Multiple-analysis correlation study between human psychological variables and binary random events

• Main Author: Hartmut Grote
• Format: Article
• Language: English
• Published: SSE 2017-06-01
• Series: Journal of Scientific Exploration
• Online Access: http://journalofscientificexploration.org/index.php/jse/article/view/1095

Mind-matter interaction experiments have been progressing from targeting simple bias of random number generators to correlation studies between psychological and physical variables, carried out over multiple combinations of these. This paper reports on a new correlation study between human intention and the output of a binary random number generator. The study comprises a total of 720000 bits from 20 equal sessions each on a different human participant. Each participant spent 1 hour of time attempting to ’influence’ the outcome of the random number generator according to a pre-selected intention. During this time the participant was provided feedback on his/her performance by an analog mechanical display, with the needle of a galvanometric instrument moving to the left or right hand side of its current position, according to the instantaneous output of the random number generator. Psychological variables were obtained from the participants by a hardware dial ahead of each individual run and by a questionnaire before the participants first experimental session. Three types of data analysis were defined and tested before looking at the data, resembling a blind analysis technique. The first analysis looks at the distribution of hit rates from the 20 participants. A former study of this kind had found a significant result for this type of analysis. The second analysis tests for correlations between psychological variables obtained before each run and the hit rate of the corresponding subsequent run. The third analysis is a conceptual replication of von Lucadous correlation matrix method. It consists of multiple correlation tests between psychological and physical variables, which also can be interpreted as a multiple-analysis technique. The results of the study are p-values of p = 0.438, p = 0.703, and p = 0.0949 for the three analysis’ results to have occurred by chance under a null hypothesis. The combined p-value for these results is p = 0.315. While none of the pre-defined analysis results is found significant, a post-hoc variant of analysis 3 that includes the control data is significant with p = 0.012 to have occurred by chance, under a null hypothesis.