Statistical analysis of climate measurements for resilient design in social housing

Abstract

Climate change is a progressive phenomenon that, although it can be mitigated, it cannot be stopped. As a consequence, the level of uncertainty is high to propose resilient design strategies to counteract its effects on people's comfort and health. Likewise, a limitation is the collection of information and access to climatic data of each place, so in the present work a cycle of temperature, relative humidity and wind speed measurements was proposed in a case study of social housing in the city of Tunja, Colombia. Thus, the objective of the article is to analyze and validate the reliability of the data collected on site. For this purpose, a descriptive statistical analysis of the information was carried out with tools such as Excel and PSPP version 1.4.1. As a result, it was found that, although the average level of reliability is acceptable, there are data below the minimum value of acceptability. It was concluded that descriptive statistics allows to know the margin of error to which the data are exposed and therefore reduce the uncertainty in the resilient design