles in the population from which the sample was drawn.
		If your sample is not truly random, a significance test may overstate the accuracy of the results, because it only considers random error.
		While this logic passes the common sense test, the mathematics behind statistical significance do not actually guarantee that 1-p gives the exact probability that there is a difference is the population.
	www.surveysystem.com /signif.htm (1299 words)

	Tests of Significance (Site not responding. Last check: 2007-10-24)
		The test statistic z is used to compute the P-value for the standard normal distribution, the probability that a value at least as extreme as the test statistic would be observed under the null hypothesis.
		In the test score example, for a fixed significance level of 0.10, suppose the school board wishes to be able to reject the null hypothesis (that the mean = 70) if the mean for female students is in fact 72.
		The test statistic z is used to compute the P-value for the t distribution, the probability that a value at least as extreme as the test statistic would be observed under the null hypothesis.
	www.stat.yale.edu /Courses/1997-98/101/sigtest.htm (2643 words)

	Significance Test (Site not responding. Last check: 2007-10-24)
		In this table and the next two, asterisks indicate the results of the chi-square significance tests.
		These significance tests measure the likelihood that the association between the independent and dependent variables is caused by chance.
		Thus, when the chi-square is less than.05, we can be confident in rejecting the possibility that no association exists between the independent and dependent variables.
	chnm.gmu.edu /survey/chi.html (86 words)

	Statistics Glossary - hypothesis testing
		The critical value(s) for a hypothesis test is a threshold to which the value of the test statistic in a sample is compared to determine whether or not the null hypothesis is rejected.
		The choice between a one-sided and a two-sided test is determined by the purpose of the investigation or prior reasons for using a one-sided test.
		The choice between a one-sided test and a two-sided test is determined by the purpose of the investigation or prior reasons for using a one-sided test.
	www.stats.gla.ac.uk /steps/glossary/hypothesis_testing.html (2225 words)

	PA 765: Univariate GLM, ANOVA, and ANCOVA
		For instance, performance test might be the interval dependent variable, noise distraction might be the within-subjects repeated factor (measure) administered to all subjects in a counterbalanced sequence, and the between-subjects factor might be mode of testing (ex., having a pen-and-paper test group and a computer-tested group).
		Planned comparisons with the t-test: The t-test is a test of significance of the difference in the means of a single interval dependent, for the case of two groups formed by a categorical independent.
		Consequently, where the t test tests the difference between two means, the q-statistic tests the probability that the largest mean and smallest mean among the k groups formed by the categories of the independent(s) were sampled from the same population.
	www2.chass.ncsu.edu /garson/pa765/anova.htm (15037 words)

	Significance Test -- Market System Analyzer
		Significance testing can be a powerful tool to aid in the development and testing of trading systems and methods.
		With regard to trading, a significance test can be used to help determine if a trading system or method is likely to be profitable in the future.
		Significance testing can also be used to detect curve-fit or over-optimized trading systems.
	www.adaptrade.com /sigtest.htm (684 words)

	PA 765: Chi-Square Significance Tests
		Significance testing, of which chi-square tests are a type, is also treated in a separate section.
		Note that chi square is more likely to establish significance to the extent that (1) the relationship is strong, (2) the sample size is large, and/or (3) the number of values of the two associated variables is large.
		If found significant, the interpretation is that increases in one variable are associated with increases (or decreases for negative relationships) in the other greater than would be expected by chance of random sampling.
	www2.chass.ncsu.edu /garson/pa765/chisq.htm (1591 words)

	Statistical Significance
		Significance is a statistical term that tells how sure you are that a difference or relationship exists.
		In these situations, the word "significant" is used to advise a client to take note of a particular difference or relationship because it may be relevant to the company's strategic plan.
		One important concept in significance testing is whether you use a one-tailed or two-tailed test of significance.
	www.statpac.com /surveys/statistical-significance.htm (894 words)

	SIGTEST
		Consequently, the use of the significance test should be assessed with reference to the rationale of scientific investigation that is at a level of abstraction different from that of statistics.
		That is, that the significance test may sometimes be misused in an insufficient reason to abandon the method.
		Some early criticisms of the use of the significance test have been responded to by (a) distinguishing between a statistical alternative hypothesis and a theoretical rival hypothesis and (b) showing that the binary statistical decision is compatible with the incremental growth of scientific knowledge.
	uregina.ca /~chowsl/pub_papers/SIGTEST.htm (5396 words)

	The significance test as randomization test
		Recent interpretations of the significance test do not focus on it as a means to infer to an underlying population - at least not in experimental contexts.
		In randomization tests, the critical random process is not to draw a random sample from an underlying population distribution, but rather to randomly assign subjects (or stimuli) to experimental conditions.
		According to this rationale, a randomization test informs about the probability of the empirical data (in terms of differences in central tendencies), under the assumption that they are exclusively the result of the random assignment procedure, that is, chance.
	www.dgps.de /fachgruppen/methoden/mpr-online/issue3/art11/node2.html (579 words)

	Module 28: CHOOSING A SIGNIFICANCE TEST: International Development Research Centre
		In other words, a significance test is used to find out whether a study result, which is observed in a sample can be considered as a result which indeed exists in the study population from which the sample was drawn.
		The reasoning behind significance tests is the same, no matter whether a researcher is comparing two groups for differences or whether (s)he is measuring two variables to detect possible associations.
		Once it is clear to everybody why significance tests are performed, you might ask participants to give examples of results (cross-tables) from their own projects for which significance tests have to be performed.
	www.idrc.ca /en/ev-56462-201-1-DO_TOPIC.html (3662 words)

	Test Result Significance
		I had an additional function test for kidney and liver done in late Dec. and my alkaline phosphatase is now 160.
		My GP says he wants to repeat this test and do a more extensive test to see where this is originating from in 4 weeks, but is not concerned that anything serious is going on.
		Further testing can include an abdominal ultrasound to evaluate the liver and gallbladder, or a bone scan to evaluate for any bony pathology.
	www.medhelp.org /forums/FamilyPractice/messages/690.html (333 words)

	T-test online. Compare two means, two proportions or counts online.
		In one-sided tests it is assumed that before doing the test you had a hypothesis that one mean of the two means was bigger than the other mean, i.e.
		The double sided significance test according to the method of small p's and the notation >= gives the exact probability of the difference between the expected and the observed value or any larger difference, considering the location of the expected and the observed value.
		The Chi-squares tests give only an estimate of the true Chi-square and associated probability value, an estimate which might not be very good in the case of the margins being very uneven or with a small value (~less than five) in one of the cells.
	home.clara.net /sisa/t-thlp.htm (3209 words)

	A sensible alternative to a null-hypothesis test:
		The introduction of hypothesis testing did lead to an attempt to reformulate the significance test as a test of a point null hypothesis against all possible alternatives.
		A common formulation for the conventional test-of-hypothesis version of the test of significance is the traditional test for the equality of two population means, using Student’s t distribution.
		Note that those accustomed to make "tests of hypotheses" at.05 would, using the procedures set forth here, do the same arithmetic but would describe their results as a "test of significance" at one-half of.05, i.e., at.025.
	forrest.psych.unc.edu /jones-tukey112399.html (1741 words)

	Significance Testing online. For z-score, t-test, f-test, correlation and chi-square distribution
		Significance is designed to provide help for people who calculate statistical procedures by hand or to be used in case your statistical program gives you parameter values but not the statistical significance of the parameter.
		The procedure to approximate the significance of the t-value is based on algorithm '03' from Applied Statistics (1968).
		The significance of the correlation coefficient is calculated by using a single sided t-test, following Cohen.
	home.clara.net /sisa/signhlp.htm (595 words)

	Cogprints - The null-hypothesis significance-test procedure is still warranted (Site not responding. Last check: 2007-10-24)
		Bakan, D. The test of significance in psychological research.
		Neyman, J., and Pearson, E. On the use and interpretation of certain test criteria for purposes of statistical inferences (Part I).
		Schmidt, F. Statistical significance testing and cumulative knowledge in psychology: Implications for the training of researchers.
	cogprints.org /837 (1142 words)

	New Page (Site not responding. Last check: 2007-10-24)
		Significance testing for the "title" type sample sets will be described further on in section 2.
		Please note that the null hypothesis, and the significance test derived from it, took no part in the considerations which guided us in the definition of the calibrated proximity index and the general convergence tendency, upon which their statistical significance is based.
		Please note, that also in the case of the null hypothesis, and the significance test derived from it, we make no use of the considerations which guided us in defining the calibrated proximity measure and the general proximity tendency, upon which their statistical significance is based.
	members.cox.net /mkarep/WRR3.htm (7733 words)

	Improved significance test for DNA microarray data: temporal effects of shear stress on endothelial genes -- Zhao et ...
		Improved significance test for DNA microarray data: temporal effects of shear stress on endothelial genes -- Zhao et al.
		Improved significance test for DNA microarray data: temporal effects of shear stress on endothelial genes
		The proportion of genes tested positive that are truly positive (PPV) increases as the sensitivity of the test increases, when the specificity of the test is fixed.
	physiolgenomics.physiology.org /cgi/content/full/12/1/1 (5710 words)

	Marks Nester's References and Quotes
		I (i.e., Nester) contend that the general acceptance of statistical hypothesis testing is one of the most unfortunate aspects of 20th century applied science.
		Tests for the identity of population distributions, for equality of treatment means, for presence of interactions, for the nullity of a correlation coefficient, and so on, have been responsible for much bad science, much lazy science, and much silly science.
		in many cases, instead of the tests of significance it would be more to the point to measure the magnitudes of the relationships, attaching proper statements of their sampling variation.
	www.warnercnr.colostate.edu /~anderson/nester.html (4975 words)

	Significance Test
		Reject Ho According to a 2001 study conducted by the Department of Water – City of Chicago, “the average pH in the Chicago district waters is at 8.20.” I performed a significance test to determine if the population pH value in 1997 was higher than the 2001 average level.
		The null hypothesis is that there is no significant difference between the pH in 1997 versus the pH in 2001.
		In other words, there is a significant difference between the pH in 1997 and the pH in 2001.
	shrike.depaul.edu /~mapel1/page5.htm (143 words)

	Statistical Test (from Internet Glossary of Statistical Terms)
		A statistical test is a procedure for deciding whether an assertion (e.g.
		We test an hypothesis of this sort by drawing a random sample from the population in question and calculating an appropriate statistic on its items.
		Finally, it is noteworthy that the appropriate conduct of any statistical test invariably requires many thoughtful decisions.
	www.animatedsoftware.com /statglos/sgsttest.htm (204 words)

	Citebase - Significance Test or Effect Size?
		I describe and question the argument that in psychological research, the significance test should be replaced (or, at least, supplemented) by a more informative index (viz., effect size or statistical power) in the case of theory-corroboration experimentation because it has been made on the basis of some debatable assumptions about the rationale of scientific investigation.
		This binary decision supplies the minor premise for the syllogism implicated when a theory is being tested.
		Some metatheoretical considerations reveal that the magnitude of the effect-size estimate is not a satisfactory alternative to the significance test.
	citebase.org /cgi-bin/citations?archiveID=oai:cogprints.soton.ac.uk:824 (172 words)

	The Reasoning of a Statistical Test (Site not responding. Last check: 2007-10-24)
		A statistical test assesses the evidence provided by data against some claim (the null hypothesis H
		This applet allows you to gather data until you are ready to reach a conclusion about the truth of a null hypothesis.
		It illustrates the reasoning of tests: are the data compatible with a claim, or do they give evidence against it?
	bcs.whfreeman.com /bps3e/content/cat_010/applets/testsignificance.html (165 words)

	Significance Test (Site not responding. Last check: 2007-10-24)
		The chi-square significance test in the far-right column measures the likelihood that the observed association between the independent variable (e.g.,'age') and the dependent variable (e.g., 'participation in the given activity') is caused by chance.
		As the chi-square increases above.05 the likelihood that the observed association occurred by chance increases.
		NS indicates that the chi-square is not significant using the.05 threshold.
	chnm.gmu.edu /survey/sig.html (85 words)

	StatSci-Equidistant Letter Sequences in the Book of Genesis
		To test whether the ELS's in a given text may contain "hidden information," we write the text in the form of two-dimensional arrays, and define the distance between ELS's according to the ordinary two-dimensional Euclidean metric.
		We test the significance of the phenomenon on samples of pairs of related words (such as hammer-anvil and Zedekia-Matanya).
		In order to avoid any conceivable appearance of having fitted the tests to the data, it was later decided to use a fresh sample, without changing anything else.
	www.torahcodes.co.il /wrr1/wrr1.htm (5148 words)

	Significance test (1 of 2) (Site not responding. Last check: 2007-10-24)
		A significance test is performed to determine if an observed value of a statistic differs enough from a hypothesized value of a parameter to draw the inference that the hypothesized value of the parameter is not the true value.
		The hypothesized value of the parameter is called the "null hypothesis." A significance test consists of calculating the probability of obtaining a statistic as different or more different from the null hypothesis (given that the null hypothesis is correct) than the statistic obtained in the sample.
		Suppose the mean running time for the large reward were 1.5 seconds and the mean running time for the small reward were 2.1 seconds.
	davidmlane.com /hyperstat/A6642.html (187 words)

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