Document |
Description |
Acrobat |
Mathcad 6.0 |

Comparative Statistics |
Statistical comparison of two data sets. Calculations include; mean, standard deviation (population and sample), and confidence intervals for each data set. Then comparison of means using t-test and pooled standard deviation. |
comparative_stats.pdf |
comparative_stats.mcd |

Descriptive Statistics |
Calculations include; mean, standard deviation (population and sample), confidence interval, and comparison to "true" value. |
descriptive_stats.pdf |
descriptive_stats.mcd |

Gaussian Distribution |
Properties of a gaussian distribution. Shape of distribution, area under distribution (integration and graphs). |
gaussian.pdf |
gaussian.mcd |

Calibration Example |
Calibration examples with descritpive information. Includes; linear regression, uncertainty of regression, unknown, graphs, and an example of error propagation. |
calibration_sample.pdf |
calibration_sample.mcd |

Calibration Lecture |
Based upon calibration example document, but with large fonts for lecture use. |
cal_lecture.pdf |
cal_lecture.mcd |

Linear Regression |
Linear Regression calculations for a calibration curve. Calculates line of best fit, uncertainty of regression, concentration of unknown (based upon response), and uncertainty in calculated concentration of unknown. Data is graphed. |
regression.pdf |
regression.mcd |

Multiple Regression |
Regression analysis using 1^{st}, 2^{nd}, 3^{rd}, 4^{th} and 5^{th} order regression. Regression analysis performed using matrix techniques. For each order data is graphed with regression fit. |
multiple_regression.pdf |
multiple_regression.mcd |

Standard Addition Example |
Document introduces standard addition using an easy to follow example (The M&M Mystery) and then shows calculations for a typical calibration problem. |
std_addition.pdf |
std_addition.mcd |

Signal Averaging and Filters |
Shows the effect of averaging and filtering on the observed signal. User may set signal, noise, averaging, and filter parameters. |
sigavg.pdf |
sigavg.mcd |