Introduction to Sensors and Data Analysis
ME 3263 Fall 2020
Labs 0 and 1 have a 3-page limit and 2-figure limit. Labs 2-6 have a 5-page limit and 4-figure limit. You can add additional pages and figures in an Appendix. The Appendix will not be graded, but you can use it to refer to data, methods, or diagrams that are relevant.
The report is scored 0-100. Over 70 is passing. Late submissions receive 10 point penalty per day.
Repository for laboratory notebooks
To access notebooks and interactive lab material, sign into github.uconn.edu, then follow the link to the class server.
ME3263 Introduction to Sensors and Data Analysis (Fall 2018)
Lab #0 - Introduction to the Student t-test
We use statistics to draw conclusions from limited data. No measurement is exact. Every measurement you make has two types of uncertainties, systematic and random. Systematic uncertainties come from faults in your assumptions or equipment. Random uncertainties are associated with unpredictable (or unforeseen at the time) experimental conditions. These can also be due to simplifications of your model. Here are some examples for caliper measurements:
In theory, all uncertainies could be accounted for by factoring in all physics in your readings. In reality, there is a diminishing return on investment for this practice. So we use some statistical insights to draw conclusions.
Labs 1-6 coming soon
check HuskyCT, Piazza, and ME3263 repo for updates!