A single trait factor, Calculation Speed, and five state factors, General Energy Level, Fatigue, Excitation, Rhythm and Volitional Tention, are extracted from a (30×30) correlation matrix obtained from a 30-minute performance of simple additions of two single-digit numbers in the Uchida-Kraepelin Psychodiagnostic Test. Factor scores are estimated by the multiple regression method and thirty error factors are calculated by substituting them into the formula of the factor analytic model. The distributions of common and error factor scores are completely normal with the zero mean and the unit variance in each. Discrepancies between the observed and synthetic data are found to be very small. A computer program in Fortran language is also prepared as an objective evaluation of the Uchida-Kraepelin Test.

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Factor analysis has been proposed and used as a method of statistical analysis of several measurements made on one individual repeatedly over a period time.
The purpose of this study was to analyse the intra-individual difference of a single person on the work curve of the Uchida-Kraepelin Psychodiagnostic Test by means of P-O-technique factorization. Furthermore, the purpose was to indicate to what extent the subjects' curve revealed. A unique pattern of factor loadings for each person and to what extent it was stable through the repetition of this test.
Our students sat as the subjects for 40 days in succession. The performance scores of each row were directly used for the raw scores. In P-technique, 30 variables (row 30 of this test) based upon the 40 day to day variation of intra individual differences were correlated, and in O-technique, 40 occasions based upon the 30 row to row variations were correlated. The principal component method of factorization was applied to these matrices of correlations.
The main findings were as follows.
1) The P-factors eliminated seemed to be identified with the factors already obtained by means of R-technique analysis. We might conclude that the greater part of the factor pattern was the same.
2) For the person indicating the higher contribution of factor I to all factor space in P-technique, the considerable stability of his work efficiency could be predicated over the entire time of the series.
3) On factor II and the following factors in P-technique, in spite of a smaller contribution to all factor space, the unique factor loading profiles of each person could be observed. This implied that the combination of these factor profiles made a characteristic feature of the work curve for each person.
4) In O-technique, we could eliminate several factors which indicated the patterns of a multiple work curve. This result implied that the unique curve of one individual was constructed by several different patterns of the work curve. But the higher loadings on factor I over the time of the series indicated that a rather dominant pattern of work curve could existed in one individual, and under the condition, in which factor I occupied the greater part of the contribution to all factor space, cosiderable stability of the work curve in one subject could be predicated.
5) About the factor structure, especially from the point of the factor loadings in factor I and II, we could observe that the work curve appearing in the first test was dissimilar to the curve of a subject having an inner consistency over the time of the series. This implied that, it was impossible to predict the immutability of one particular individual in the results of only the first test.

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The intra-individual distribution of errors in simple, monotonous, and repetitive tasks can be theoretically described by the Poisson distribution, since the occurrence of error in each S, being a rare and random probability event, will be the Bernoullian stochastic process. Moreover, the previous observations tell that the combined error distribution of a group of Ss fits very closely the Pólya-Eggenberger distribution. Then, the inter-individual distribution should be the Gamma distribution. 12 Ss were asked to add pairs of numbers in sequence as precisely and as quickly as possible, in a manner similar to the Uchida-Kraepelin test. The results indicate that the occurrence of errors in each S obeys the Poisson distribution, and the combined distribution is in fact the Pólya-Eggenberger distribution.

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本研究では, ホーニング音が作業者に与える影響について, ホーニング音環境下において内田クレペリン精神検査を行うことにより, 作業能率に及ぼす影響を定量的に調べた. その時の作業者の脳波を測定し, 作業者心理に及ぼす影響を把握した. 得られた結果をまとめると次のようになる. 高音圧のホーニング音環境下においても, の異常は定型崩れにとどまり, 被験者の心理状態が極めて異常な状態に陥ることはなかった. ホーニング音の心理的影響と作業能率への影響は, 主に「初頭努力の欠如」が現れ, 作業に対する取りかかりが悪くなった. ホーニング音が周期性のある騒音であることから, 時間の経過に伴いホーニング音の心理的影響は小さくなり, このため後期におけるその影響は小さかった. ホーニング音の影響の度合いには個人差があるが, 誤謬の過多などを生じるほどの大きな影響を及ぼすことはなかった.

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In overseas factories where labor costs are lower than in Japan, assembly work and other such production line operations rely heavily on manpower, so the quality and quantity of the products produced depend on the capabilities of the workers. To produce conforming articles speedily, workers have to be able to do repetitive work evenly on the production line. However, work abilities differ greatly from individual to individual. To hire the workers best suited for the tasks to be done and place them in the right jobs, a way of accurately testing their aptitudes, a paper-and-pencil test, for example, is necessary. In this study,to establish an effective autonomous way to find out if a person is suited for production work in advance in production sites throughout the world, we studied the use of the RT method to judge workers' working capabilities from the results of the Kraepelin general-purpose aptitude test. As a result, it was confirmed that worker capability can be determined at a level that is effective enough for practical use.

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