BME100 f2013:W900 Group17 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: Jeremy Becker Role(s) Name: Luis Hernandez Role(s) Name: Alison Llave Role(s) Name: Naazaneen Maududi Role(s) LAB 3A WRITE-UP Descriptive Statistics In order to describe this data set, statistical values were taken from both the data set of values collected inside and the data set collected outside as well as the entire data set of the product test. In total, temperature readings from the inside and outside were taken by 15 groups for a total of 15 trials. For the subset of temperature readings taken with the thermometer within the inside data set the average reading was 97.57533333 degrees accross with a standard deviation of 0.778049244 and a standard error of 0.063527455. Then for the subset of temperature readings taken with the RAIIN sensor within the inside data set the average reading was 94.48466667 degrees with a standard deviation of 2.064618419 and a standard error of 0.168575388. Taking a T test comparing the thermometer readings set of results with the RAIIN sensor set of results the result was 1.22112E-39 which signifies that there is a high level of confidence in a difference existing within the two data sets. Furthermore, upon taking the Pearson's r correlation test it was found that there is only a positive correlation level of 0.165252944 between the temperature readings data set and the RAIIN sensor data set within the context of the larger inside data set. This is not a high correlation and so it is safe to conclude that the two data sets are significantly different. Now the subset of temperature readings taken with the thermometer within the outside data set the average reading was 97.49666667 degrees with a standard deviation of 0.897227262 and a standard error of 0.066875372. Then for the subset of temperature readings taken with the RAIIN sensor within the outside data set the average reading was 95.57944444 degrees with a standard deviation of 1.479494751 and a standard error of 0.110275028. Then taking a T test comparing the thermometer readings set of results with the RAIIN sensor set of results the result was 4.04259E-38 which signifies that there is a high level of confidence in a difference existing within the two data sets. Also, upon taking the Pearson's r correlation test it was found that there is only a positive correlation level of 0.225273129 between the temperature readings data set and the RAIIN sensor data set within the context of the larger inside data set. This is not a high correlation and so it is safe to conclude that the two data sets are significantly different. Now taking the outside data set and inside data set togetherer with the new set separation being solely the set of readings taken with the thermometer and the set of readings taken with the RAIIN sensor, a t-test result was found, 4.18844E-72, which again indicates that there is a significant difference between the readings taken with the thermometer and those taken with the RAIIN sensor. And with a correlation of only 0.167395055 found between these two sets, it is safe to further strengthen the conclusion that the readings taken with the two devices are not similar. Results Analysis (Perform inferential statistics described in assignment.) Summary/Discussion The results showed that there is a low p-value from the t-tests, showing that there exists a difference between the values collected by each device. There were various errors with the RAIIN device itself. Phone signal and interference from other phones gets in the way of measuring one person's body temperature. In addition, there should be a different name for the Bluetooth for each device so that the user won't confuse one device's Bluetooth with another. Another problem with RAIIN is its indecipherable, ambiguous instructions. It is difficult to determine where the sensor should be placed on the arm with just a simple picture. The instructions should be more specific so that the user gets the most accurate results. Lastly, the RAIIN sensor is easily affected by the temperature of the environment, increasing in its measurement of body temperature outside and decreasing inside. The difference was more apparent inside as the temperature inside a room is further from normal body temperature than outside in the sun. To fix this, there should be some type of insulation system so that the environment temperature doesn't affect the sensor readings. In conclusion, the RAIIN sensor iPhone app was found to be unreliable in measuring body temperature. (Please discuss the results and statistical analysis. State your conclusion as well as design flaws and recommendations.) LAB 3B WRITE-UP Target Population and Need Athletes Parents with young children so that they could monitor the body temperature of their kids Device Design Smaller, variety of colors, one color Inferential Statistics Graph