BME100 f2013:W900 Group10 L3

BME 100 Fall 2013	Home People Lab Write-Up 1 | Lab Write-Up 2 | Lab Write-Up 3 Lab Write-Up 4 | Lab Write-Up 5 | Lab Write-Up 6 Course Logistics For Instructors Photos Wiki Editing Help
OUR TEAM Name: Barrett Anderies Name: Liam Williams Role(s) Name: student Role(s) Name: student Role(s) Name: student Role(s) Name: student Role(s) LAB 3A WRITE-UP Descriptive Statistics In this experiment, two medical devices were used to collect body temperature data. The first device used was the RAIING Medical Company Wireless Thermometer (Model: WTM-BT30-T). The other medical device used was a standard oral thermometer, the accepted standard for reading body temperature, against which we will compare the RAIING Wireless Thermometer. The table below shows the average, standard deviation, end point #'s and standard errors of body temperature for each medical device labeled Oral and Sensor (RAIING Wireless Thermometer). Results Analysis Summary/Discussion T-Test: Analysis of the data with a t-test shows that there is a significant correlation between data. The p-value is well below 0.05 which is the maximum value to show significance. Pearson's r: Pearson's r coefficient shows that the data has little linear correlation. This implies that that, when compared with the readings from the accepted measurement device (oral thermometer), the sensor reports widely varying and inconsistent temperature readings showing how imprecise it was in reality. Trend Line: If the sensor were to report precise data, we would expect the slope of the trend line to be close to one. The slope of our trend line was closer to 0, indicating that the sensor does not report precise data. Standard Deviation: Because we took both control readings (stationary in consistent environment) and non-control readings (outside, moving, exercise, etc.) we would expect the data of each group to have some standard deviation. Furthermore, if both devices were to precisely report data, we would expect the standard deviation of both groups to be almost the same. This is not the case with our data, indicating that one device (in this case the sensor) reports data with more variation. Summary From all of our collected data from both the thermometer and RAIING we concluded that the sensor was not a reliable source for determining temperature. Recommendations as How to Improve the Device Recommend a different wireless system be used other than bluetooth. Our team experience difficulties syncing the RAIING Wireless Thermometer to the iPhone app used to record the body temperature data LAB 3B WRITE-UP Target Population and Need Device Design Inferential Statistics Graph