Factor analysis on farmer perception regarding soil health card in Surguja district of Chhattisgarh

Factor analysis is a useful tool for reducing large numbers of related variables in questionnaires, allowing for more manageable data for analysis. This study aimed to analyze a questionnaire's factor analysis to identify key variables determining perceptual satisfaction. The researchers used the determinant score, Kaiser-Meyer-Olkin, and Bartlett's Test of Sphericity to examine the likelihood of using factor analysis for the given data set. Factorability is assessed using Determinant score, Kaiser's Criterion and Scree test, and varimax orthogonal factor rotation method. Internal consistency is confirmed through Cronbach's alpha and composite reliability. The key variables were identifiedusing principal component analysis and the varimax orthogonal factor rotation approach. The study involved 150 farmers aged 28 to 61 years, with a total sample size of 150. The results showed that perception index, education, farming experience, annual income, extension contact, social interaction, innovativeness, exposure to media, and attitude towards science were the most significant factors affecting perceptual satisfaction. However, further research is needed to make firmer decisions on perception satisfaction factors to support farmers in a country. The convergent validity is established when average variance extracted is greater than or equal to 0.003. The results have revealed thatthe factor analysis not only allows detecting irrelevant items but will also allow extracting the valuable factors from the data set of a questionnaire survey.