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Der Vergleich unabhängiger Stichproben gemessener Werte

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Book cover Angewandte Statistik

Zusammenfassung

Wissen wir einiges über die zu erwartende Heterogenität innerhalb der Grundgesamtheit, die wir untersuchen wollen, dann gibt es wirksamere Verfahren als die Auswahl zufälliger Stichproben. Wichtig ist die Verwendung geschichteter oder stratifizierter Stichproben; hier wird die Grundgesamtheit in relativ homogene Teilgrundgesamtheiten, Schichten oder Strata unterteilt, und zwar jeweils nach den Gesichtspunkten, die für das Studium der zu untersuchenden Variablen von Bedeutung sind. Geht es um die Voraussage von Wahlergebnissen, dann wird man die Stichprobe so wählen, daß sie ein verkleinertes Modell der Gesamtbevölkerung darstellt. Dabei werden in erster Linie Altersschichtung, das Verhältnis zwischen Männern und Frauen und die Einkommensgliederung berücksichtigt. So gliedern sich die Erwerbstätigen in der BRD nach der Stellung im Beruf etwa in 50% Arbeiter, 35% Angestellte, 8% Selbständige und 7% Beamte. Stratifizierung verteuert meist die Stichprobenerhebung, ist jedoch ein wichtiges Hilfsmittel. Der Stichprobenumfang pro Schicht ist umso kleiner, je kleiner die Schicht, je kleiner die Varianz und je teurer die Erhebung in der betreffenden Schicht ist.

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Literatur zu den einzelnen Kapiteln

  • Ailing, D. W.: Early decision in the Wilcoxon two-sample test. J. Amer. Statist. Assoc. 58 (1963), 713–720 [vgl. auch 69 (1974), 414-422].

    MathSciNet  Google Scholar 

  • Anscombe, F. J.: Rejection of outliers. Technometrics 2 (1960), 123–166 [vgl. auch 11 (1969), 527-550, 13 (1971), 110-112, 15 (1973), 385-404, 723-737].

    MathSciNet  MATH  Google Scholar 

  • Banerji, S.K.: Approximate confidence interval for linear functions of means of k populations when the population variances are not equal. Sankhya 22 (1960), 357 + 358.

    Google Scholar 

  • Bauer, R. K.: Der „Median-Quartile-Test“: Ein Verfahren zur nichtparametrischen Prüfung zweier unabhängiger Stichproben auf un spezifizierte Verteilungsunterschiede. Metrika 5 (1962), 1–16.

    MathSciNet  MATH  Google Scholar 

  • Behrens, W.-V.: Ein Beitrag zur Fehlerberechnung bei wenigen Beobachtungen. Landwirtschaftliche Jahrbücher 68 (1929), 807–837.

    Google Scholar 

  • Belson, I., and Nakano, K.: Using single-sided non-parametric tolerance limits and percentiles. Industrial Quality Control 21 (May 1965), 566–569.

    Google Scholar 

  • Bhapkar, V.P., and Deshpande, J. V.: Some nonparametric tests for multisample problems. Techno-metrics 10 (1968), 578–585.

    Google Scholar 

  • Birnbaum, Z. W., und Hall, R. A.: Small sample distribution for multisample statistics of the Smirnov type. Ann. Math. Stat. 31 (1960), 710–720 [vgl. auch 40 (1969), 1449-1466 sowie J. Amer. Statist. Assoc. 71 (1976), 757-762].

    MathSciNet  MATH  Google Scholar 

  • Bowker, A.H., and Lieberman, G.J.: Engineering Statistics. (Prentice-Hall) Englewood Cliffs, N.J. 1959.

    Google Scholar 

  • Box, G.E.P.: Non-normality and tests on variances. Biometrika 40 (1953), 318–335.

    MathSciNet  MATH  Google Scholar 

  • Box, G.E.P., and Andersen, S.L.: Permutation theory in the derivation of robust criteria and the study of departures from assumption. With discussion. J. Roy. Statist. Soc., Ser. B 17 (1955), 1–34.

    MATH  Google Scholar 

  • Boyd, W.C.: A nomogramm for the “Studenf”-Fisher t test. J. Amer. Statist. Assoc. 64 (1969), 1664–1667.

    Google Scholar 

  • Bradley, J.V.: Distribution-Free Statistical Tests. (Prentice-Hall, pp.388) Englewood Cliffs, N.J. 1968, Chapters 5 and 6.

    Google Scholar 

  • Bradley, R.A., Martin, D.C., and Wilcoxon, F.: Sequential rank-tests I. Monte Carlo studies of the two-sample procedure. Technometrics 7 (1965), 463–483.

    MathSciNet  Google Scholar 

  • Bradley, R.A., S.D. Merchant, and Wilcoxon, F.: Sequential rank tests II. Modified two-sample procedures. Technometrics 8 (1966), 615–623.

    MathSciNet  Google Scholar 

  • Breny, H.: L’état actuel du problème de Behrens-Fisher. Trabajos Estadist. 6 (1955), 111–131.

    MathSciNet  MATH  Google Scholar 

  • Burrows, G. L.: (1) Statistical tolerance limits — what are they? Applied Statistics 12 (1963), 133–144.

    Google Scholar 

  • (2) One-sided normal tolerance factors. New tables and extended use of tables. Mimeograph, Knolls Atomic Power Lab., General Electric Company, USA 1964.

    Google Scholar 

  • Cacoullos, T.: A relation between t and F-distributions. J. Amer. Statist. Assoc. 60 (1965), 528–531.

    MathSciNet  MATH  Google Scholar 

  • Cadwell, J.H.: (1) Approximating to the distributions of measures of dispersion by a power of chi-square. Biometrika 40 (1953), 336–346.

    MathSciNet  MATH  Google Scholar 

  • Cadwell, J.H.: (2) The statistical treatment of mean deviation. Biometrika 41 (1954), 12–18.

    MathSciNet  MATH  Google Scholar 

  • Carnal, H. and Riedwyl, H.: On a one-sample distribution-free test statistic V. Biometrika 59 (1972), 465–467 [vgl. auch Statist. Hefte 14 (1973), 193-202].

    MathSciNet  MATH  Google Scholar 

  • Chacko, V.J.: Testing homogeneity against ordered alternatives. Ann. Math. Statist. 34 (1963), 945–956 [vgl. auch 38 (1967), 1740-1752].

    MathSciNet  MATH  Google Scholar 

  • Chakravarti, I. M.: Confidence set for the ratio of means of two normal distributions when the ratio of variances is unknown. Biometrische Zeitschr. 13 (1971), 89–94.

    MathSciNet  MATH  Google Scholar 

  • Chun, D.: On an extreme rank sum test with early decision. J. Amer. Statist. Assoc. 60 (1965), 859–863.

    Google Scholar 

  • Cochran, W.G.: (1) Some consequences when the assumptions for the analysis of variance are not satisfied. Biometrics 3 (1947), 22–38.

    MathSciNet  Google Scholar 

  • Cochran, W.G.: (2) Modern methods in the sampling of human populations. Amer. J. Publ. Health 41 (1951), 647–653.

    Google Scholar 

  • Cochran, W.G.: (3) Query 12, Testing two correlated variances. Technometrics 7 (1965), 447–449.

    MathSciNet  Google Scholar 

  • Cochran, W.G., Mosteller, F., and Tukey, J.W.: Principles of sampling. J. Amer. Statist. Assoc. 49 (1954), 13–35.

    Google Scholar 

  • Cohen, J.: Statistical Power Analysis for the Behavioral Sciences (Acad. Pr., pp. 474) N. Y. 1977.

    Google Scholar 

  • Conover, W. J.: Two k-sample slippage tests. J. Amer. Statist. Assoc. 63 (1968), 614–626.

    Google Scholar 

  • Croarkin, Mary C.: Graphs for determining the power of Student’s t-test. J. Res. Nat. Bur. Stand. 66 B (1962), 59–70 (vgl. Errata: Mathematics of Computation 17 (1963), 83 [334]).

    MathSciNet  Google Scholar 

  • D’Agostino, R.B.: (1) Simple compact portable test of normality: Geary’s test revisited. Psychol. Bull. 74 (1970), 138–140 [vgl. auch 78 (1972), 262-265].

    Google Scholar 

  • D’Agostino, R.B.: (2) An omnibus test of normality for moderate and large size samples. Biometrika 58 (1971), 341–348 [vgl. auch 63 (1976), 143-147].

    MathSciNet  MATH  Google Scholar 

  • D’Agostino, R.B.: (3) Small sample probability points for the D test of normality. Biometrika 59 (1972), 219–221 [vgl. auch 60 (1973), 169-173, 613-622, 623-628, 61 (1974), 181-184, 185-189].

    Google Scholar 

  • Danziger, L., and Davis, S.A.: Tables of distribution-free tolerance limits. Ann. Math. Statist. 35 (1964), 1361–1365 [vgl. auch J. Qual. Technol. 7 (1975), 109-114].

    MathSciNet  MATH  Google Scholar 

  • Darling, D.A.: The Kolmogorov-Smirnov, Cramér-von Mises tests. Ann. Math. Statist. 28 (1957), 823–838.

    MathSciNet  MATH  Google Scholar 

  • Davies, O. L.: The Design and Analysis of Industrial Experiments. London 1956, p. 614.

    Google Scholar 

  • Dietze, Doris: t for more than two. Perceptual and Motor Skills 25 (1967), 589–602.

    Google Scholar 

  • Dixon, W. J.: (1) Analysis of extreme values. Ann. Math. Statist. 21 (1950), 488–506.

    Google Scholar 

  • Dixon, W. J.: (2) Processing data for outliers. Biometrics 9 (1953), 74–89.

    Google Scholar 

  • Dixon, W. J.: (3) Rejection of Observations. In Sarhan, A. E., and Greenberg, B. G. (Eds.): Contributions to Order Statistics. New York 1962, pp. 299-342.

    Google Scholar 

  • Dixon, W. J., and Tukey, J.W.: Approximate behavior of the distribution of Winsorized t (trimming/Winsorization 2). Technometrics10 (1968), 83–98 [vgl. auch Statist. Hefte 15 (1974), 157-1

    MathSciNet  Google Scholar 

  • Edington, E. S.: The assumption of homogeneity of variance for the /-test and nonparametric tests. Journal of Psychology 59 (1965), 177–179.

    Google Scholar 

  • Faulkenberry, G.D., and Daly, J.C.: Sample size for tolerance limits on a normal distribution. Technometrics 12 (1970), 813–821.

    MATH  Google Scholar 

  • Fisher, R. A.: (1) The comparison of samples with possibly unequal variances. Ann. Eugen. 9 (1939), 174–180.

    Google Scholar 

  • Fisher, R. A.: (2) The asymptotic approach to Behrens’s integral, with further tables for the d test of significance. Ann. Eugen. 11 (1941), 141–172.

    Google Scholar 

  • Fisher, R.A., and Yates, F.: Statistical Tables for Biological, Agricultural and Medical Research, 6th ed., London 1963.

    Google Scholar 

  • Geary, R.C.: (1) Moments of the ratio of the mean deviation to the standard deviation for normal samples. Biometrika 28 (1936), 295–305 (vgl. auch 27, 310/32, 34, 209/42 60, 613/622 sowie 61, 181/184).

    MATH  Google Scholar 

  • Geary, R.C.: (2) Tests de la normalité. Ann. Inst. Poincaré 15 (1956), 35–65.

    MathSciNet  MATH  Google Scholar 

  • Gibbons, J.D.: On the power of two-sample rank tests on the equality of two distribution functions. J. Roy. Statist. Soc. B 26 (1964), 293–304.

    MathSciNet  MATH  Google Scholar 

  • Glasser, G. J.: A distribution-free test of independence with a sample of paired observations. J. Amer. Statist. Assoc. 57 (1962), 116–133.

    MathSciNet  MATH  Google Scholar 

  • Goldman, A.: On the Determination of Sample Size. (Los Alamos Sei. Lab.; LA-2520; 1961) U.S. Dept. Commerce, Washington 25, D.C. 1961 [vgl. auch Biometrics 19 (1963), 465-477].

    Google Scholar 

  • Granger, C.W. J., and Neave, H.R.: A quick test for slippage. Rev. Inst. Internat. Statist. 36 (1968), 309–312.

    MATH  Google Scholar 

  • Graybill, F.A., and Connell, T.L.: Sample size required to estimate the ratio of variances with bounded relative error. J. Amer. Statist. Assoc. 58 (1963), 1044–1047.

    MathSciNet  MATH  Google Scholar 

  • Grubbs, F.E.: Procedures for detecting outlying observations in samples. Technometrics 11 (1969), 1–21 [vgl. auch 527-550 und 14 (1972), 847-854; 15 (1973), 429].

    Google Scholar 

  • Guenther, W.C.: Determination of sample size for distribution-free tolerance limits. The American Statistician 24 (Febr. 1970), 44–46.

    MathSciNet  Google Scholar 

  • Gurland, J., and McCullough, R.S.: Testing equality of means after a preliminary test of equality of variances. Biometrika 49 (1962), 403–417.

    MathSciNet  MATH  Google Scholar 

  • Guttmann, I.: Statistical Tolerance Regions. Classical and Bayesian. (Griffin, pp. 150) London 1970.

    Google Scholar 

  • Haga, T.: A two-sample rank test on location. Annals of the Institute of Statistical Mathematics 11 (1960), (211–219).

    MathSciNet  MATH  Google Scholar 

  • Hahn, G. J.: Statistical intervals for a normal population. Part I and II. J. Qual. Technol. 2 (1970), 115–125 and 195-206 [vgl. auch 9 (1977), 6-12, 5 (1973), 178-188, Biometrika 58 (1971), 323-332, J. Amer. Statist. Assoc. 67 (1972), 938-942 sowie Technometrics 15 (1973), 897-914].

    Google Scholar 

  • Halperin, M.: Extension of the Wilcoxon-Mann-Whitney test to samples censored at the same fixed point. J. Amer. Statist. Assoc. 55 (1960), 125–138 [vgl. Biometrika 52 (1965), 650-653].

    MathSciNet  MATH  Google Scholar 

  • Harmann, A. J.: Wilks’ tolerance limit sample sizes. Sankhya A 29 (1967), 215–218.

    Google Scholar 

  • Harter, H.L.: Percentage points of the ratio of two ranges and power of the associated test. Biometrika 50 (1963), 187–194.

    MathSciNet  MATH  Google Scholar 

  • Herrey, Erna M. J.: Confidence intervals based on the mean absolute deviation of a normal sample. J. Amer. Statist. Assoc. 60 (1965), 257–269 (vgl. auch 66 [1971], 187 + 188).

    MathSciNet  MATH  Google Scholar 

  • Hodges, J.L., Jr., and Lehmann, E.L.: (1) The efficiency of some nonparametric competitors of the t-test. Ann. Math. Statist. 27 (1956), 324–335.

    MathSciNet  MATH  Google Scholar 

  • Hodges, J.L., Jr., and Lehmann, E.L.: (2) A compact table for power of the t-test. Ann. Math. Statist. 39 (1968), 1629–1637.

    MathSciNet  MATH  Google Scholar 

  • (3) Basic Concepts of Probability and Statistics. 2nd ed. (Holden-Day, pp.401) San Francisco 1970.

    Google Scholar 

  • Hsiao, F. S. T.: The diagrammatical representation of confidence-interval estimation and hypothesis testing. The American Statistician 26 (Dec. 1972), 28+29.

    Google Scholar 

  • Jacobson, J. E.: The Wilcoxon two-sample statistic: tables and bibliography. J. Amer. Statist. Assoc. 58 (1963), 1086–1103.

    MathSciNet  MATH  Google Scholar 

  • Johnson,.N.L., and Welch, B.L.: Applications of the noncentral /-distribution. Biometrika 31 (1940), 362–389.

    MathSciNet  MATH  Google Scholar 

  • Kendall, M.G.: The treatment of ties in ranking problems. Biometrika 33 (1945), 239–251.

    MathSciNet  MATH  Google Scholar 

  • Kim, P. J.: On the exact and approximate sampling distribution of the two sample Kolmogorov-Smirnow criterion D mn mn. J. Amer. Statist. Assoc. 64 (1969), 1625–1637 [vgl. auch. 68 (1973), 994-997 und Ann. Math. Statist. 40 (1969), 1449-1466].

    MathSciNet  Google Scholar 

  • Kolmogoroff, A.N.: Sulla determinazione empirica di una legge di distribuzione. Giornale Istituto Italiano Attuari 4 (1933), 83–91.

    Google Scholar 

  • Krishnan, M.: Series representations of the doubly noncentral /-distribution. J. Amer. Statist. Assoc. 63 (1968), 1004–1012.

    MATH  Google Scholar 

  • Kruskal, W.H.: A nonparametric test for the several sampling problem. Ann. Math. Statist. 23 (1952), 525–540.

    MathSciNet  MATH  Google Scholar 

  • Kruskal, W.H., and Wallis, W. A.: Use of ranks in one-criterion variance analysis. J. Amer. Statist. Assoc. 47 (1952), 583–621 und

    MATH  Google Scholar 

  • Kruskal, W.H., and Wallis, W. A.: Use of ranks in one-criterion variance analysis. J. Amer. Statist. Assoc. 48 (1953), 907–911.

    MATH  Google Scholar 

  • Krutchkoff, R.G.: The correct use of the sample mean absolute deviation in confidence intervals for a normal variate. Technometrics 8 (1966), 663–674.

    MathSciNet  Google Scholar 

  • Laan, P. van der: Simple distribution-free confidence intervals for a difference in location. Philips Res. Repts. Suppl. 1970, No. 5, pp.158.

    Google Scholar 

  • Levene, H.: Robust tests for equality of variances. In I. Olkin and others (Eds.): Contributions to Probability and Statistics. Essays in Honor of Harold Hotelling, pp. 278-292. Stanford 1960 [vgl. J. Statist. Comput. Simul. 1 (1972), 183-194 u. J. Amer. Statist. Assoc. 69 (1974), 364-367].

    Google Scholar 

  • Lieberman, G.J.: Tables for one-sided statistical tolerance limits. Industrial Quality Control 14 (Apr. 1958), 7–9.

    Google Scholar 

  • Lienert, G.A., und Schulz, H.: Zum Nachweis von Behandlungswirkungen bei heterogenen Patientenstichproben. Ärztliche Forschung 21 (1967), 448–455.

    Google Scholar 

  • Lindgren, B.W.: Statistical Theory. (Macmillan; pp. 427) New York 1960, p. 401, Table VI.

    Google Scholar 

  • Lindley, D.V., East, D.A. and Hamilton, P.A.: Tables for making inferences about the variance of a normal distribution. Biometrika 47 (1960), 433–437.

    MathSciNet  MATH  Google Scholar 

  • Linnik, Y.V.: Latest investigation on Behrens-Fisher-problem. Sankhya 28 A (1966), 15–24.

    MathSciNet  Google Scholar 

  • Lord, E.: (1) The use of range in place of standard deviation in the /-test. Biometrika 34 (1947), 41–67.

    MathSciNet  MATH  Google Scholar 

  • Lord, E.: (2) Power of the modified t-test (u-test) based on range. Biometrika 37 (1950), 64–77.

    MathSciNet  MATH  Google Scholar 

  • Mace, A. E.: Sample-Size Determination. (Reinhold; pp.226) New York 1964.

    Google Scholar 

  • MacKinnon, W.J.: Table for both the sign test and distribution-free confidence intervals of the median for sample sizes to 1,000. J. Amer. Statist. Assoc. 59 (1964), 935–956.

    MathSciNet  MATH  Google Scholar 

  • Mann, H. B., and Whitney, D. R.: On a test of whether one of two random variables is stochastically larger than the other. Ann. Math. Statist. 18 (1947), 50–60.

    MathSciNet  MATH  Google Scholar 

  • Massey, F.J., Jr.: (1) The distribution of the maximum deviation between two sample cumulative step functions. Ann. Math. Statist. 22 (1951), 125–128.

    MathSciNet  MATH  Google Scholar 

  • Massey, F.J., Jr.: (2) Distribution table for the deviation between two sample cumulatives. Ann. Math. Statist. 23 (1952), 435–441.

    MathSciNet  MATH  Google Scholar 

  • McCullough, R.S., Gurland, J., and Rosenberg, L.: Small sample behaviour of certain tests of the hypothesis of equal means under variance heterogeneity. Biometrika 47 (1960), 345–353.

    MATH  Google Scholar 

  • McHugh, R.B.: Confidence interval inference and sample size determination. The American Statistician 15 (April 1961), 14–17.

    Google Scholar 

  • Mehta, J. S. and Srinivasan, R.: On the Behrens-Fisher problem. Biometrika 57 (1970), 649–655.

    MATH  Google Scholar 

  • Meyer-Bahlburg, H.F.L.: A nonparametric test for relative spread in k unpaired samples. Metrika 15 (1970), 23–29.

    MATH  Google Scholar 

  • Miller, L.H.: Table of percentage points of Kolmogorov statistics. J. Amer. Statist. Assoc. 51 (1956), 113–115.

    Google Scholar 

  • Milton, R.C.: An extended table of critical values for the Mann-Whitney (Wilcoxon) two-sample statistic. J. Amer. Statist. Assoc. 59 (1964), 925–934.

    MathSciNet  MATH  Google Scholar 

  • Minton, G.: (1) Inspection and correction error in data processing. J. Amer. Statist. Assoc. 64 (1969), 1256–1275 [vgl. auch 71 (1976), 17-35 sowie insbesondere Maria E. Gonzalez u. Mitarb., J. Amer. Statist. Assoc. 70 (Sept. 1975), Nr. 351, Part II, 1-23].

    Google Scholar 

  • Minton, G.: (2) Some decision rules for administrative applications of quality control. J. Qual. Technol. 2 (1970), 86–98 [vgl. auch 3 (1971), 6-17].

    Google Scholar 

  • Mitra, S.K.: Tables for tolerance limits for a normal population based on sample mean and range or mean range. J. Amer. Statist. Assoc. 52 (1957), 88–94.

    MathSciNet  MATH  Google Scholar 

  • Moore, P.G.: The two sample /-test based on range. Biometrika 44 (1957), 482–489.

    MathSciNet  MATH  Google Scholar 

  • Mosteller, F.: A k-sample slippage test for an extreme population. Ann. Math. Stat. 19 (1948), 58–65 (vgl. auch 21 [1950], 120-123).

    MathSciNet  MATH  Google Scholar 

  • Neave, H.R.: (1) A development of Tukeys quick test of location. J. Amer. Statist. Assoc. 61 (1966), 949–964.

    MathSciNet  MATH  Google Scholar 

  • Neave, H.R.: (2) Some quick tests for slippage. The Statistician 21 (1972), 197–208 [vgl. 22, 269-280].

    Google Scholar 

  • Neave, H.R., and Granger, C.W.J.: A Monte Carlo study comparing various two-sample tests for differences in mean. Technometrics 10 (1968), 509–522.

    Google Scholar 

  • Nelson, L.S.: (1) Nomograph for two-sided distribution-free tolerance intervals. Industrial Quality Control 19 (June 1963), 11–13.

    Google Scholar 

  • Nelson, L.S.: (2) Tables for Wilcoxon’s rank sum test in randomized blocks. J. Qual. Technol. 2 (Oct. 1970), 207–218.

    Google Scholar 

  • Neyman, J.: First Course in Probability and Statistics. New York 1950.

    Google Scholar 

  • Owen, D.B.: (1) Factors for one-sided tolerance limits and for variables sampling plans. Sandia Corporation, Monograph 607, Albuquerque, New Mexico, March 1963.

    Google Scholar 

  • Owen, D.B.: (2) The power of Student’s t-test. J. Amer. Statist. Assoc. 60 (1965), 320–333 and 1251.

    MathSciNet  MATH  Google Scholar 

  • Owen, D.B.: (3) A survey of properties and applications of the noncentral t-distribution. Technometrics 10 (1968), 445–478.

    MathSciNet  MATH  Google Scholar 

  • Owen, D.B., and Frawley, W.H.: Factors for tolerance limits which control both tails of the normal distribution. J. Qual. Technol. 3 (1971), 69–79.

    Google Scholar 

  • Parren, J.L. Van der: Tables for distribution-free confidence limits for the median. Biometrika 57 (1970), 613–617.

    MATH  Google Scholar 

  • Pearson, E.S., and Stephens, M.A.: The ratio of range to standard deviation in the same normal sample. Biometrika 51 (1964), 484–487.

    MathSciNet  MATH  Google Scholar 

  • Penfleld, D.A., and McSweeney, Maryellen: The normal scores test for the two-sample problem. Psychological Bull. 69 (1968), 183–191.

    Google Scholar 

  • Peters, C.A.F.: Über die Bestimmung des wahrscheinlichen Fehlers einer Beobachtung aus den Abweichungen der Beobachtungen von ihrem arithmetischen Mittel. Astronomische Nachrichten 44 (1856), 30+31.

    Google Scholar 

  • Pierson, R.H.: Confidence interval lengths for small numbers of replicates. U.S. Naval Ordnance Test Station. China Lake, Calif. 1963.

    Google Scholar 

  • Pillai, K.C.S., and Buenaventura, A.R.: Upper percentage points of a substitute F-ratio using ranges. Biometrika 48 (1961), 195+196.

    MathSciNet  Google Scholar 

  • Potthoff, R.F.: Use of the Wilcoxon statistic for a generalized Behrens-Fisher problem. Ann. Math. Stat. 34 (1963), 1596–1599.

    MathSciNet  MATH  Google Scholar 

  • Pratt, J. W.: Robustness of some procedures for the two-sample location problem. J. Amer. Statist. Assoc. 59 (1964), 665–680.

    MathSciNet  Google Scholar 

  • Proschan, F.: Confidence and tolerance intervals for the normal distribution. J. Amer. Statist. Assoc. 48 (1953), 550–564.

    MathSciNet  MATH  Google Scholar 

  • Quesenberry, C.P., and David, H.A.: Some tests for outliers. Biometrika 48 (1961), 379–390.

    MATH  Google Scholar 

  • Raatz, U.: Eine Modifikation des White-Tests bei großen Stichproben. Biometrische Zeitschr. 8 (1966), 42–54 [vgl. auch Arch. ges. Psychol. 118 (1966), 86-92].

    Google Scholar 

  • Reiter, S.: Estimates of bounded relative error for the ratio of variances of normal distributions. J. Amer. Statist. Assoc. 51 (1956), 481–488.

    MathSciNet  MATH  Google Scholar 

  • Rosenbaum, S.: (1) Tables for a nonparametric test of dispersion. Ann. Math. Statist. 24 (1953), 663–668.

    MathSciNet  MATH  Google Scholar 

  • Rosenbaum, S.: (2) Tables for a nonparametric test of location. Ann. Math. Statist. 25 (1954), 146–150.

    MathSciNet  MATH  Google Scholar 

  • Rosenbaum, S.: (3) On some two-sample non-parametric tests. J. Amer. Statist. Assoc. 60 (1965), 1118–1126.

    MathSciNet  Google Scholar 

  • Rytz, C.: Ausgewählte parameterfreie Prüfverfahren im 2-und k-Stichproben-Fall. Metrika 12 (1967), 189–204 und.

    Google Scholar 

  • Rytz, C.: Ausgewählte parameterfreie Prüfverfahren im 2-und k-Stichproben-Fall. Metrika 13 (1968), 17–71.

    Google Scholar 

  • Sachs, L.: Statistische Methoden. 5. neubearb. Aufl. (Springer, 124 S.) Berlin, Heidelberg, New York 1982, S. 52-55, 72 und 95-97.

    Google Scholar 

  • Sandelius, M.: A graphical version of Tukey’s confidence interval for slippage. Technometrics 10 (1968), 193+194.

    MathSciNet  Google Scholar 

  • Saw, J. G.: A non-parametric comparison of two samples one of which is censored. Biometrika 53 (1966), 599–602 [vgl. auch 52 (1965), 203-223 und 56 (1969), 127-132].

    MathSciNet  MATH  Google Scholar 

  • Scheffé, H.: Practical solutions of the Behrens-Fisher problem. J. Amer. Statist. Assoc. 65 (1970), 1501–1508 [vgl. auch 66 (1971), 605-608 und J. Pfanzagl, Biometrika 61 (1974), 39-47, 647].

    MathSciNet  MATH  Google Scholar 

  • Scheffé, H., and Tukey, J.W.: Another Beta-Function Approximation. Memorandum Report 28, Statistical Research Group, Princeton University 1949.

    Google Scholar 

  • Shorack, G.R.: Testing and estimating ratios of scale parameters. J. Amer. Statist. Assoc. 64 (1969), 999–1013.

    Google Scholar 

  • Siegel, S.: Nonparametric Statistics for the Behavioral Sciences. New York 1956, p. 278.

    Google Scholar 

  • Siegel, S., and Tukey, J. W.: A nonparametric sum of ranks procedure for relative spread in unpaired samples. J. Amer. Statist. Assoc. 55 (1960), 429–445.

    MathSciNet  Google Scholar 

  • Smirnoff, N. W.: (1) On the estimation of the discrepancy between empirical curves of distribution for two independent samples. Bull. Université Moskov. Ser. Internat., Sect A 2 (2) (1939), 3–8.

    MathSciNet  Google Scholar 

  • Smirnoff, N. W.: (2) Tables for estimating the goodness of fit of empirical distributions. Ann. Math. Statist. 19 (1948), 279–281.

    Google Scholar 

  • Stammberger, A.: Über einige Nomogramme zur Statistik. (Fertigungstechnik und Betrieb 16 [1966], 260-263 oder) Wiss. Z. Humboldt-Univ. Berlin, Math.-Nat. R. 16 (1967), 86–93.

    Google Scholar 

  • Sukhatme, P.V.: On Fisher and Behrens’s test of significance for the difference in means of two normal samples. Sankhya 4 (1938), 39–48.

    Google Scholar 

  • Szameitat, K., und Koller, S.: Über den Umfang und die Genauigkeit von Stichproben. Wirtschaft u. Statistik 10 NF (1958), 10–16.

    Google Scholar 

  • Szameitat, K., und K.-A. Schäffer: (1) Fehlerhaftes Ausgangsmaterial in der Statistik und seine Konsequenzen für die Anwendung des Stichprobenverfahrens. Allgemein. Statist. Arch. 48 (1964), 1–22.

    Google Scholar 

  • Szameitat, K., und K.-A. Schäffer: (2) Kosten und Wirtschaftlichkeit von Stichprobenstatistiken. Allgem. Statist. Arch. 48 (1964), 123–146.

    Google Scholar 

  • Szameitat, K., and R. Deininger: Some remarks on the problem of errors in statistical results. Bull. Int. Statist. Inst. 42, I (1969), 66–91 [vgl. 41, II (1966), 395-417 u. Allgem. Statist. Arch. 55 (1971), 290-303].

    Google Scholar 

  • Thöni, H.P.: Die nomographische Lösung des t-Tests. Biometrische Zeitschr. 5 (1963), 31–50.

    Google Scholar 

  • Thompson jr., W.A., and Endriss, J.: The required sample size when estimating variances. The American Statistician 15 (June 1961), 22+23.

    Google Scholar 

  • Thompson, W.A., and Willke, T.A.: On an extreme rank sum test for outliers. Biometrika 50 (1963), 375–383 [vgl. auch J. Qual. Technol. 9 (1977), 38-41 u. 208].

    MathSciNet  MATH  Google Scholar 

  • Tiku, M.L.: Tables of the power on the F-test. J. Amer. Statist. Assoc. 62 (1967), 525–539 [vgl. auch 63 (1968), 1551 u. 66 (1971), 913-916 sowie 67 (1972), 709 + 710].

    MathSciNet  MATH  Google Scholar 

  • Trickett, W.H., Welch, B.L., and James, G.S.: Further critical values for the two-means problem. Biometrika 43 (1956), 203–205.

    MathSciNet  MATH  Google Scholar 

  • Tukey, J. W.: (1) A quick, compact, two-sample test to Duckworth’s specifications. Technometrics 1 (1959), 31–48.

    MathSciNet  Google Scholar 

  • (2) A survey of sampling from contaminated distributions. In I. Olkin and others (Eds.): Contributions to Probability and Statistics. Essays in Honor of Harold Hotelling. pp. 448-485, Stanford 1960.

    Google Scholar 

  • Tukey, J. W.: (3) The future of data analysis. Ann. Math. Statist. 33 (1962), 1–67, 812.

    MathSciNet  MATH  Google Scholar 

  • Waerden, B. L., van der: Mathematische Statistik. 2. Aufl., Berlin-Heidelberg-New York 1965, S. 285/95, 334/5, 348/9 [vgl. X-Test Schranken: Math. Operat-forsch. u. Statist. 3 (1972), 389-400].

    Google Scholar 

  • Walter, E.: Über einige nichtparametrische Testverfahren. Mitteilungsbl. Mathem. Statist. 3 (1951), 31–44 und 73-92.

    MATH  Google Scholar 

  • Weiler, H.: A significance test for simultaneous quantal and quantitative responses. Technometrics 6 (1964), 273–285.

    MathSciNet  Google Scholar 

  • Weiling, F.: Die Mendelschen Erbversuche in biometrischer Sicht. Biometrische Zeitschr. 7 (1965), 230–262, S. 240.

    Google Scholar 

  • Weir, J.B. de V.: Significance of the difference between two means when the population variances may be unequal. Nature 187 (1960), 438.

    MATH  Google Scholar 

  • Weissberg, A., and Beatty, G. H.: Tables of tolerance-limit factors for normal distributions. Technometrics 2 (1960), 483–500 [vgl. auch J. Amer. Statist. Assoc. 52 (1957), 88-94 u. 64 (1969), 610-620 sowie Industrial Quality Control 19 (Nov. 1962), 27 + 28].

    MathSciNet  MATH  Google Scholar 

  • Welch, B. L.: (1) The significance of the difference between two means when the population variances are unequal. Biometrika 29 (1937), 350–361.

    Google Scholar 

  • Welch, B. L.: (2) The generalization of “Student’s” problem when several different population variances are involved. Biometrika 34 (1947), 28–35.

    MathSciNet  MATH  Google Scholar 

  • Wenger, A.: Nomographische Darstellung statistischer Prüfverfahren. Mitt. Vereinig. Schweizer. Versicherungsmathematiker 63 (1963), 125–153.

    MathSciNet  MATH  Google Scholar 

  • Westlake, W. J.: A one-sided version of the Tukey-Duckworth test. Technometrics 13 (1971), 901–903.

    Google Scholar 

  • Wilcoxon, F.: Individual comparisons by ranking methods. Biometrics 1 (1945), 80–83.

    Google Scholar 

  • Wilcoxon, F., Katti, S.K., and Wilcox, Roberta A.: Critical Values and Probability Levels for the Wilcoxon Rank Sum Test and the Wilcoxon Signed Rank Test. Lederle Laboratories, Division Amer. Cyanamid Company, Pearl River, New York, August 1963.

    Google Scholar 

  • Wilcoxon, F., Rhodes, L.J., and Bradley, R.A.: Two sequential two-sample grouped rank tests with applications to screening experiments. Biometrics 19 (1963), 58–84 (vgl. auch 20 [1964], 892).

    MathSciNet  MATH  Google Scholar 

  • Wilcoxon, F., and Wilcox, Roberta A.: Some Rapid Approximate Statistical Procedures. Lederle Laboratories, Pearl River, New York 1964.

    Google Scholar 

  • Wilks, S.S.: (1) Determination of sample sizes for setting tolerance limits. Ann. Math. Statist. 12 (1941), 91–96 [vgl. auch The American Statistician 26 (Dec. 1972), 21].

    MathSciNet  Google Scholar 

  • Wilks, S.S.: (2) Statistical prediction with special reference to the problem of tolerance limits. Ann. Math. Statist. 13 (1942), 400–409.

    MathSciNet  MATH  Google Scholar 

  • Winne, D.: (1) Zur Auswertung von Versuchsergebnissen: Der Nachweis der Übereinstimmung zweier Versuchsreihen. Arzneim.-Forschg. 13 (1963), 1001–1006.

    Google Scholar 

  • Winne, D.: (2) Zur Planung von Versuchen: Wieviel Versuchseinheiten? Arzneim.-Forschg. 18 (1968), 1611–1618.

    Google Scholar 

Lehrbücher der Stichprobentheorie

  • Billeter, E.P.: Grundlagen der repräsentativen Statistik. Stichprobentheorie und Versuchsplanung. (Springer, 160 S.) Wien und New York 1970.

    Google Scholar 

  • Cochran, W.G.: Sampling Techniques. 2nd ed., New York 1963 (Übersetzung erschien 1972 bei de Gruyter, Berlin und New York; 3rd. ed. 1977).

    Google Scholar 

  • Conway, Freda: Sampling: An Introduction for Social Scientists. (G. Allen and Unwin, pp.154) London 1967.

    Google Scholar 

  • Deming, W.E.: Sampling Design in Business Research. London 1960.

    Google Scholar 

  • Desabie, J.: Théorie et Pratique des Sondages. Paris 1966.

    Google Scholar 

  • Raj, D.: (1) Sampling Theory. (McGraw-Hill, pp.225) New York 1968.

    Google Scholar 

  • (2) The Design of Sample Surveys. (McGraw-Hill, pp.416) New York 1972.

    Google Scholar 

  • Hansen, M.H., Hurwitz, W.N., and Madow, W.G.: Sample Survey Methods and Theory. Vol. I and II (Wiley, pp.638, 332) New York 1964.

    Google Scholar 

  • Kellerer, H.: Theorie und Technik des Stichprobenverfahrens. Einzelschriften d. Dtsch. Statist. Ges. Nr. 5, 3. Aufl., München 1963.

    Google Scholar 

  • Kish, L.: Survey Sampling. New York 1965 [vgl. auch J. Roy. Statist. Soc. B 36 (1974), 1-37, A 139 (1976), 183-204 and Dalenius, T., Int. Stat. Rev. 45 (1977), 71-89, 181-197, 303-317].

    Google Scholar 

  • Menges, G.: Stichproben aus endlichen Gesamtheiten. Theorie und Technik, Frankfurt/Main 1959.

    MATH  Google Scholar 

  • Murthy, M.N.: Sampling Theory and Methods. (Statistical Publ. Soc., pp.684) Calcutta 1967.

    Google Scholar 

  • Parten, Mildred: Surveys, Polls, and Samples: Practical Procedures. (Harper and Brothers, pp. 624) New York 1969 (Bibliography pp. 537/602 [vgl. auch Struening, E. L. and Marcia Guttentag (Eds.): Handbook of Evaluation Research. (Sage; pp.696) London 1975]).

    Google Scholar 

  • Sampford, M.R.: An Introduction to Sampling Theory with Applications to Agriculture. London 1962.

    Google Scholar 

  • Statistisches Bundesamt Wiesbaden (Hrsg.): Stichproben in der amtlichen Statistik. Stuttgart 1960 Stenger, H.: Stichprobentheorie. (Physica-Vlg., 228 S.) Würzburg 1971.

    Google Scholar 

  • Stuart, A.: Basic Ideas of Scientific Sampling. (Griffin, pp.99) London 1969.

    Google Scholar 

  • Sukhatme, P.V., and Sukhatme, B.V.: Sampling Theory of Surveys With Applications. 2nd rev. ed. (Iowa State Univ. Press; pp.452) Ames, Iowa 1970.

    Google Scholar 

  • United Nations: A short Manual on Sampling. Vol. I. Elements of Sample Survey Theory. Studies in Methods Ser. F No. 9, rev. 1, New York 1972.

    Google Scholar 

  • Yamane, T.: Elementary Sampling Theory. (Prentice-Hall, pp.405) Englewood Cliffs, N.J. 1967.

    Google Scholar 

  • Zarkovich, S.S.: Sampling Methods and Censuses. (Fao, UN, pp.213) Rome 1965.

    Google Scholar 

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Sachs, L. (1984). Der Vergleich unabhängiger Stichproben gemessener Werte. In: Angewandte Statistik. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-05748-3_6

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