Statistical Analysis of Temperature Sensors
To simulate crop environmental changes (such day and night) while collecting data with temperature sensors, student samples are moved from inside under a heat lamp (left) to outside in the shade (right).Copyright 2016 Trent Kosel, North Dakota State University Fargo RET
Working as if they are engineers aiming to analyze and then improve data collection devices for precision agriculture, students determine how accurate temperature sensors are by comparing them to each other. Teams record soil temperature data during a class period while making changes to the samples to mimic real-world crop conditions—such as the addition of water and heat and the removal of the heat. Groups analyze their collected data by finding the mean, median, mode, and standard deviation. Then, the class combines all the team data points in order to compare data collected from numerous devices and analyze the accuracy of their recording devices by finding the standard deviation of temperature readings at each minute. By averaging the standard deviations of each minute’s temperature reading, students determine the accuracy of their temperature sensors. Students present their findings and conclusions, including making recommendations for temperature sensor improvements.
In every engineering field, researchers are continually innovating and improving existing devices. To do this, engineers collect data and rely on technology such as spreadsheets—like Microsoft® Excel® and Google Sheets—to help them analyze the data. Use of these programs provides valuable assistance in determining the accuracy and precision of real-world measurements collected in the field. Like engineers, in this activity students collect data and then use Google Sheets to analyze, interpret and draw conclusions from a dataset. For example, civil engineers, collect roadway elevation data in order to determine if the roadway profile meets current design standards.
After this activity, students should be able to:
- Interpret temperature data and communicate their findings.
- Find the mean, median, mode, range, and standard deviation of a dataset and its data subsets.
- Use statistical analysis to determine if a temperature sensor is accurate.
- Recognize maximum, minimum, mean, and mode of recorded temperatures based on graphs and data reports.