Undergraduate Curriculum Learning Objectives
MCEN 3037 - Experimental Design and Data Analysis
The purpose of this course is to prepare students to properly plan and carry out experiments, and to analyze the resulting data.
1. Measurement Fundamentals
- Understand the purposes of measurements: comparison with models, performance measurements, process/quality control, physical constant determination.
- The experiment system: transduction, signal conditioning, data acquisition and display.
- Understand the concepts of variability, error and resolution.
- Understand the purpose of calibration and the necessity for uncertainty and statistical data analysis.
- Understand different classes of measurement including stationary and transient systems.
2. Sampling and Descriptive Statistics, Probability and Probability Distributions
- Understand the concepts of population and sampling.
- Learn how to characterizing data sets, including mean and standard deviation.
- Learn what probability means and why distributions are useful.
- Study some common useful distributions.
3. Uncertainty in Experimental Measurements and its Propagation
- Distinguish between random and systematic uncertainties
- Compute uncertainty for the following circumstances: design stage, repeated measurements, single measurements, propagation of uncertainty.
- Apply objective outlier rejection techniques.
4. Confidence Intervals and Hypothesis Testing
- Learn about confidence intervals and how they can be sued to make probabilistic statements about data sets.
- Learn how to test hypotheses about the properties of populations based on the measured properties of samples.
5. Correlation, Regression and Classification
- Learn how to see if data is correlated.
- Carry out linear and non-linear regression.
- Learn some simple methods for classification.
6. Analysis of time series
- Learn about types of time series including stationary and non-stationary signals.
- Learn meaning of Fourier transform and how to carry Fast Fourier Transforms (FFT).