STATISTICAL ANALYSIS OF RELATIVE HUMIDITY PATTERNS OF LOKOJA, NIGERIA
Abstract
This study focuses on the management of moisture and the monitoring of relative humidity (RH) patterns in order to maintain optimal conditions for finished products and human comfort. High humidity levels in homes can lead to issues such as the growth of dust mites, causing various irritations and allergies. The research emphasizes the importance of considering relative humidity values in the planning of tropical humid cities to create healthy and comfortable urban environments. Statistical measures and methods are employed to analyze the trend and project future relative humidity measurements. The study presents summary statistics of monthly relative humidity patterns, highlighting the variations across different months. Cumulative summaries indicate the overall range of relative humidity recorded over the years. Stationarity and normality tests are conducted to ensure the suitability of the data for modeling. Autocorrelation and partial autocorrelation analyses are used to identify potential ARIMA models for future humidity prediction. The information criteria aid in selecting the best-fitting ARIMA model, and the estimated coefficients are presented. Finally, predictions of relative humidity are provided for future dates. The study concludes that the ARIMA (9,1,1) model is suitable for predicting future relative humidity, and it highlights the importance of monitoring and managing relative humidity for maintaining optimal conditions.
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