#Correlation coefficient jmp software

On the one hand, there are commercial products that provide users with relatively easy-to-use devices and software that, most of the time, lacks the capability of hardware calibration but provides a direct output of concentration values in parts per million or similar via calibration by the manufacturer. Triggered by this development, smart home devices that make use of such sensors have entered the market, and different OEMs offer various solutions for how different types of sensors can be operated and how recorded data can be stored, accessed, and visualized. Since in some areas of the world, the information on air quality is either highly sparse or non-existent due to the high cost of traditional monitoring stations, the monitoring of outdoor and indoor air quality in urban areas through low-cost sensor networks has received increasing interest by manufacturers, communities, and scientists alike. In the past, several studies have shown the importance of air quality for the well-being and health of humans and the challenges that come with the assessment of air pollutants. Furthermore, we discuss sensor properties in regard to selectivity and long-term stability. We investigated the linear correlation between the sensor and reference data and thus calculated the coefficient of determination, the average and maximum residuals, and the correlation coefficient. Data analysis was carried out with the help of the basic functions in MS Excel. The process of evaluating the performance of the low-cost sensors was carried out and compared to similar studies. During co-location, concentrations of 0.20 ± 0.06 ppm, 7.14 ± 8.66 ppb, and 17.58 ± 9.90 ppb were measured for CO, NO, and NO 2, respectively. Five AirSensEUR units equipped with chemical sensors were placed next to a reference air quality measuring station in Vienna, Austria. In this study, we examined the feasibility of the application of such devices. Initiatives that focus on an open framework for air quality monitoring, such as the AirSensEUR project, offer competitive open source alternatives. However, most devices that utilize such sensors are based on proprietary hardware and software and, therefore, do not offer users the ability to replace sensors or interact with the hardware, software, and data in a meaningful way. Electrochemical low-cost sensors, suitable for the monitoring of different air quality parameters such as carbon monoxide or nitrogen dioxide levels, are viable tools for creating affordable handheld devices for short-term or dense air quality monitoring networks for long-term measurements and IoT applications.

Correlation coefficient jmp