Praktyka wnioskowania statystycznego

Agresti A. (1990): Categorical Data Analysis. John Wiley and Sons, New York.
Zobacz w Google Scholar

Ahad N. A., Yin T. S., Othman A. R., Yaacob C. R. (2011): Sensitivity of Normality Tests to Non-normal Data. „Sains Malaysiana”, 40, 6, s. 637–641.
Zobacz w Google Scholar

Aitkin M. (2011): Paradigms for Statistical Inference, https://researchers.ms.unimelb.edu.au/~maitkin@unimelb/paradigms2.pdf, https://pdfs.semanticscholar.org/5226/77da13ad4ee11b2e8a9a02b0c1bdf6a77f4f.pdf (dostęp: 29.08.2011).
Zobacz w Google Scholar

Allen J., Le H. (2007): An Additive Measure of Overall Effect Size for Logistic Regression Models. „Journal of Educational and Behavioral Statistics”, http://jebs.aera.net (dostęp: 1.12.2008).
Zobacz w Google Scholar

Anscombe F. J., Aumann R. J. (1963): A Definition of Subjective Probability. „The Annals of Mathematical Statistics”, 34, 1, s. 199–205.
Zobacz w Google Scholar

APA (2010): Publication Manual. Sixth Edition. American Psychological Association, Washington.
Zobacz w Google Scholar

Armitage P., Doll R. (1954): The Age Distribution of Cancer and a Multi-stage Theory of Carcinogenesis. „British Journal of Cancer”, 8, 1, s. 1–12.
Zobacz w Google Scholar

Armitage P., Doll R. (1961): Stochastic Models for Carcinogenesis. „Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, University of California Press”, 4, s. 19–38.
Zobacz w Google Scholar

Armstrong J. S. (2007): Significance Tests Harm Progress in Forecasting. „International Journal of Forecasting”, 23, 2, s. 321–327.
Zobacz w Google Scholar

Awan H. M. (2001): Effect of Departure from Standard Assumptions Used in Analysis of Variance. „Journal of Research (Science)”, 12, 2, s. 180–188.
Zobacz w Google Scholar

Babu G. J., Padmanabhan A. R., Puri M. L. (1999): Robust One-Way ANOVA under Possibly Non-Regular Conditions. „Biometrical Journal”, 41, 3, s. 321–339.
Zobacz w Google Scholar

Bakeman R. (2005): Recommended Effect Size Statistics for Repeated Measures Designs. „Behavior Research Methods”, 37, 3, s. 379–384.
Zobacz w Google Scholar

Bandyopadhyay P. S., Forster M. R. (red.) (2011): Handbook of Philosophy of Science, Vol. 7: Philosophy of Statistics. Elsevier, Amsterdam.
Zobacz w Google Scholar

Bernardo J. M. (2011): Modern Bayesian inference: foundations and objective methods. W: Handbook of Philosophy of Science, Vol. 7: Philosophy of Statistics. Red. P. S. Bandyopadhyay, M. R. Forster, s. 263–306. Elsevier, Amsterdam.
Zobacz w Google Scholar

Berger J. O. (2003): Could Fisher, Jefreys and Neyman Have Agreed on Testing? „Statistical Sciences”, 18, 1, s. 1–32.
Zobacz w Google Scholar

Berger J. O., Berry D. A. (1988): Statistical Analysis and the Illusion of Objectivity. „American Scientist”, 76, s. 159–165.
Zobacz w Google Scholar

Blalock H. M. (1975): Statystyka dla socjologów. Państwowe Wydawnictwo Naukowe, Warszawa.
Zobacz w Google Scholar

Blume J. D. (2002): Likelihood Methods for Measuring Statistical Evidence. „Statistics in Medicine”, 21, s. 2563–2599.
Zobacz w Google Scholar

Bock R. D. (1975): Multivariate Statistical Methods in Behavioral Research. McGraw-Hill Inc., New York.
Zobacz w Google Scholar

Bromek T., Pleszczyńska E. (red.) (1988): Teoria i praktyka wnioskowania statystycznego. Państwowe Wydawnictwo Naukowe, Warszawa.
Zobacz w Google Scholar

Brown M. B., Forsythe A. B. (1974): Robust Tests for the Equality of Variances. „Journal of the American Statistical Association”, 69, s. 364–367.
Zobacz w Google Scholar

Calculating Cancer Risk Due to Occupational Exposure to Genotoxic Carcinogens (1995). Report of the Dutch Expert Committee on Occupational Standards, a Committee of the Health Council of the Netherlands, No. 1995/06WGD, The Hague, 18 October 1995.
Zobacz w Google Scholar

Carlin B. P., Louis T. A. (2000): Bayes and Empirical Bayes Methods for Data Analysis. Chapman and Hall/CRC, Boca Raton.
Zobacz w Google Scholar

Carver R. P. (1993). The Case against Statistical Significance Testing, Revisited. „Journal of Experimental Education”, 1993, 61, s. 287–292. Cyt. za: A. J. Onwuegbuzie, N. L. Leech (2004): Post Hoc Power: A Concept Whose Time Has Come. „Understanding Statistics”, 3, 4, s. 201–230.
Zobacz w Google Scholar

Chinn S. (2000): A Simple Method for Converting an Odds Ratio to Effect Size for Use in Meta-analysis. „Statistics in Medicine”, 19, 22, s. 3127–3131.
Zobacz w Google Scholar

Chmura-Kraemer H., Kupfer D. J. (2006): Size of Treatment Effects and Their Importance to Clinical Research and Practice. „Biological Psychiatry”, 56, 11, s. 90–996.
Zobacz w Google Scholar

Christensen R. (2005): Testing Fisher, Neyman, Pearson, and Bayes. „The American Statistician”, 59, 2, s. 121–126.
Zobacz w Google Scholar

Cohen J. (1988): Statistical Power Analysis for the Behavioral Sciences. Second Edition. Lawrence Erlbaum Associates Inc., Hillsdale.
Zobacz w Google Scholar

Cohen J. (1992a): A Power Primer. „Psychological Bulletin”, 112, 1, s. 155–159.
Zobacz w Google Scholar

Cohen J. (1992b): Statistical Power Analysis. „Current Directions in Psychological Sciences”, 1, 3, s. 98–101.
Zobacz w Google Scholar

Cohen J. (1994): The Earth Is Round (p < .05). „American Psychologist”, 49, 12, s. 997–1003.
Zobacz w Google Scholar

Collins J. F., Brown J. P., Dawson S. V., Marty M. A. (1991): Risk Assessment for Benzo[a]pyrene. „Regulatory Toxicology and Pharmacology”, 13, 2, s. 170–184.
Zobacz w Google Scholar

Congdon P. (2002): Bayesian Statistical Modelling. John Wiley and Sons, Chichester. Connett J. E., Smith Judith A., McHugh R. B. (1987): Sample Size and Power for Pairmatched Case-control Studies. „Statistics in Medicine”, 6, s. 53–59.
Zobacz w Google Scholar

Connor R. J. (1987): Sample Size for Testing Differences in Proportions for the Paired-sample Design. „Biometrics”, 43, s. 207–211.
Zobacz w Google Scholar

Conover W. J., Johnson M. E., Johnson M. M. (1981): A Comparative Study of Tests for Homogeneity of Variances, with Applications to the Outer Continental Shelf Bidding Data. „Technometrics”, 23, s. 351–361.
Zobacz w Google Scholar

Cumming G. (2014): The New Statistics: Why and How. „Psychological Science ”, 25, 1, s. 7–29.
Zobacz w Google Scholar

De Kleijn W. P. E., De Vries J., Petal A. H. M., Wijnen P. A. H. M., Drent M. (2011): Minimal (clinically) important differences for the Fatigue Assessment Scale in sarcoidosis, „Respiratory Medicine”, 105, 1, s. 1388–1395.
Zobacz w Google Scholar

Denis D. J. (2003): Alternatives to Null Hypothesis Significance Testing. “Theory and Science”, 4, 1, s. 1–17, http://theoryandscience.icaap.org/content/vol14.1/02_denis.html (dostęp: 6.12.2007).
Zobacz w Google Scholar

Dienes Z. (2011): Bayesian Versus Orthodox Statistics: Which Side Are You On? „Perspective on Psychological Science”, 6, 3, s. 274–290.
Zobacz w Google Scholar

Donoghue D., Physiotherapy Research and Older People (PROP), Stokes E. K. (2009): How Much Change is True Change? The Minimum Detectable Change of the Berg Balance Scale in Elderly People. „Journal of Rehabilitation Medicine”, 41, s. 343–346.
Zobacz w Google Scholar

Dudek B. (2007): Stres związany z pracą: teoretyczne i metodologiczne podstawy badań zależności między zdrowiem a stresem zawodowym. W: Perspektywy psychologii pracy. Red. M. Górnik-Durose, B. Kożusznik, s. 220–246. Wydawnictwo Uniwersytetu Śląskiego, Katowice.
Zobacz w Google Scholar

Efron B. (1978): Controversies in the Foundation of Statistics. „American Mathematical Monthly”, 85, 4, s. 231–246.
Zobacz w Google Scholar

Efron B. (1998): R. A. Fisher in the 21st Century. Invited Paper Presented at the 1996 R. A. Fisher Lecture. „Statistical Science”, 13, 2, s. 95–122.
Zobacz w Google Scholar

Eisen S. V., Ranganathan G., Seal P., Spiro A. III (2007): Measuring Clinically Meaningful Change Following Mental Health Treatment. „The Journal of Behavioral Health Services and Research”, 34, 3, s. 272–289.
Zobacz w Google Scholar

Field A. (2009): Discovering Statistics Using SPSS. Third Edition. Sage Publications, Thousand Oaks.
Zobacz w Google Scholar

Fisher R. A. (1922): On the Mathematical Foundations of Theoretical Statistics. „Philosophical Transactions of the Royal Society of London”. Series A, Containing Papers of a Mathematical or Physical Character, 222, s. 309–368.
Zobacz w Google Scholar

Fisher R. A. (1935): The Logic of Inductive Inference (with Discussion). „Journal of the Royal Statistical Society”, 98, 1, s. 39–82.
Zobacz w Google Scholar

Fisher R. A. (1955): Statistical Methods and Scientific Induction. „Journal of the Royal Statistical Society”. Series B (Methodological), 17, 1, s. 69–78.
Zobacz w Google Scholar

Fisher R. A. (1956): Statistical Methods and Scientific Inference. Oliver and Bond, Edinburgh. Cyt. za: G. Gigerenzer (2004): Mindless Statistics. „Journal of Behavioral and Experimental Economics” (formerly „The Journal of Socio-Economics”), 33, 5, s. 587–606.
Zobacz w Google Scholar

Fisz M. (1969): Rachunek prawdopodobieństwa i statystyka matematyczna. Państwowe Wydawnictwo Naukowe, Warszawa.
Zobacz w Google Scholar

Frans F. A., Nieuwkerk P. T., Met R., Bipat S., Legemate D. A., Reekers J. A., Koelemay M. J. W. (2014): Statistical or Clinical Improvement? Determining the Minimally Important Difference for the Vascular Quality of Life Questionnaire in Patients with Critical Limb Ischemia. „European Journal of Vascular and Endovascular Surgery”, 47, 2, s. 180–186.
Zobacz w Google Scholar

Freedman D. (1995/1996): Some Issues in the Foundations of Statistics. „Foundations of Science”, 1, s. 19–39.
Zobacz w Google Scholar

Freeman G. H., Halton J. H. (1951): Note on an Exact Treatment of Contingency, Goodness of Fit and Other Problems of Significance. „Biometrika”, 38, s. 141–149.
Zobacz w Google Scholar

Games P. A. (1971): Multiple Comparisons of Means. „American Educational Research Journal”, 8, s. 531–565.
Zobacz w Google Scholar

Garcia-Perez A. (2008): Approximations for F-Tests Which Are Ratios of Sums of Squares of Independent Variables with a Model Close to Normal. „Test”, 17, 2, s. 350–369.
Zobacz w Google Scholar

Garson G. D. (2012): Testing Statistical Assumptions. Statistical Associates Publishing, North Carolina State University, Raleigh.
Zobacz w Google Scholar

Gart J. J., Krewski D., Lee P. N., Tarone R. E., Wahrendorf J. (1986): Statistical Methods in Cancer Research, Vol. III: The Design and Analysis of Long-term Animal Experiments. International Agency for Research on Cancer, Lyon.
Zobacz w Google Scholar

Gastwirth J. L., Gel Yulia R., Miao W. (2009): The Impact of Levene’s Test of Equality of Variances on Statistical Theory and Practice. „Statistical Science”, 24, 3, s. 343–360.
Zobacz w Google Scholar

Gigerenzer G. (2004): Mindless Statistics. „Journal of Behavioral and Experimental Economics” (formerly „The Journal of Socio-Economics”), 33, 5, s. 587–606.
Zobacz w Google Scholar

Gigerenzer G., Marewski J. N. (2015): Surrogate Science: The Idol of a Universal Method for Scientific Inference. „Journal of Management”, 41, 2, s. 421–440.
Zobacz w Google Scholar

Gigerenzer G., Krauss S., Vitouch O. (2004): The Null Ritual. What You Always Wanted to Know About Significance Testing but Were Afraid to Ask. W: The Sage Handbook of Quantitative Methodology for the Social Sciences. Red. D. Kaplan, s. 391–408. Sage Publications, Thousand Oaks.
Zobacz w Google Scholar

Gillett R. (1994): Post Hoc Power Analysis. „Journal of Applied Psychology”, 79, 5, s. 783–785.
Zobacz w Google Scholar

Glass G. V., Peckham P. D., Sanders J. R. (1972): Consequences of Failure to Meet Assumptions Underlying the Fixed Effects Analyses of Variance and Covariance. „Review of Educational Research”, 42, 3, s. 237–288.
Zobacz w Google Scholar

Gomez J. (2012): Tam gdzie proste są krzywe. Geometrie nieeuklidesowe. RBA Coleccionables, Barcelona.
Zobacz w Google Scholar

Gray C. D., Kinnear P. R. (2012): IBM SPSS Statistics 19 Made Simple. Psychology Press, New York. Cyt. za: K. L. Wuensch (2015): Nonparametric Effect Size Estimators. Materiały dydaktyczne. East Carolina University Department of Psychology, core.ecu.edu/psyc/wuenschk/docs30/Nonparametric-EffectSize.pdf (dostęp: 16.06.2015).
Zobacz w Google Scholar

Greenland S., Schlesselman J. J., Criqui M. H. (1986): The Fallacy of Employing Standardized Regression Coefficients and Correlations as Measures of Effect. „American Journal of Epidemiology”, 123, 2, s. 203–208.
Zobacz w Google Scholar

Greenland S., Maclure M., Schlesselman J. J., Poole C., Morgenstern H. (1991): Standardized Regression Coefficients: A Further Critique and Review of Some Alternatives. „Epidemiology”, 2, 5, s. 387–392.
Zobacz w Google Scholar

Greń J. (1968): Modele i zadania statystyki matematycznej. Państwowe Wydawnictwo Naukowe, Warszawa.
Zobacz w Google Scholar

Hagen R. L. (1997): In Praise of the Null Hypothesis Statistical Test. „American Psychologist”, 52, 1, s. 15–24.
Zobacz w Google Scholar

Häggström O. (2012): Why the Empirical Sciences Need Statistics So Desperately. W: European Congress of Mathematics, Krakow, 2–7 July, 2012. Red. R. Latała, A. Ruciński, P. Strzelecki, J. Świątkowski, D. Wrzosek, P. Zakrzewski, s. 347–360. European Mathematical Society Publishing House, Zurich.
Zobacz w Google Scholar

Hartley, H. O. (1950): The Maximum F-rates as a Shortcut Test for Heterogeneity of Variance. „Biometrika”, 37, 308–312.
Zobacz w Google Scholar

Hilbe J. M. (2009): Logistic Regression Models. Chapman and Hall/CRC, Boca Raton. Hoenig J. M., Heisey D. M. (2001): The Abuse of Power: The Pervasive Fallacy of Power Calculations for Data Analysis. „The American Statistician”, 55, 1, s. 19–24.
Zobacz w Google Scholar

Hosmer D. W., Lemeshow L. (1989): Applied Logistic Regression. John Wiley and Sons, New York.
Zobacz w Google Scholar

Hsieh F. Y. (1989): Sample Size Tables for Logistic Regression. „Statistics in Medicine”, 8, s. 795–802.
Zobacz w Google Scholar

Hubbard R., Armstrong J. S. (2006): Why We Don’t Really Know What „Statistical Significance” Means: A Major Educational Failure. „Journal of Marketing Education”, 28, 2, s. 114–120.
Zobacz w Google Scholar

Hubbard R., Bayarri M. J. (2003): Confusion Over Measures of Evidence (p’s) Versus Errors (α’s) in Classical Statistical Testing. „The American Statistician”, 57, 3, s. 171–182.
Zobacz w Google Scholar

Inman H. F. (1994): Karl Pearson and R. A. Fisher on Statistical Tests: A 1935 Exchange From Nature. „The American Statistician”, 48, 1, s. 2–11.
Zobacz w Google Scholar

Jacobson N. S., Truax P. (1991): Clinical Significance: A Statistical Approach to Defining Meaningful Change in Psychotherapy Research. „Journal of Consulting and Clinical Psychology”, 59, 1, s. 12–19.
Zobacz w Google Scholar

Jeffreys H. (1961): Theory of Probability, 3rd ed. Oxford University Press, Oxford. Cyt. za: J. O. Berger (2003): Could Fisher, Jefreys and Neyman Have Agreed on Testing? „Statistical Sciences”, 18, 1, s. 1–32.
Zobacz w Google Scholar

Jones L. V., Tukey J. W. (2000): A Sensible Formulation of the Significance Test. „Psychological Methods”, 5, 4, s. 411–414.
Zobacz w Google Scholar

Karni E. (1993): A Definition of Subjective Probabilities with State-dependent Preferences. „Econometrica”, 61, 1, s. 187–198.
Zobacz w Google Scholar

Kerby D. S. (2014): The Simple Difference Formula: An Approach to Teaching Nonparametric Correlation. „Innovative Teaching”, 3, 1. Cyt. za: K. L. Wuensch (2015): Nonparametric Eff ct Size Estimators. Materiały dydaktyczne. East Carolina University, Department of Psychology, Greenville.
Zobacz w Google Scholar

Keselman H. J., Cribbie R. A., Wilcox R. R. (2002): Pairwise Multiple Comparison Tests When Data Are Nonnormal. „Educational and Psychological Measurement”, 62, 3, s. 420–434.
Zobacz w Google Scholar

Khan A., Rayner G. D. (2003): Robustness to Non-Normality of Common Tests for the ManySample Location Problem. „Journal of Applied Mathematics and Decision Sciences”, 7, 4, s. 187–206.
Zobacz w Google Scholar

Killeen P. R. (2005): An Alternative to Null-Hypothesis Significance Tests. „Psychological Science”, 16, 5, s. 345–353.
Zobacz w Google Scholar

Kirk R. E. (1994): Experimental Design: Procedures for the Behavioral Sciences, 3rd ed. Wadsworth Publishing, Belmont CA.
Zobacz w Google Scholar

Kochanski G. (2005): Brute Force as a Statistical Tool, http://kochanski.org/gpk (dostęp: 1.03.2005).
Zobacz w Google Scholar

Kołmogorow A. N. (1933): Grundbegriffe der Wahrscheinlichkeitsrechnung. „Ergebnisse der Mathematik und ihrer Grenzgebiete”, 3, s. 1–62. Cyt. za: H. Bauer (1968): Probability Theory and Elements of Measure Theory. Holt, Rinehart and Winston Inc., New York. Krämer W. (2011): The Cult of Statistical Significance. What Economists Should and Should Not Do to Make Their Data Talk. Working Paper Series of the German Data Forum (RatSWD). Working Paper No. 176, April 2011.
Zobacz w Google Scholar

Kubot A. (2017): Zastosowanie radialnej fali uderzeniowej i ultradźwięków w leczeniu zespołu łokcia tenisisty. Rozprawa na stopień doktora nauk medycznych, Uniwersytet Medyczny, Łódź.
Zobacz w Google Scholar

Kubot A., Grzegorzewski A., Synder M., Szymczak W., Kozłowski P. (2017): Zastosowanie radialnej fali uderzeniowej i ultradźwięków w leczeniu zespołu łokcia tenisisty. „Ortopedia Traumatologia Rehabilitacja”, 19, 5(6), s. 415–426.
Zobacz w Google Scholar

Kuhn T. S. (2009): Struktura rewolucji naukowych. Wydawnictwo Aletheia, Warszawa. Tłum. z: The Structure of Scientific Revolutions, 3rd ed. The University of Chicago Press, Chicago–London 1996.
Zobacz w Google Scholar

Kyburg H. E., Jr. (1977): Decisions, Conclusions, and Utilities. „Synthese”, 36, s. 87–96.
Zobacz w Google Scholar

Lachin J. M. (1986): Evaluation of Sample Size and Power for Analyses of Survival with Allowance for Nonuniform Patient Entry, Losses to Follow-up, Noncompliance, and Stratification. „Biometrics”, 42, s. 507–519.
Zobacz w Google Scholar

Lambdin C. (2012): Significance Tests as Sorcery: Science Is Empirical – Significance Tests Are Not. „Theory and Psychology”, 22, 1, s. 67–90.
Zobacz w Google Scholar

Lantz B. (2013): The Impact of Sample Non-normality on ANOVA and Alternative Methods. „British Journal of Mathematical and Statistical Psychology”, 66, s. 224–244.
Zobacz w Google Scholar

Laplace P. S. (1812): Theorie analytique des probabilites, Courcier, Paris.
Zobacz w Google Scholar

Lee H. B., Katz G. S., Restori A. F. (2010): A Monte Carlo Study of Seven Homogeneity of Variance Tests. „Journal of Mathematics and Statistics”, 6, 3, s. 359–366.
Zobacz w Google Scholar

Lee M. D., Wagenmakers E.-J. (2005): Bayesian Statistical Inference in Psychology: Comment on Trafimow (2003). „Psychological Review”, 112, 3, s. 662–668.
Zobacz w Google Scholar

Lehmann E. L. (1959): Testing Statistical Statistics. John Wiley and Sons, New York. Pol. tłum.: Testowanie hipotez statystycznych. Państwowe Wydawnictwo Naukowe, Warszawa 1968.
Zobacz w Google Scholar

Lehmann E. L. (1968): Testowanie hipotez statystycznych. Państwowe Wydawnictwo Naukowe, Warszawa.
Zobacz w Google Scholar

Lehmann E. L. (1993): The Fisher, Neyman-Pearson Theories of Testing Hypotheses: One Theory or Two? „Journal of the American Statistical Association”, 88, 424, s. 1242–1249.
Zobacz w Google Scholar

Lehmann E. L. (1995): Neyman’s Statistical Philosophy. „Probability and Mathematical Statistics”, 15, s. 29–36.
Zobacz w Google Scholar

Lehmann E. L. (2006): Nonparametrics. Statistical Methods Based on Ranks. Springer, New York.
Zobacz w Google Scholar

Lemeshow S., Hosmer D. W., Klar J. (1988): Sample Size Requirements for Studies Estimating Odds Ratios or Relative Risks. „Statistics in Medicine”, 7, s. 759–764.
Zobacz w Google Scholar

Lenth R. V. (2007): Post Hoc Power: Tables and Commentary. Technical Report No. 378, The University of Iowa, Department of Statistics and Actuarial Sciences, s. 1–13.
Zobacz w Google Scholar

Levene H. (1960): Robust Tests of Equality of Variances. W: Contributions to Probability and Statistics. Essays in Honor of Harold Hotelling, Red. I. Olkin, S. G. Ghurye, W. Hoeffding, W. G. Madow, H. B. Mann, s. 278–292. Stanford University Press, Palo Alto.
Zobacz w Google Scholar

Leventhal L., Huynh C. L. (1996): Directional Decisions for Two-Tailed Tests: Power, Error Rates and Sample Size. „Psychological Methods”, 1, 3, s. 278–292.
Zobacz w Google Scholar

Levine T. R., Hullett C. R. (2002): Eta Squared, Partial Eta Squared, and Misreporting of Effect Size in Communication Research. „Human Communication Research”, 28, 4, s. 612–625.
Zobacz w Google Scholar

Levine T. R., Weber R., Hullet C., Park H. S., Lindsey Lisa L. M. (2008): A Critical Assessment of Null Hypothesis Significance Testing in Quantitative Communication Research. “Human Communication Research”, 34, 171–187.
Zobacz w Google Scholar

Levy P. S., Lemeshow S. (1991): Sampling of Populations: Methods and Applications. John Wiley and Sons, New York.
Zobacz w Google Scholar

Lillestøl J. (2014): Statistical Inference: Paradigms and Controversies in Historic Perspective. NHH Norwegian School of Economics, Bergen, Department of Business and Management Science, https://www.nhh.no/globalassets/departments/business-and-management-science/statistical_inference.pdf (dostęp: 16.06.2015).
Zobacz w Google Scholar

Lim T.-S., Loh W.-Y. (1996): A Comparison of Tests of Equality of Variances. „Computational Statistics and Data Analysis”, 22, s. 287–301.
Zobacz w Google Scholar

Lindgren B. W. (1962): Statistical Theory. The Macmillan Co., New York.
Zobacz w Google Scholar

Lindley D. V. (1961): The Use of Prior Probability Distributions in Statistical Inference and Decisions. Proceedings of the Fourth Berkeley Symposium on Mathematical Statistics and Probability, University of California Press, Berkeley–Los Angeles.
Zobacz w Google Scholar

Lindquist E. F. (1938): A First Course in Statistics. Houghton Mifflin Harcourt, Cambridge.
Zobacz w Google Scholar

Cyt za: Huberty C. J. (1993): Historical Origins of Statistical Testing Practices: The Treatment of Fisher Versus Neyman-Pearson Views in Textbooks. „Journal of Experimental Education”, 61, 4, s. 317–333.
Zobacz w Google Scholar

Loftus G. R. (1996): Psychology Will Be a Much Better Science When We Change the Way We Analyze Data. „Current Directions in Psychological Science”, 5, 6, s. 161–171.
Zobacz w Google Scholar

Machina M. J., Schmeidler D. (1992): A More Robust Definition of Subjective Probability. „Econometrica”, 60, 4, s. 745–780.
Zobacz w Google Scholar

Magee L. (1990): R2 Measures Based on Wald and Likelihood Ratio Joint Significance Tests. „The American Statistician”, 44, 3, s. 250–253.
Zobacz w Google Scholar

Magiera R. (2007): Modele i metody statystyki matematycznej. Część II: Wnioskowanie statystyczne, wydanie drugie rozszerzone. Oficyna Wydawnicza GiS, Wrocław.
Zobacz w Google Scholar

Manthey J. (2010): Elementary Statistics: A History of Controversy. AMATYC 2010 Conference – Bridging Past to Future Mathematics, Boston MA, November 11–14, 2010.
Zobacz w Google Scholar

Mara C. A. (2013): Testing for Equivalence of Group Variances. A Dissertation Submitted to the Faculty of Graduate Studies in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy. York University, Toronto.
Zobacz w Google Scholar

Maslow A. H. (1966): The Psychology of Science. Harper and Row, New York.
Zobacz w Google Scholar

Mehlman M. H. (2017): ANOVA: Analysis of Variance. University of New Haven, http://math.newhaven.edu/mhm/courses/bstat/items.html, http://math.newhaven.edu/mhm/courses/estat/slides/ANOVA.pdf (dostęp: 4.12.2017).
Zobacz w Google Scholar

Mehta C. R., Patel N. R. (1983). A Network Algorithm for Performing Fisher’s Exact Test in r × c Contingency Tables. „Journal of the American Statistical Association”, 78, 382, s. 427–434.
Zobacz w Google Scholar

Mehta C. R., Patel N. R. (1986): Algorithm 643. FEXACT: A Fortran Subroutine for Fisher’s Exact Test on Unordered r × c Contingency Tables. „ACM Transactions on Mathematical Software”, 12, s. 154–161.
Zobacz w Google Scholar

Menard S. (2000): Coefficients of Determination for Multiple Logistic Regression Analysis. „The American Statistician”, 54, 1, s. 17–24.
Zobacz w Google Scholar

Miller W. R., Manuel J. K. (2008): How Large Must a Treatment Effect Be Before it Matters to Practitioners? An Estimation Method and Demonstration. „Drug and Alcohol Review”, 27, s. 524–528.
Zobacz w Google Scholar

Mises R., von (1936): Wahrscheinlichkeit, Statistik und Wahrheit. Springer Verlag, Wienna. Moolgavkar S. H. (1986): Carcinogenic Modeling: From Molecular Biology to Epidemiology. „The Annual Review of Public Health”, 7, s. 151–169.
Zobacz w Google Scholar

Nagelkerke N. J. D. (1991): A Note on a General Definition of the Coefficient of Determination. „Biometrika”, 78, 3, s. 691–692.
Zobacz w Google Scholar

Neveu J. (1964): Bases mathématiques du calcul des probabilités. Masson et Cie, Paris.
Zobacz w Google Scholar

Neyman J. (1969): Zasady rachunku prawdopodobieństwa i statystyki matematycznej. Państwowe Wydawnictwo Naukowe, Warszawa.
Zobacz w Google Scholar

Neyman J. (1977): Frequentist Probability and Frequentist Statistics. „Synthese”, 36, s. 97–131.
Zobacz w Google Scholar

Neyman J., Pearson E. S. (1933): On the Problem of the Most Efficient Tests of Statistical Hypotheses. „Philosophical Transactions of the Royal Statistical Society. Section A”, 231, s. 289–337. Cyt. za: E. L. Lehmann (1995): Neyman’s Statistical Philosophy. „Probability and Mathematical Statistics”, 15, s. 29–36.
Zobacz w Google Scholar

Nordstokke D. W., Zumbo B. D. (2007): A Cautionary Tale About Levene’s Tests for Equal Variances. „Journal of Educational Research and Policy Studies”, 7, 1, s. 1–14.
Zobacz w Google Scholar

O’Keefe D. J. (2007): Post Hoc Power, Observed Power, A Priori Power, Retrospective Power, Prospective Power, Achieved Power: Sorting Out Appropriate Uses of Statistical Power Analyses. „Communication Methods and Measures”, 1, 4, s. 291–299.
Zobacz w Google Scholar

Onwuegbuzie A. J., Leech N. L. (2004): Post Hoc Power: A Concept Whose Time Has Come. „Understanding Statistics”, 3, 4, s. 201–230.
Zobacz w Google Scholar

Papoulis A. (1972): Prawdopodobieństwo, zmienne losowe i procesy stochastyczne. Tłum. T. Gerstenkorn, Wydawnictwa Naukowo-Techniczne, Warszawa.
Zobacz w Google Scholar

Parra-Frutos I. (2009): The Behaviour of the Modified Levene’s Test When Data Are Not Normally Distributed. „Computational Statistics”, 24, s. 671–693.
Zobacz w Google Scholar

Pawłowski Z. (1976): Statystyka matematyczna. Państwowe Wydawnictwo Naukowe, Warszawa.
Zobacz w Google Scholar

Portier C. J., Kopp-Schneider A., Sherman C. D. (1993): Using Cell Replication Data in Mathematical Modeling in Carcinogenesis. „Environ Health Perspect” 101 (Suppl. 5), s. 79–86.
Zobacz w Google Scholar

Rao C. R. (1965): Linear Statistical Inference and Its Applications. John Wiley and Sons, New York. Pol. tłum.: Modele liniowe statystyki matematycznej. Państwowe Wydawnictwo Naukowe, Warszawa, 1982.
Zobacz w Google Scholar

Rao C. R. (1994): Statystyka i prawda. Wydawnictwo Naukowe PWN, Warszawa.
Zobacz w Google Scholar

Rasch D. (2012): Hypothesis Testing and the Error of the Third Kind. „Psychological Test and Assessment Modeling”, 54, 1, s. 90–99.
Zobacz w Google Scholar

Razali N. M., Wah Y. B. (2011): Power Comparisons of Shapiro-Wilk, Kolmogorov-Smirnov, Lilliefors and Anderson-Darling Tests. „Journal of Statistical Modeling and Analytics”, 2, 1, s. 21–33.
Zobacz w Google Scholar

Richardson J. T. E. (1996): Measures of Effect Size. „Behavior Research Methods, Instruments and Computers”, 28, 1, s. 12–22.
Zobacz w Google Scholar

Richardson J. T. E. (2011): Eta Squared and Partial Eta Squared as Measures of Effect Size in Educational Research. „Educational Research Review”, 6, s. 135–147.
Zobacz w Google Scholar

Roberts S., Pashler H. (2000): How Persuasive Is a Good Fit? A Comment on Theory Testing. „Psychological Review”, 107, 2, s. 358–367.
Zobacz w Google Scholar

Robinson D. H., Wainer H. (2001): On the Past and Future of Null Hypothesis Significance Testing. Research Report RR-01-24, Educational Testing Service, Princeton.
Zobacz w Google Scholar

Rodgers J. L. (2010): The Epistemology of Mathematical and Statistical Modeling. A Quiet Methodological Revolution. „American Psychologist”, 65, 1, s. 1–12.
Zobacz w Google Scholar

Rosenthal R. (1991): Meta-analytic Procedures for Social Research, 2nd ed. Sage Publications, Newbury Park CA. Cyt. za: A. Field (2009): Discovering Statistics Using SPSS, 3rd ed. Sage Publications, Newbury Park.
Zobacz w Google Scholar

Rosnow R. L., Rosenthal R. (2005): Beginning Behavioural Research: A Conceptual Primer, 5th ed. Pearson/Prentice Hall, Englewood Cliffs. Cyt. za: A. Field (2009): Discovering Statistics Using SPSS, 3rd ed. Sage Publications, Thousand Oaks.
Zobacz w Google Scholar

Royall R. (2000a): On the Probability of Observing Misleading Statistical Evidence (with Comments). „Journal of the American Statistical Association”, 95, 451, s. 760–780.
Zobacz w Google Scholar

Royall R. (2000b): Statistical Evidence. A Likelihood Paradigm. Chapman and Hall/CRC, Boca Raton.
Zobacz w Google Scholar

Royston P. (1982): An Extension of Shapiro and Wilks’s W Test for Normality to Large Samples. „Applied Statistics”, 31, s. 115–124.
Zobacz w Google Scholar

Royston P. (1983): A Simple Method for Evaluating the Shapiro-Francia W Test of Nonnormality. „Statistician”, 32, s. 297–300.
Zobacz w Google Scholar

Satten G. A., Kupper L. L. (1990): Sample Size Requirements for Interval Estimation on the Odds Ratio. „American Journal of Epidemiology”, 131, 1, s. 177–184.
Zobacz w Google Scholar

Savage L. J. (1954): The Foundations of Statistics. John Wiley and Sons, New York.
Zobacz w Google Scholar

Savage L. J. (1958): Recent Tendencies in the Foundations of Statistics. Invited address to Section VI of the International Congress of Mathematicians, Edinburgh, 14–21 August 1958.
Zobacz w Google Scholar

Schoenfeld D. A. (1983): Sample-Size Formula for the Proportional-Hazards Regression Model. „Biometrics”, 39, s. 499–503.
Zobacz w Google Scholar

Sedlmeier P., Gigerenzer G. (1989): Do Studies of Statistical Power Have an Effect on the Power of Studies. „Psychological Bulletin”, 105, 2, s. 309–316.
Zobacz w Google Scholar

Shapiro S. S., Francia R. S. (1972): An Approximate Analysis of Variance Test for Normality. „Journal of the American Statistical Association”, 67, s. 215–216.
Zobacz w Google Scholar

Shapiro S. S., Wilk M. B. (1965): An Analysis of Variance Test for Normality (Complete Samples). „Biometrika”, 52, s. 591–611.
Zobacz w Google Scholar

Silvey S. D. (1978): Wnioskowanie statystyczne. Państwowe Wydawnictwo Naukowe, Warszawa.
Zobacz w Google Scholar

Sink C. A., Mvududu N. H. (2010): Statistical Power, Sampling, and Effect Sizes: Three Keys to Research Relevancy. „Counseling Outcome Research and Evaluation”, 1, 2, s. 1–18.
Zobacz w Google Scholar

Spiegelhalter D. J., Abrams K. R., Myles J. P. (2004): Bayesian Approaches to Clinical Trials and Health-Care Evaluation. John Wiley and Sons, Chichester.
Zobacz w Google Scholar

Starek A., Szabla J., Szymczak W., Zapór L. (2006): Comparison of Acute Haematotoxicity of 2-mthoxyethanol, 2-ethoxyethanol and 2-butoxyethanol in Male Rats. „Acta Toxicologica”, 14, 1–2, s. 63–71.
Zobacz w Google Scholar

Sterne J. A. C. (2002): Teaching Hypothesis Tests – Time for Significant Change? „Statistics in Medicine”, 21, 7, s. 985–994.
Zobacz w Google Scholar

Szymczak W. (1999): Ryzyko choroby nowotworowej a narażenie na substancje chemiczne. Instytut Medycyny Pracy, Łódź.
Zobacz w Google Scholar

Szymczak W. (2018): Podstawy statystyki dla psychologów, wydanie trzecie rozszerzone. Wydawnictwo Difin, Warszawa.
Zobacz w Google Scholar

Tabachnick B. G., Fidell L. S. (2007): Using Multivariate Statistics, 5th ed. Pearson Education Inc., Boston.
Zobacz w Google Scholar

Thalheimer W., Cook S. (2002): How to Calculate Effect Sizes from Published Research Articles: A Simplified Methodology, http://work-learning.com/effect_sizes.htm (dostęp: 28.08.2012).
Zobacz w Google Scholar

Thompson Bill. (2007): The Nature of Statistical Evidence. Springer, New York.
Zobacz w Google Scholar

Thompson Bruce. (1994): The Concept of Statistical Significance Testing. „Practical Assessment, Research and Evaluation”, 4, 5, s. 1–3.
Zobacz w Google Scholar

Trafi ow D. (2003): Hypothesis Testing and Theory Evaluation at the Boundaries: Surprising Insights from Bayes’ Theorem. „Psychological Review”, 110, 3, s. 526–535.
Zobacz w Google Scholar

US EPA (1984) (U.S. Environmental Protection Agency): Health Eff cts Assessment for Benzo[a]pyrene. EPA 540/1-86-022. Environmental Criteria and Assessment Office, Cincinnati.
Zobacz w Google Scholar

US EPA (1988) (U.S. Environmental Protection Agency): Recommendations for and Documentation of Biological Values for Use in Risk Assessment. EPA 600/6-87-008. Office of Health and Environmental Assessment, Cincinnati.
Zobacz w Google Scholar

Valentine J. C., Cooper H. (2003): Effect Size Substantive Interpretation Guidelines: Issues in the Interpretation of Effect Sizes. What Works Clearinghouse, Washington.
Zobacz w Google Scholar

Volker M. A. (2006): Reporting Effect Size Estimates in School Psychology Research. „Psychology in the Schools”, 43, 6, s. 653–672.
Zobacz w Google Scholar

Vorapongsathorn T., Taejaroenkul S., Viwatwongkasem C. (2004): A Comparison of Type I Error and Power of Bartlett’s Test, Levene’s Test and Cochran’s Test under Violation of Assumptions. „Songklanakarin Journal of Science and Technology”, 26, 4, s. 537–547.
Zobacz w Google Scholar

Wasserman L. (2006): All of Nonparametric Statistics. Springer, New York.
Zobacz w Google Scholar

Welch B. L. (1951): On the Comparison of Several Mean Values: An Alternative Approach, „Biometrika”, 38, s. 330–336.
Zobacz w Google Scholar

Whittemore A. S. (1981): Sample Size for Logistic Regression with Small Response Probability. „Journal of the American Statistical Association”, 76, 373, s. 27–32.
Zobacz w Google Scholar

Wilcox R. R. (2002): Understanding the Practical Advantages of Modern ANOVA Methods. „Journal of Clinical Child and Adolescent Psychology”, 31, 3, s. 399–412.
Zobacz w Google Scholar

Williams R. H., Zimmerman D. W. (1989): Statistical Power Analysis and Reliability of Measurement. „Journal of General Psychology”, 116, 4, s. 359–369.
Zobacz w Google Scholar

Winer (1971): Statistical Principles in Experimental Design, 2nd ed. McGraw-Hill, Tokyo.
Zobacz w Google Scholar

Winer B. J., Brown D. R., Michels K. M. (1991): Statistical Principles in Experimental Design, 3rd ed. McGraw-Hill, Boston.
Zobacz w Google Scholar

Woolson R. F. (1987): Statistical Methods for the Analysis of Biomedical Data. John Wiley and Sons, New York.
Zobacz w Google Scholar

Wuensch K. L. (2015): Nonparametric Effect Size Estimators. Materiały dydaktyczne. East Carolina University Department of Psychology, http://core.ecu.edu/psyc/wuenschk/docs30/Nonparametric-EffectSize.pdf (dostęp: 16.06.2015).
Zobacz w Google Scholar

Young G. A., Smith R. L. (2005): Essentials of Statistical Inference. Cambridge University Press, Cambridge.
Zobacz w Google Scholar

Ziliak S. T., McCloskey D. N. (2009): The Cult of Statistical Significance. Presented at the Joint Statistical Meetings, August 3rd, Washington.
Zobacz w Google Scholar

Zimmerman D. W. (2004): A Note on Preliminary Tests of Equality of Variances. „British Journal of Mathematical and Statistical Psychology”, 57, s. 173–181.
Zobacz w Google Scholar

Zubrzycki S. (1970): Wykłady z rachunku prawdopodobieństwa i statystyki matematycznej. Państwowe Wydawnictwo Naukowe, Warszawa.
Zobacz w Google Scholar