Circular Pattern of Temperature Changes and Its Effect on Workers’ Attitude (A Case Study of the Federal Polytechnic Offa)
Asian Journal of Probability and Statistics · pp. 21–27 · Published 30 Aug 2022
10.9734/ajpas/2022/v19i330470Abstract
This study is to determine the effect of temperature on workplace attitude, which led to the investigation of a circular pattern of temperature changes. The idea of time series data being presented in circular form since time itself rotates around the circle of a clock was the moving force in studying the pattern and behaviour of air temperature to identify peak periods. The data on air temperature (0C) in Offa was collected monthly from 2016 to 2020 from a reliable online source tcktcktck.org which tally with an available short period of temperature recorded by the Metrological Garden of Science Laboratory Department, The Federal Polytechnic Offa. While the data on workers’ attitudes was from a questionnaire with an 8.5 reliability index. The study adopted a descriptive approach in the first instance, where responses from the questionnaire were in tabular form and the monthly means temperature in a circular plot before the application of cosinor regression to the original monthly temperature data for further examinations. The result of the circular plot indicated seasonality in the data because the monthly mean temperature differs, making the plot not perfectly circular. The presence of seasonality noticed in the cosinor plot was confirmed in the cosinor regression analysis as being significant at a 5% level of significance. The temperature amplitude from 2016 to 2020 had its peaks in February when 50.9% to 56% of workers are likely to experience fatigue (exhausted). The analysis for 2016 indicates temperature amplitude in Offa at 2.30C which peaks in early February. While in 2020, the temperature amplitude of 3.80C peaks at the beginning of February. The increase between 2016 and 2020 is due to climate change. The government and other stakeholders should provide facilities to reduce workers’ fatigue and do more about climate change.
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