BME100 f2013:W900 Group10 L3: Difference between revisions
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==Descriptive Statistics== | ==Descriptive Statistics== | ||
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Revision as of 20:22, 27 September 2013
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 TEAMLAB 3A WRITE-UPDescriptive StatisticsBME100_Group10_statistics.jpg
Results
Analysis
Summary/DiscussionT-Test: Analysis of the data with a t-test shows that there is a significant correlation between data. The p-value is well below the value required to achieve 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 (not precise). 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 is much lower than one, indicating that the sensor does not report precise data. Standard Deviation: Because we took both control readings 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.
LAB 3B WRITE-UPTarget Population and Need
Device Design
Inferential Statistics
Graph
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