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Journal articles on the topic 'Null hypotheses'

Author: Grafiati

Published: 4 June 2021

Last updated: 5 February 2022

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1

VALEN, L. M. VAN. "Null hypotheses and prediction." Nature 314, no. 6008 (1985): 230. http://dx.doi.org/10.1038/314230b0.

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Church, Samuel H., and Cassandra G. Extavour. "Null hypotheses for developmental evolution." Development 147, no. 8 (2020): dev178004. http://dx.doi.org/10.1242/dev.178004.

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3

Futschik, Andreas, Thomas Taus, and Sonja Zehetmayer. "An omnibus test for the global null hypothesis." Statistical Methods in Medical Research 28, no. 8 (2018): 2292–304. http://dx.doi.org/10.1177/0962280218768326.

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Global hypothesis tests are a useful tool in the context of clinical trials, genetic studies, or meta-analyses, when researchers are not interested in testing individual hypotheses, but in testing whether none of the hypotheses is false. There are several possibilities how to test the global null hypothesis when the individual null hypotheses are independent. If it is assumed that many of the individual null hypotheses are false, combination tests have been recommended to maximize power. If, however, it is assumed that only one or a few null hypotheses are false, global tests based on individu

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4

Stensrud, Mats J., Kjetil Røysland, and Pål C. Ryalen. "On null hypotheses in survival analysis." Biometrics 75, no. 4 (2019): 1276–87. http://dx.doi.org/10.1111/biom.13102.

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5

Brown, Lawrence D., and John I. Marden. "Complete Class Results for Hypothesis Testing Problems with Simple Null Hypotheses." Annals of Statistics 17, no. 1 (1989): 209–35. http://dx.doi.org/10.1214/aos/1176347012.

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6

Hwang, Yi-Ting, Hsun-Chih Kuo, Chun-Chao Wang, and Meng Feng Lee. "Estimating the number of true null hypotheses in multiple hypothesis testing." Statistics and Computing 24, no. 3 (2013): 399–416. http://dx.doi.org/10.1007/s11222-013-9377-5.

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7

Brown, Michael K., and Mark J. Gibbons. "Null models for null hypotheses in taxonomy: a test using Scyphozoa." Biological Journal of the Linnean Society 134, no. 1 (2021): 240–45. http://dx.doi.org/10.1093/biolinnean/blab070.

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Abstract Although molecular tools are becoming more important in the delineation of scyphozoan species there is, perforce, a need to substantiate new species definitions using morphological data. Access to type material is often difficult and detailed, raw morphometric data are rarely provided in older type descriptions, which makes comparisons of new with old challenging. Here, we use null models based on simple measures of central tendency to generate morphometric data sets for four species of Aurelia, three species of Chrysaora and two species of Crambionella. The results of PERMANOVA and C

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8

Good, I. J. "C420. The existence of sharp null hypotheses." Journal of Statistical Computation and Simulation 49, no. 3-4 (1994): 241–42. http://dx.doi.org/10.1080/00949659408811587.

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9

Sellke, Thomas, M. J. Bayarri та James O. Berger. "Calibration ofρValues for Testing Precise Null Hypotheses". American Statistician 55, № 1 (2001): 62–71. http://dx.doi.org/10.1198/000313001300339950.

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10

O'QUIGLEY, J., and C. E. BAUDOIN. "Null hypotheses and the misuse of statistics." Nature 316, no. 6029 (1985): 582. http://dx.doi.org/10.1038/316582d0.

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11

Shin, Jennifer J., and David Zurakowski. "Null Hypotheses, Interval Estimation, and Bayesian Analysis." Otolaryngology–Head and Neck Surgery 157, no. 6 (2017): 919–20. http://dx.doi.org/10.1177/0194599817728898.

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Hypothesis testing using a frequentist approach is the mainstay of biostatistics and forms the foundation for assessing the significance of study results. This classical method has well-understood advantages as it determines whether data are statistically improbable and provides a threshold (ie, the P value) for delineating significance. Alternative statistical approaches have been proposed, including Bayesian analysis. This technique incorporates a prior probability as to what is already known clinically with the observed data. It is important for otolaryngologists to understand the advantage

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12

Choi, Jeong-Seok. "Biostatistics for Multiple Testing." Korean Journal of Otorhinolaryngology-Head and Neck Surgery 63, no. 3 (2020): 97–100. http://dx.doi.org/10.3342/kjorl-hns.2020.00164.

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Multiple testings are instances that contain simultaneous tests for more than one hypothesis. When multiple testings are conducted at the same time, it is more likely that the null hypothesis is rejected, even if the null hypothesis is correct. If individual hypothesis decisions are based on unadjusted <i>p</i>-values, it is usually more likely that some of the true null hypotheses will be rejected. In order to solve the multiple testing problems, various studies have attempted to increase the power by taking into account the family-wise error rate or false discovery rate and stati

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13

Koford, Kenneth. "Dimensions in Congressional Voting." American Political Science Review 83, no. 3 (1989): 949–62. http://dx.doi.org/10.2307/1962068.

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While dimensional studies of congressional voting find a single, ideological dimension, regression estimates find several constituency and party dimensions in addition to ideology. I rescale several unidimensional studies to show their increased classification success over the null hypothesis that votes are not unidimensional. Several null hypotheses are explored. With these null hypotheses, 66%–75% of nonunidimensional roll call votes are nevertheless correctly classified by one dimension. After the rescaling, one dimension succeeds in correctly classifying 25%–50% of the votes, and second an

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14

Gilinsky, Norman L., and Richard K. Bambach. "The evolutionary bootstrap: a new approach to the study of taxonomic diversity." Paleobiology 12, no. 3 (1986): 251–68. http://dx.doi.org/10.1017/s0094837300013762.

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The evolutionary bootstrap is a new approach to the analysis of patterns of taxonomic diversity. In general, the evolutionary bootstrap works by surveying the diversity history of a taxon, learning its dynamic properties, and then generating randomly large numbers of artificial diversity histories based upon what was learned. The distribution of artificial—or bootstrapped—diversity histories approximates the distribution of diversity histories that were possible for taxa with the dynamic properties of the real taxon, and serves as a paleontological null hypothesis for studying statistically th

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15

Serlin, Ronald C. "Answering Two Criticisms of Hypothesis Testing: A Comment." Psychological Reports 87, no. 2 (2000): 579–81. http://dx.doi.org/10.2466/pr0.2000.87.2.579.

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In a recent article, Leventhal (1999) responds to two criticisms of hypothesis testing by showing that the one-tailed test and the directional two-tailed test are valid, even if all point null hypotheses are false and that hypothesis tests can provide the probability of decisions being correct which are based on the tests. Unfortunately, the falseness of all point null hypotheses affects the operating characteristics of the directional two-tailed test, seeming to weaken certain of Leventhal's arguments in favor of this procedure.

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16

Chow, Siu L. "The null-hypothesis significance-test procedure is still warranted." Behavioral and Brain Sciences 21, no. 2 (1998): 228–35. http://dx.doi.org/10.1017/s0140525x98591169.

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Entertaining diverse assumptions about empirical research, commentators give a wide range of verdicts on the NHSTP defence in Statistical significance. The null-hypothesis significance-test procedure (NHSTP) is defended in a framework in which deductive and inductive rules are deployed in theory corroboration in the spirit of Popper's Conjectures and refutations (1968b). The defensible hypothetico-deductive structure of the framework is used to make explicit the distinctions between (1) substantive and statistical hypotheses, (2) statistical alternative and conceptual alternative hypotheses, a

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17

Okubo, Akane, Yuki Higuchi, and Kazuhiro Takeyasu. "Hypothesis Testing for the Questionnaire Investigation on Tourists’ Behavior." International Business Research 10, no. 12 (2017): 68. http://dx.doi.org/10.5539/ibr.v10n12p68.

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Tourists from abroad are increasing rapidly in Japan. Kawazu town in Izu Peninsula is famous for its cherry trees. In the cherry blossom season, many tourists visit this town. The Kawazu Cherry Blossom Festival was carried out in February 2015. Our research investigation was performed during that period. In this paper, a questionnaire investigation is executed in order to clarify tourists’ behavior, and to seek the possibility of developing regional collaboration among local government, tourism related industry and visitors. Hypothesis testing was executed based on that. We have set 10 Null hy

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18

Leventhal, Les. "Answering Two Criticisms of Hypothesis Testing." Psychological Reports 85, no. 1 (1999): 3–18. http://dx.doi.org/10.2466/pr0.1999.85.1.3.

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Two generations of methodologists have criticized hypothesis testing by claiming that most point null hypotheses are false and that hypothesis tests do not provide the probability that the null hypothesis is true. These criticisms are answered. (1) The point-null criticism, if correct, undermines only the traditional two-tailed test, not the one-tailed test or the little-known directional two-tailed test. The directional two-tailed test is the only hypothesis test that, properly used, provides for deciding the direction of a parameter, that is, deciding whether a parameter is positive or negat

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19

Poisson, Laila M., and Debashis Ghosh. "Statistical Issues and Analyses of in vivo and in vitro Genomic Data in order to Identify Clinically Relevant Profiles." Cancer Informatics 3 (January 2007): 117693510700300. http://dx.doi.org/10.1177/117693510700300008.

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In vitro experimentation provides a convenient controlled environment for testing biological hypotheses of functional genomics in cancer induction and progression. However, it is necessary to validate resulting gene signatures from these in vitro experiments in human tumor samples (i.e. in vivo). We discuss the several methods for integrating data from these two sources paying particular attention to formulating statistical tests and corresponding null hypotheses. We propose a classification null hypothesis that can be simply modeled via permutation testing. A classification method is proposed

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20

De LAND, PAUL N., and WALTER Wm CHASE. "Entry III.A: Statistical Hypotheses, Null vs. Alternative; Entry III.B; Statistical vs. Research Hypothesis." Optometry and Vision Science 68, no. 7 (1991): 565–68. http://dx.doi.org/10.1097/00006324-199107000-00011.

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21

Sampath, S., and L. Pephine Renitta. "Chance Hypotheses Testing." International Journal of Fuzzy System Applications 5, no. 3 (2016): 77–108. http://dx.doi.org/10.4018/ijfsa.2016070105.

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This paper considers the problem of testing hypotheses about hybrid distributions which are models representing situations where impreciseness (explained through fuzzy measure) and randomness (explained through probability measure) coexist. A criterion similar to the Neyman-Pearson criterion is proposed for testing a simple chance null hypothesis against a simple chance alternative hypothesis. The suggested criterion has been applied for testing hypotheses about hybrid triangular Bernoulli distribution and hybrid Poisson distribution. Optimal properties of the resulting tests have also been in

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22

Zumbo, Bruno D. "A viable alternative to null-hypothesis testing." Behavioral and Brain Sciences 21, no. 2 (1998): 227–28. http://dx.doi.org/10.1017/s0140525x98581162.

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This commentary advocates an alternative to null-hypothesis testing that was originally represented by Rozeboom over three decades ago yet is not considered by Chow (1996). The central distinguishing feature of this approach is that it allows the scientist to conclude that the data are much better fit by those hypotheses whose values fall inside the interval than by those outside.

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23

Page, Roderic D. M. "Random Dendrograms and Null Hypotheses in Cladistic Biogeography." Systematic Zoology 40, no. 1 (1991): 54. http://dx.doi.org/10.2307/2992221.

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24

Ghosh, Abhik, and Ayanendranath Basu. "Testing composite null hypotheses based on S-divergences." Statistics & Probability Letters 114 (July 2016): 38–47. http://dx.doi.org/10.1016/j.spl.2016.02.007.

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25

Morey, Richard D., and Jeffrey N. Rouder. "Bayes factor approaches for testing interval null hypotheses." Psychological Methods 16, no. 4 (2011): 406–19. http://dx.doi.org/10.1037/a0024377.

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26

Maris, Gunter. "Posterior predictive p-values for classical null hypotheses." Statistica Neerlandica 59, no. 1 (2005): 70–81. http://dx.doi.org/10.1111/j.1467-9574.2005.00280.x.

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27

Page, R. D. M. "Random Dendrograms and Null Hypotheses in Cladistic Biogeography." Systematic Biology 40, no. 1 (1991): 54–62. http://dx.doi.org/10.1093/sysbio/40.1.54.

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28

W. Goodall, David. "Environmental Management: the Precautionary Principle and Null Hypotheses." Pacific Conservation Biology 5, no. 2 (1999): 78. http://dx.doi.org/10.1071/pc990078.

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A recent paper (Calver et al. 1999) exemplifies an approach to environmental problems which, though common, is often inappropriate, and may indeed be counterproductive in confrontational situations. An examination seems called for.

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29

Shrout, Patrick E. "Should Significance Tests be Banned? Introduction to a Special Section Exploring the Pros and Cons." Psychological Science 8, no. 1 (1997): 1–2. http://dx.doi.org/10.1111/j.1467-9280.1997.tb00533.x.

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Significance testing of null hypotheses is the standard epistemological method for advancing scientific knowledge in psychology, even though it has drawbacks and it leads to common inferential mistakes These mistakes include accepting the null hypothesis when it fails to be rejected, automatically interpreting rejected null hypotheses as theoretically meaningful, and failing to consider the likelihood of Type II errors Although these mistakes have been discussed repeatedly for decades, there is no evidence that the academic discussion has had an impact A group of methodologists is proposing a

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30

Ge, Yongchao, and Xiaochun Li. "Control of the False Discovery Proportion for Independently Tested Null Hypotheses." Journal of Probability and Statistics 2012 (2012): 1–19. http://dx.doi.org/10.1155/2012/320425.

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Consider the multiple testing problem of testingmnull hypothesesH1,…,Hm, among whichm0hypotheses are truly null. Given theP-values for each hypothesis, the question of interest is how to combine theP-values to find out which hypotheses are false nulls and possibly to make a statistical inference onm0. Benjamini and Hochberg proposed a classical procedure that can control the false discovery rate (FDR). The FDR control is a little bit unsatisfactory in that it only concerns the expectation of the false discovery proportion (FDP). The control of the actual random variable FDP has recently drawn

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31

Marewski, Julian N., and Henrik Olsson. "Beyond the Null Ritual." Zeitschrift für Psychologie / Journal of Psychology 217, no. 1 (2009): 49–60. http://dx.doi.org/10.1027/0044-3409.217.1.49.

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Rituals shape many aspects of our lives, and they are no less common in scientific research than elsewhere. One that figures prominently in hypothesis testing is the null ritual, the pitting of hypotheses against chance. Although known to be problematic, this practice is still widely used. One way to resist the lure of the null ritual is to increase the precision of theories by casting them as formal models. These can be tested against each other, instead of against chance, which in turn enables a researcher to decide between competing theories based on quantitative measures. This article give

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32

Boca, Simina M., and Jeffrey T. Leek. "A direct approach to estimating false discovery rates conditional on covariates." PeerJ 6 (December 10, 2018): e6035. http://dx.doi.org/10.7717/peerj.6035.

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Modern scientific studies from many diverse areas of research abound with multiple hypothesis testing concerns. The false discovery rate (FDR) is one of the most commonly used approaches for measuring and controlling error rates when performing multiple tests. Adaptive FDRs rely on an estimate of the proportion of null hypotheses among all the hypotheses being tested. This proportion is typically estimated once for each collection of hypotheses. Here, we propose a regression framework to estimate the proportion of null hypotheses conditional on observed covariates. This may then be used as a m

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33

Yin, Yuliang, and Bingbing Wang. "The Agreement between the GeneralizedpValue and Bayesian Evidence in the One-Sided Testing Problem." International Journal of Mathematics and Mathematical Sciences 2016 (2016): 1–7. http://dx.doi.org/10.1155/2016/8656909.

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In the problem of testing one-sided hypotheses, a frequentist may measure evidence against the null hypothesis by thepvalue, while a Bayesian may measure it by the posterior probability that the null hypothesis is true. In this paper, we consider the relationship between the generalizedpvalue and the Bayesian evidence in testing one-sided hypotheses in the presence of nuisance parameters. The sufficient conditions for the agreement between these two kinds of evidence are given. Some examples are provided to show the agreement of Bayesian and frequentist evidence in many classical testing probl

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34

Thinh, Le Phuc, Michele Dall'Arno, and Valerio Scarani. "Worst-case Quantum Hypothesis Testing with Separable Measurements." Quantum 4 (September 11, 2020): 320. http://dx.doi.org/10.22331/q-2020-09-11-320.

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For any pair of quantum states (the hypotheses), the task of binary quantum hypotheses testing is to derive the tradeoff relation between the probability p01 of rejecting the null hypothesis and p10 of accepting the alternative hypothesis. The case when both hypotheses are explicitly given was solved in the pioneering work by Helstrom. Here, instead, for any given null hypothesis as a pure state, we consider the worst-case alternative hypothesis that maximizes p10 under a constraint on the distinguishability of such hypotheses. Additionally, we restrict the optimization to separable measuremen

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35

van de Schoot, Rens, and Dagmar Strohmeier. "Testing informative hypotheses in SEM increases power: An illustration contrasting classical hypothesis testing with a parametric bootstrap approach." International Journal of Behavioral Development 35, no. 2 (2011): 180–90. http://dx.doi.org/10.1177/0165025410397432.

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In the present paper, the application of a parametric bootstrap procedure, as described by van de Schoot, Hoijtink, and Deković (2010), will be applied to demonstrate that a direct test of an informative hypothesis offers more informative results compared to testing traditional null hypotheses against catch-all rivals. Also, more power can be gained when informative hypotheses are tested directly. In this paper we will (a) compare the results of traditional analyses with the results of this novel methodology; (b) introduce applied researchers to the parametric bootstrap procedure for the evalu

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36

Sohn, David. "Psychology of the Scientist: LXVI. The Idiot Savants Have Taken over the Psychology Labs! or Why in Science Using the Rejection of the Null Hypothesis as the Basis for Affirming the Research Hypothesis is Unwarranted." Psychological Reports 73, no. 3_suppl (1993): 1167–75. http://dx.doi.org/10.2466/pr0.1993.73.3f.1167.

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The fable of a group of idiot savants, who conduct methodologically flawless research to test senseless research hypotheses and are able to affirm some of them on the basis of the rejection of the null hypothesis, is used to dramatize the argument that the rejection of the null hypothesis, by itself, is not sufficient grounds for affirming the research hypothesis. Reasons and examples are given to argue that affirmation of a scientific hypothesis must be based primarily on substantive evidence that is independent of an hypothesis test.

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37

Pesaran, M. Hashem. "Global and Partial Non-Nested Hypotheses and Asymptotic Local Power." Econometric Theory 3, no. 1 (1987): 69–97. http://dx.doi.org/10.1017/s0266466600004138.

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This paper addresses two related issues in the literature of non-nested hypotheses testing. Firstly, by means of a measure of “closeness” of probability density functions, it shows how any two hypotheses can be placed into the nested and the non-nested categories with the latter category being subdivided further into “globally” and “partially” non-nested hypotheses. Secondly, by emphasizing the distinction between a “local null” and a “local alternative,” the paper shows that only in the case of partially non-nested hypotheses is it possible to specify local alternatives. In this case the pape

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38

Cayuela, Luis, Nicholas J. Gotelli, and Robert K. Colwell. "Ecological and biogeographic null hypotheses for comparing rarefaction curves." Ecological Monographs 85, no. 3 (2015): 437–55. http://dx.doi.org/10.1890/14-1261.1.

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39

Cabras, Stefano. "A note on multiple testing for composite null hypotheses." Journal of Statistical Planning and Inference 140, no. 3 (2010): 659–66. http://dx.doi.org/10.1016/j.jspi.2009.08.010.

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40

Delampady, Mohan. "Lower Bounds on Bayes Factors for Interval Null Hypotheses." Journal of the American Statistical Association 84, no. 405 (1989): 120–24. http://dx.doi.org/10.1080/01621459.1989.10478746.

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41

Sun, Wenguang, and Alexander C. McLain. "Multiple Testing of Composite Null Hypotheses in Heteroscedastic Models." Journal of the American Statistical Association 107, no. 498 (2012): 673–87. http://dx.doi.org/10.1080/01621459.2012.664505.

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42

Yin, Yuliang. "A new Bayesian procedure for testing point null hypotheses." Computational Statistics 27, no. 2 (2011): 237–49. http://dx.doi.org/10.1007/s00180-011-0252-6.

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43

Patriota, Alexandre G. "A classical measure of evidence for general null hypotheses." Fuzzy Sets and Systems 233 (December 2013): 74–88. http://dx.doi.org/10.1016/j.fss.2013.03.007.

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44

B.E., Uwameiye. "SOME SELECTED FACTORS AFFECTING EATING BEHAVIOR OF ADOLESCENT: IMPLICATION FOR HOME ECONOMICS." International Journal of Research -GRANTHAALAYAH 6, no. 12 (2018): 1–11. http://dx.doi.org/10.29121/granthaalayah.v6.i12.2018.1069.

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This research identified some selected factors affecting the eating behavior of adolescent in Esan West Local Government Area. Four questions and four null hypotheses guided the study. A total of 679 students were utilized. A 30-item questionnaire was the instrument for gathering the data. Mean, standard deviations answered the research questions, while the t-test was utilized for testing the null hypotheses at.05 level of significance. Findings revealed among others that the respondents have poor eating behavior such as skipping of breakfast among urban and rural respondents (1.06, 1.02), low

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45

Lee, Tze-San. "The Bayes Factor for the Misclassified Categorical Data." International Journal of Statistics and Probability 7, no. 4 (2018): 91. http://dx.doi.org/10.5539/ijsp.v7n4p91.

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This article addresses the issue of misclassification in a single categorical variable, that is, how to test whether the collected categorical data are misclassified. To tackle this issue, a pair of null and alternative hypotheses is proposed. A mixed Bayesian approach is taken to test these hypotheses. Specifically, a bias-adjusted cell proportion estimator is presented that accounts for the bias caused by classification errors in the observed categorical data. The chi-square test is then adjusted accordingly. To test the null hypothesis that the data are not misclassified under a specified m

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46

Shaldehi, Ahmad Hedayatpanah, Mohammad Saeed Hedayatpanah Shaldehi, and Marziyeh Hedayatpanah Shaldehi. "Comparative Analysis of Similarities and Differences between Null Hypotheses, Assumption of Breach." Indian Journal of Advanced Mathematics 1, no. 2 (2021): 20–26. http://dx.doi.org/10.35940/ijam.b1110.101221.

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The main purpose of this paper is to comparatively study the similarities and differences between of the , null hypothesis and assumption of breach .The null hypothesis , in applied researches, particularly experiments for confirm or rejection .a hypothesis, regard to inferential statistics That used in many different fields of humanities researchers, particularly psychology, education, management and sociological placed assumption of breach, to prove geometric proposition( theorems), which hypothetical temporary, that with the help of reasoning, the false statements, it we conclude. Such a st

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47

Holmberg, Anders. "Is There a Little Pro? Evidence from Finnish." Linguistic Inquiry 36, no. 4 (2005): 533–64. http://dx.doi.org/10.1162/002438905774464322.

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The traditional view of the null subject as pro identified by Agr (the φ-features of I) cannot be maintained in a theory where Agr is uninterpretable. Two hypotheses are compared with regard to the predictions they make for Finnish null subject constructions: (A) Agr is interpretable in null subject languages, and pro is therefore redundant; (B) null subjects are specified but unpronounced pronouns that assign values to the uninterpretable features of Agr. Since Finnish observes the Extended Projection Principle and has an expletive pronoun, Hypothesis A predicts that null subjects should cooc

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48

Higuchi, Yuki, Akane Okubo, Daisuke Suzuki, and Kazuhiro Takeyasu. "Hypothesis Testing for the Questionnaire Investigation on the Needs at Fuji City." International Business Research 11, no. 6 (2018): 139. http://dx.doi.org/10.5539/ibr.v11n6p139.

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Shopping streets at local city in Japan became old and are generally declining. In this paper, we handle the area rebirth and/or regional revitalization of shopping street. We focus on Fuji city in Japan. Four big festivals are held at Fuji city. Many people visit these festivals including residents in that area. Therefore a questionnaire investigation to the residents and visitors is conducted during these periods in order to clarify residents and visitors’ needs for the shopping street and utilize them to the plan building of the area rebirth and/or regional revitalization of shopping street

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49

Morey, Richard D., Saskia Homer, and Travis Proulx. "Beyond Statistics: Accepting the Null Hypothesis in Mature Sciences." Advances in Methods and Practices in Psychological Science 1, no. 2 (2018): 245–58. http://dx.doi.org/10.1177/2515245918776023.

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Scientific theories explain phenomena using simplifying assumptions—for instance, that the speed of light does not depend on the direction in which the light is moving, or that the shape of a pea plant’s seeds depends on a small number of alleles randomly obtained from its parents. These simplifying assumptions often take the form of statistical null hypotheses; hence, supporting these simplifying assumptions with statistical evidence is crucial to scientific progress, though it might involve “accepting” a null hypothesis. We review two historical examples in which statistical evidence was use

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50

Schumm, Walter R. "Statistical Requirements for Properly Investigating a Null Hypothesis." Psychological Reports 107, no. 3 (2010): 953–71. http://dx.doi.org/10.2466/02.03.17.21.pr0.107.6.953-971.

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Issues involved in the evaluation of null hypotheses are discussed. The use of equivalence testing is recommended as a possible alternative to the use of simple t or F tests for evaluating a null hypothesis. When statistical power is low and larger sample sizes are not available or practical, consideration should be given to using one-tailed tests or less conservative levels for determining criterion levels of statistical significance. Effect sizes should always be reported along with significance levels, as both are needed to understand results of research. Probabilities alone are not enough

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