Journal articles: 'Statistical hypotheses testing'

1

Lehmann, E. L. "Testing Statistical Hypotheses." Biometrics 53, no. 4 (December 1997): 1563. http://dx.doi.org/10.2307/2533531.

Full text

APA, Harvard, Vancouver, ISO, and other styles

2

Neath, Andrew A. "Testing Statistical Hypotheses." Journal of the American Statistical Association 101, no. 474 (June 1, 2006): 847–48. http://dx.doi.org/10.1198/jasa.2006.s100.

Full text

APA, Harvard, Vancouver, ISO, and other styles

3

Ziegel, Eric. "Testing Statistical Hypotheses." Technometrics 29, no. 4 (November 1987): 494. http://dx.doi.org/10.1080/00401706.1987.10488294.

Full text

APA, Harvard, Vancouver, ISO, and other styles

4

Mukerjee, Hari, and E. L. Lehmann. "Testing Statistical Hypotheses." Journal of the American Statistical Association 82, no. 400 (December 1987): 1192. http://dx.doi.org/10.2307/2289421.

Full text

APA, Harvard, Vancouver, ISO, and other styles

5

Biggins, J. D., and E. L. Lehmann. "Testing Statistical Hypotheses." Journal of the Royal Statistical Society. Series A (Statistics in Society) 151, no. 1 (1988): 231. http://dx.doi.org/10.2307/2982206.

Full text

APA, Harvard, Vancouver, ISO, and other styles

6

K. Sharma, Narendra. "Hypothesis Statement and Statistical Testing: A Tutorial." BOHR International Journal of Operations Management Research and Practices 1, no. 1 (2022): 52–58. http://dx.doi.org/10.54646/bijomrp.007.

Full text

Abstract:

Many researchers and beginners in social research have several dilemmas and confusion in their mind about hypothesis statement and statistical testing of hypotheses. A distinction between the research hypothesis and statistical hypotheses, and understanding the limitations of the historically used null hypothesis statistical testing, is useful in clarifying these doubts. This article presents some data from the published research articles to support the view that the is format as well as the will format is appropriate to stating hypotheses. The article presents a social research framework to present the research hypothesis and statistical hypotheses is proper perspective.

APA, Harvard, Vancouver, ISO, and other styles

7

Lazar, Nicole. "Testing Statistical Hypotheses of Equivalence." Technometrics 45, no. 3 (August 2003): 271–72. http://dx.doi.org/10.1198/tech.2003.s775.

Full text

APA, Harvard, Vancouver, ISO, and other styles

8

Munk, Axel. "Testing Statistical Hypotheses of Equivalence." Journal of the American Statistical Association 99, no. 465 (March 2004): 293. http://dx.doi.org/10.1198/jasa.2004.s317.

Full text

APA, Harvard, Vancouver, ISO, and other styles

9

Meeden, Glen, W. C. M. Kallenberg, J. Beirlant, P. Van Blokland, J. J. Dik, P. J. M. M. Does, A. J. Van Es, et al. "Testing Statistical Hypotheses: Worked Solutions." Journal of the American Statistical Association 81, no. 395 (September 1986): 860. http://dx.doi.org/10.2307/2289027.

Full text

APA, Harvard, Vancouver, ISO, and other styles

10

COUSENS, ROGER, and CHARLES MARSHALL. "Dangers in testing statistical hypotheses." Annals of Applied Biology 111, no. 2 (October 1987): 469–76. http://dx.doi.org/10.1111/j.1744-7348.1987.tb01476.x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

11

Hormozinejad, Farshin. "Optimal testing of statistical hypotheses and multiple familywise error rates." Filomat 30, no. 3 (2016): 681–88. http://dx.doi.org/10.2298/fil1603681h.

Full text

Abstract:

In this article the author considers the statistical hypotheses testing to make decision among hypotheses concerning many families of probability distributions. The statistician would like to control the overall error rate relative to draw statistically valid conclusions from each test, while being as efficient as possible. The familywise error (FWE) rate metric and the hypothesis test procedure while controlling both the type I and II FWEs are generalized. The proposed procedure shows simultaneous more reliability and less conservative error control relative to fixed sample and other recently proposed sequential procedures. Also, the characteristics of logarithmically asymptotically optimal (LAO) hypotheses testing are studied. The purpose of research is to express the optimal functional relation among the reliabilities of LAO hypotheses testing and to judge with FWE metric.

APA, Harvard, Vancouver, ISO, and other styles

12

Grzegorzewski, Przemysław. "Testing statistical hypotheses with vague data." Fuzzy Sets and Systems 112, no. 3 (June 2000): 501–10. http://dx.doi.org/10.1016/s0165-0114(98)00061-x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Wu, Hsien-Chung. "Statistical hypotheses testing for fuzzy data." Information Sciences 175, no. 1-2 (September 2005): 30–56. http://dx.doi.org/10.1016/j.ins.2003.12.009.

Full text

APA, Harvard, Vancouver, ISO, and other styles

14

Darkhovskii, B. S. "Sequential testing of two composite statistical hypotheses." Automation and Remote Control 67, no. 9 (September 2006): 1485–99. http://dx.doi.org/10.1134/s0005117906090104.

Full text

APA, Harvard, Vancouver, ISO, and other styles

15

Morris, Richard W. "Testing Statistical Hypotheses about Rat Liver Foci." Toxicologic Pathology 17, no. 4_part_1 (April 1989): 569–78. http://dx.doi.org/10.1177/0192623389017004103.

Full text

Abstract:

Tests of statistical hypotheses concerning treatment effect on the development of hepatocellular foci can be carried out directly on two-dimensional observations made on histologic sections or on estimates of the density and volume of foci in three dimensions. Inferences about differences in the density or size of foci from tests based on two-dimensional observations, however, can be misleading. This is because both the number of focus cross-sections observed in a tissue section and the percent area occupied by foci can be expressed in terms of the number of foci per unit volume of liver tissue and the mean focus size. As a consequence, a treatment difference may be caused by a difference in the density of foci, their average size, or both. Of more serious concern is the possibility that failure to detect a treatment effect may occur not only when there is no treatment effect but also when the density and size of foci differ between treatments in such a way that their product is unchanged. This can happen if the effect of treatment is to increase the number of foci and decrease their average size, or vice versa. A similar difficulty of interpretation is associated with hypothesis tests based on average focus cross-section area. Tests based on estimates of the number of foci per unit volume and mean focus volume allow direct inference about the quantities of interest, but these estimates are unstable because they have large variances. Empirical estimates of statistical power for the Wilcoxon rank sum test and the t-test from data on control rats suggest power may be limited in experiments with group sizes of ten and low observed numbers of focus cross-sections. If hypothesis tests based on estimates of the density and size of foci are to form the basis for a bioassay, then the power of statistical tests used to identify treatment effects should be investigated.

APA, Harvard, Vancouver, ISO, and other styles

16

De Martini, Daniele. "Reproducibility probability estimation for testing statistical hypotheses." Statistics & Probability Letters 78, no. 9 (July 2008): 1056–61. http://dx.doi.org/10.1016/j.spl.2007.09.064.

Full text

APA, Harvard, Vancouver, ISO, and other styles

17

Akbari, Mohammad Ghasem, and Gholamreza Hesamian. "Testing statistical hypotheses for intuitionistic fuzzy data." Soft Computing 23, no. 20 (October 20, 2018): 10385–92. http://dx.doi.org/10.1007/s00500-018-3590-2.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Schall, Robert. "Book Review: Testing statistical hypotheses of equivalence." Clinical Trials: Journal of the Society for Clinical Trials 1, no. 1 (February 2004): 139–40. http://dx.doi.org/10.1191/1740774504cn012xx.

Full text

APA, Harvard, Vancouver, ISO, and other styles

19

Choi, Jeong-Seok. "Biostatistics for Multiple Testing." Korean Journal of Otorhinolaryngology-Head and Neck Surgery 63, no. 3 (March 21, 2020): 97–100. http://dx.doi.org/10.3342/kjorl-hns.2020.00164.

Full text

Abstract:

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 statistics required for testing hypotheses. This article discuss methods that account for the multiplicity issue and introduces various statistical techniques.

APA, Harvard, Vancouver, ISO, and other styles

20

Kantzos, K., and L. Vrizidis. "Statistical testing of empirical research hypotheses in accounting." Journal of Statistics and Management Systems 4, no. 2 (January 2001): 123–36. http://dx.doi.org/10.1080/09720510.2001.10701032.

Full text

APA, Harvard, Vancouver, ISO, and other styles

21

Weston, Peter H. "Problems with the statistical testing of panbiogeographic hypotheses." New Zealand Journal of Zoology 16, no. 4 (October 1989): 511. http://dx.doi.org/10.1080/03014223.1989.10422919.

Full text

APA, Harvard, Vancouver, ISO, and other styles

22

Hesamian, Gholamreza, and Mehdi Shams. "Parametric testing statistical hypotheses for fuzzy random variables." Soft Computing 20, no. 4 (February 5, 2015): 1537–48. http://dx.doi.org/10.1007/s00500-015-1604-x.

Full text

APA, Harvard, Vancouver, ISO, and other styles

23

Kuk, Yu V., and Yu I. Petunin. "Testing hypotheses by using optimal statistical criteria. II." Ukrainian Mathematical Journal 46, no. 5 (May 1994): 539–49. http://dx.doi.org/10.1007/bf01058517.

Full text

APA, Harvard, Vancouver, ISO, and other styles

24

Kuk, Yu V., and Yu I. Petunin. "Testing hypotheses by using optimal statistical criteria. I." Ukrainian Mathematical Journal 46, no. 4 (April 1994): 396–407. http://dx.doi.org/10.1007/bf01060409.

Full text

APA, Harvard, Vancouver, ISO, and other styles

25

Lehmann, E. L. "Testing statistical hypotheses: the story of a book." Statistical Science 12, no. 1 (February 1997): 48–52. http://dx.doi.org/10.1214/ss/1029963261.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Reghenzani, Federico, Giuseppe Massari, and William Fornaciari. "Probabilistic-WCET reliability: Statistical testing of EVT hypotheses." Microprocessors and Microsystems 77 (September 2020): 103135. http://dx.doi.org/10.1016/j.micpro.2020.103135.

Full text

APA, Harvard, Vancouver, ISO, and other styles

27

Aguinis, Herman, and Charles A. Pierce. "Testing Moderator Variable Hypotheses Meta-Analytically." Journal of Management 24, no. 5 (October 1998): 577–92. http://dx.doi.org/10.1177/014920639802400501.

Full text

Abstract:

We propose and illustrate a three-step procedure for testing moderator variable hypotheses meta-analytically. The procedure is based on Hedges and Olkin's (1985) meta-analytic approach, yet it incorporates study-level corrections for methodological and statistical artifacts that are typically advocated and used within psychometric approaches to meta-analysis (e.g., Hunter & Schmidt, 1990). The three- step procedure entails: (a) correcting study-level effect size estimates for across-study variability due to methodological and statistical arti facts, (b) testing the overall homogeneity of study-level effect size esti mates after the artifactual sources of variance have been removed, and (c) testing the effects of hypothesized moderator variables.

APA, Harvard, Vancouver, ISO, and other styles

28

Gorshenin, A. K. "Testing of statistical hypotheses in the splitting component model." Moscow University Computational Mathematics and Cybernetics 35, no. 4 (November 19, 2011): 176–83. http://dx.doi.org/10.3103/s0278641911040054.

Full text

APA, Harvard, Vancouver, ISO, and other styles

29

Chang, Myron N. "Testing Statistical Hypotheses on Stochastic Ordering of Discrete Distributions." Sequential Analysis 30, no. 3 (July 2011): 249–60. http://dx.doi.org/10.1080/07474946.2011.593914.

Full text

APA, Harvard, Vancouver, ISO, and other styles

30

Steinebach, J. "E. L. Lehmann, J. P. Romano: Testing statistical hypotheses." Metrika 64, no. 2 (August 11, 2006): 255–56. http://dx.doi.org/10.1007/s00184-006-0091-6.

Full text

APA, Harvard, Vancouver, ISO, and other styles

31

Zografos, K. "f-Dissimilarity of Several Distributions in Testing Statistical Hypotheses." Annals of the Institute of Statistical Mathematics 50, no. 2 (June 1998): 295–310. http://dx.doi.org/10.1023/a:1003443215838.

Full text

APA, Harvard, Vancouver, ISO, and other styles

32

Basu, A., A. Mandal, N. Martin, and L. Pardo. "Testing statistical hypotheses based on the density power divergence." Annals of the Institute of Statistical Mathematics 65, no. 2 (July 20, 2012): 319–48. http://dx.doi.org/10.1007/s10463-012-0372-y.

Full text

APA, Harvard, Vancouver, ISO, and other styles

33

Hager, Willi, and Marcus Hasselhorn. "Testing Psychological Hypotheses Addressing Two Independent Variables and One Dependent Variable." Perceptual and Motor Skills 81, no. 3_suppl (December 1995): 1171–82. http://dx.doi.org/10.2466/pms.1995.81.3f.1171.

Full text

Abstract:

Psychological hypotheses addressing the simultaneous influence of two independent variables on one dependent variable lead to the prediction of certain data patterns usually looked upon from the perspective of statistical interaction in two-way analysis of variance. With respect to certain types of psychological hypotheses statistical interaction may best be interpreted as a contrast of contrasts or a difference between two differences. Three types of patterns derived from three different psychological hypotheses are analyzed from this point of view and with respect to statistical interaction. Our focus lies in discussing predicted patterns derived from some psychological hypotheses; we do not discuss subsequent problems such as choice of robust alternatives to the classical parametric tests we apply nor do we consider how to deal with the problem of possibly cumulating error probabilities. In addition, we stress the difference between examining psychological hypotheses adequately and exhaustively and tests of data to gain more information that may be interesting although not relevant to a particular hypothesis.

APA, Harvard, Vancouver, ISO, and other styles

34

Yusup, Muhamad, Romzi Syauqi Naufal, and Marviola Hardini. "Management of Utilizing Data Analysis and Hypothesis Testing in Improving the Quality of Research Reports." Aptisi Transactions on Management (ATM) 2, no. 2 (January 25, 2019): 159–67. http://dx.doi.org/10.33050/atm.v2i2.789.

Full text

Abstract:

Data analysis and mathematical techniques play a central role in quantitative data processing. Quantitative researchers estimate (strength) the strength of the relationship of variables, and test hypotheses statistically. Unlike the case with qualitative research. Although qualitative researchers might test a hypothesis in the analysis process, they do not estimate or test hypotheses about the relationship of variables statistically. Through tests or statistical tests can be used as the main means for interpreting the results of research data. It is through this statistical test that we as researchers can compare which data groups and what can be used to determine probabilities or possibilities that distinguish between groups based on an opportunity. Thus, it can provide evidence to determine the validity of a hypothesis or conclusion. In this study, we will discuss the preparation of data for analysis such as editing data, coding, categorizing, and entering data. As well as discussing the differences in data analysis for descriptive statistics and inferential statistics, differences in data analysis for parametric and non-parametric statistics in research, explanations of multivariate data analysis procedures, and also forms of research hypotheses.

APA, Harvard, Vancouver, ISO, and other styles

35

Cooper, Robert A. "Making Decisions with Data: Understanding Hypothesis Testing & Statistical Significance." American Biology Teacher 81, no. 8 (October 1, 2019): 535–42. http://dx.doi.org/10.1525/abt.2019.81.8.535.

Full text

Abstract:

Statistical methods are indispensable to the practice of science. But statistical hypothesis testing can seem daunting, with P-values, null hypotheses, and the concept of statistical significance. This article explains the concepts associated with statistical hypothesis testing using the story of “the lady tasting tea,” then walks the reader through an application of the independent-samples t-test using data from Peter and Rosemary Grant's investigations of Darwin's finches. Understanding how scientists use statistics is an important component of scientific literacy, and students should have opportunities to use statistical methods like this in their science classes.

APA, Harvard, Vancouver, ISO, and other styles

36

KOLDANOV, PETR, and NINA LOZGACHEVA. "MULTIPLE TESTING OF SIGN SYMMETRY FOR STOCK RETURN DISTRIBUTIONS." International Journal of Theoretical and Applied Finance 19, no. 08 (December 2016): 1650049. http://dx.doi.org/10.1142/s0219024916500497.

Full text

Abstract:

Multiple statistical procedure for testing elliptical model for stock returns distribution is proposed. Sign symmetry conditions are chosen as individual hypotheses for multiple testing. Distribution free uniformly most powerful tests of Neyman structure are constructed for individual hypotheses testing. Associated stepwise multiple testing procedure is applied for the real market data. Numerical experiments shows that hypothesis of elliptical model is rejected. At the same time it is observed that the graph of rejected individual hypotheses has unexpected structure. Namely, this graph is sparse and has a few hubs of high degree. Removing this hubs leads to nonrejection of hypothesis of elliptical model.

APA, Harvard, Vancouver, ISO, and other styles

37

Evans, Michael, and Jabed Tomal. "Measuring statistical evidence and multiple testing." FACETS 3, no. 1 (October 1, 2018): 563–83. http://dx.doi.org/10.1139/facets-2017-0121.

Full text

Abstract:

The measurement of statistical evidence is of considerable current interest in fields where statistical criteria are used to determine knowledge. The most commonly used approach to measuring such evidence is through the use of p-values, even though these are known to possess a number of properties that lead to doubts concerning their validity as measures of evidence. It is less well known that there are alternatives with the desired properties of a measure of statistical evidence. The measure of evidence given by the relative belief ratio is employed in this paper. A relative belief multiple testing algorithm was developed to control for false positives and false negatives through bounds on the evidence determined by measures of bias. The relative belief multiple testing algorithm was shown to be consistent and to possess an optimal property when considering the testing of a hypothesis randomly chosen from the collection of considered hypotheses. The relative belief multiple testing algorithm was applied to the problem of inducing sparsity. Priors were chosen via elicitation, and sparsity was induced only when justified by the evidence and there was no dependence on any particular form of a prior for this purpose.

APA, Harvard, Vancouver, ISO, and other styles

38

Ganes, A. Hari, and N. Jaimaruthi. "On Statistical Hypothesis Testing Based on Interval Type-2 Hexagonal Fuzzy Numbers." International Journal of Fuzzy Mathematical Archive 14, no. 01 (2017): 69–79. http://dx.doi.org/10.22457/ijfma.v14n1a9.

Full text

Abstract:

The classical procedures for testing hypotheses are not appropriate for dealing with imprecise data. After the inception of the notion of fuzzy set theory, there have been attempts to analyze the problem of testing hypothesis for dealing with such imprecise data. In this paper, we consider the fuzzy data instead of crisp ones, and introduce a procedure for testing of hypothesis for imprecise data based on interval type -2 generalized hexagonal fuzzy numbers.

APA, Harvard, Vancouver, ISO, and other styles

39

Cho, Hyun-Chul, and Shuzo Abe. "Overreliance on Statistical Testing Logic in the Empirical Testing of Theories and Hypotheses." Journal of Global Academy of Marketing Science 21, no. 1 (March 2011): 45–54. http://dx.doi.org/10.1080/12297119.2011.9711011.

Full text

APA, Harvard, Vancouver, ISO, and other styles

40

Casabianca, Jodi M., and Charles Lewis. "Statistical Equivalence Testing Approaches for Mantel–Haenszel DIF Analysis." Journal of Educational and Behavioral Statistics 43, no. 4 (December 1, 2017): 407–39. http://dx.doi.org/10.3102/1076998617742410.

Full text

Abstract:

The null hypothesis test used in differential item functioning (DIF) detection tests for a subgroup difference in item-level performance—if the null hypothesis of “no DIF” is rejected, the item is flagged for DIF. Conversely, an item is kept in the test form if there is insufficient evidence of DIF. We present frequentist and empirical Bayes approaches for implementing statistical equivalence testing for DIF using the Mantel–Haenszel (MH) DIF statistic. With these approaches, rejection of the null hypothesis of “DIF” allows the conclusion of statistical equivalence, a more stringent criterion for keeping items. In other words, the roles of the null and alternative hypotheses are interchanged in order to have positive evidence that the DIF of an item is small. A simulation study compares the equivalence testing approaches to the traditional MH DIF detection method with the Educational Testing Service classification system. We illustrate the methods with item response data from the 2012 Programme for International Student Assessment.

APA, Harvard, Vancouver, ISO, and other styles

41

Payton, Mark E., Anthony E. Miller, and William R. Raun. "Testing statistical hypotheses using standard error bars and confidence intervals." Communications in Soil Science and Plant Analysis 31, no. 5-6 (March 2000): 547–51. http://dx.doi.org/10.1080/00103620009370458.

Full text

APA, Harvard, Vancouver, ISO, and other styles

42

Pichugin, Yury A. "Geometrical aspects of testing complex statistical hypotheses in mathematical simulation." St. Petersburg Polytechnical University Journal: Physics and Mathematics 1, no. 2 (June 2015): 181–91. http://dx.doi.org/10.1016/j.spjpm.2015.07.001.

Full text

APA, Harvard, Vancouver, ISO, and other styles

43

Nassar, Yahya H. "Effect Size as a Complementally Statistical Procedure of Testing Hypotheses." Journal of Educational & Psychological Sciences 07, no. 02 (June 1, 2006): 35–60. http://dx.doi.org/10.12785/jeps/070202.

Full text

APA, Harvard, Vancouver, ISO, and other styles

44

Palm, Günther. "Significance testing – does it need this defence?" Behavioral and Brain Sciences 21, no. 2 (April 1998): 214–15. http://dx.doi.org/10.1017/s0140525x98431169.

Full text

Abstract:

Chow's (1996) Statistical significance is a defence of null-hypothesis significance testing (NHSTP). The most common and straightforward use of significance testing is for the statistical corroboration of general hypotheses. In this case, criticisms of NHSTP, at least those mentioned in the book, are unfounded or misdirected. This point is driven home by the author a bit too forcefully and meticulously. The awkward and cumbersome organisation and argumentation of the book makes it even harder to read.

APA, Harvard, Vancouver, ISO, and other styles

45

López, Fernando, Mariano Matilla-García, Jesús Mur, and Manuel Ruiz Marín. "Statistical Tests of Symbolic Dynamics." Mathematics 9, no. 8 (April 9, 2021): 817. http://dx.doi.org/10.3390/math9080817.

Full text

Abstract:

A novel general method for constructing nonparametric hypotheses tests based on the field of symbolic analysis is introduced in this paper. Several existing tests based on symbolic entropy that have been used for testing central hypotheses in several branches of science (particularly in economics and statistics) are particular cases of this general approach. This family of symbolic tests uses few assumptions, which increases the general applicability of any symbolic-based test. Additionally, as a theoretical application of this method, we construct and put forward four new statistics to test for the null hypothesis of spatiotemporal independence. There are very few tests in the specialized literature in this regard. The new tests were evaluated with the mean of several Monte Carlo experiments. The results highlight the outstanding performance of the proposed test.

APA, Harvard, Vancouver, ISO, and other styles

46

Patriota, Alexandre Galvão. "On Some Assumptions of the Null Hypothesis Statistical Testing." Educational and Psychological Measurement 77, no. 3 (October 5, 2016): 507–28. http://dx.doi.org/10.1177/0013164416667979.

Full text

Abstract:

Bayesian and classical statistical approaches are based on different types of logical principles. In order to avoid mistaken inferences and misguided interpretations, the practitioner must respect the inference rules embedded into each statistical method. Ignoring these principles leads to the paradoxical conclusions that the hypothesis [Formula: see text] could be less supported by the data than a more restrictive hypothesis such as [Formula: see text], where [Formula: see text] and [Formula: see text] are two population means. This article intends to discuss and explicit some important assumptions inherent to classical statistical models and null statistical hypotheses. Furthermore, the definition of the p-value and its limitations are analyzed. An alternative measure of evidence, the s-value, is discussed. This article presents the steps to compute s-values and, in order to illustrate the methods, some standard examples are analyzed and compared with p-values. The examples denunciate that p-values, as opposed to s-values, fail to hold some logical relations.

APA, Harvard, Vancouver, ISO, and other styles

47

Pugh, Stephanie L., and Annette Molinaro. "The nuts and bolts of hypothesis testing." Neuro-Oncology Practice 3, no. 3 (November 24, 2015): 139–44. http://dx.doi.org/10.1093/nop/npv052.

Full text

Abstract:

Abstract When reading an article published in a medical journal, statistical tests are mentioned and the results are often supported by a P value. What are these tests? What is a P value and what is its meaning? P values are used to interpret the result of a statistical test. Both are intrinsic parts of hypothesis testing, which is a decision-making tool based on probability. Most medical and epidemiological studies are designed using a hypothesis test so understanding the key principles of a hypothesis test are crucial to interpreting results of a study. From null and alternative hypotheses to the issue of multiple tests, this paper introduces concepts related to hypothesis testing that are crucial to its implementation and interpretation.

APA, Harvard, Vancouver, ISO, and other styles

48

Hauer, Ezra. "Statistical Test of Difference between Expected Accident Frequencies." Transportation Research Record: Journal of the Transportation Research Board 1542, no. 1 (January 1996): 24–29. http://dx.doi.org/10.1177/0361198196154200104.

Full text

Abstract:

A primer on the testing of some common statistical hypotheses in road safety is presented. The basic notions of statistical hypothesis testing are reviewed and applied to the specific circumstance when one wishes to test a statistical hypothesis about a change in the expected accident frequency beyond what is the result of a change in traffic and similar influences. The hope is that this exposition will illumine the meaning and intricacy of such tests, inform the decision about when such tests are called for, help users choose the right significance or power, and, because software is now available, improve practice in this matter. A companion paper on the detection of deterioration in safety makes use of the foundation provided.

APA, Harvard, Vancouver, ISO, and other styles

49

De Waal, D. J. "Summary on Bayes estimation and hypothesis testing." Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie 7, no. 1 (March 17, 1988): 28–32. http://dx.doi.org/10.4102/satnt.v7i1.896.

Full text

Abstract:

Although Bayes’ theorem was published in 1764, it is only recently that Bayesian procedures were used in practice in statistical analyses. Many developments have taken place and are still taking place in the areas of decision theory and group decision making. Two aspects, namely that of estimation and tests of hypotheses, will be looked into. This is the area of statistical inference mainly concerned with Mathematical Statistics.

APA, Harvard, Vancouver, ISO, and other styles

50

Olejnik, Stephen, Jianmin Li, Suchada Supattathum, and Carl J. Huberty. "Multiple Testing and Statistical Power With Modified Bonferroni Procedures." Journal of Educational and Behavioral Statistics 22, no. 4 (December 1997): 389–406. http://dx.doi.org/10.3102/10769986022004389.

Full text

Abstract:

The difference in statistical power between the original Bonferroni and five modified Bonferroni procedures that control the overall Type I error rate is examined in the context of a correlation matrix where multiple null hypotheses, H0 : ρ ij = 0 for all i ≠ j, are tested. Using 50 real correlation matrices reported in educational and psychological journals, a difference in the number of hypotheses rejected of less than 4% was observed among the procedures. When simulated data were used, very small differences were found among the six procedures in detecting at least one true relationship, but in detecting all true relationships the power of the modified Bonferroni procedures exceeded that of the original Bonferroni procedure by at least .18 and by as much as .55 when all null hypotheses were false. The power difference decreased as the number of true relationships decreased. Power differences obtained for the average power were of a much smaller magnitude but still favored the modified Bonferroni procedures. For the five modified Bonferroni procedures, power differences less than .05 were typically observed; the Holm procedure had the lowest power, and the Rom procedure had the highest.

APA, Harvard, Vancouver, ISO, and other styles

Journal articles on the topic 'Statistical hypotheses testing'

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles