Description

This two-day course, Fundamentals of Statistics with Excel Examples, covers the basics of statistics and statistical analysis, using Excel. Participants will be furnished the textbook Statistical Analysis with Excel for Dummies, by Joseph Schmuller Ph.D.

Course Outline:

Day 1:

1. Introduction to Statistics. Definition of terms and concepts with simple illustrations. Measures of central tendency: Mean, mode, medium. Measures of dispersion: Variance, standard deviation, range. Organizing random data. Introduction to Excel statistics tools.
2. Basic Probability. Probability based on: equally likely events, frequency, axioms. Permutations and combinations of distinct objects. Total, joint, conditional probabilities. Examples related to systems engineering.
3. Discrete Random Variables. Bernoulli trial. Binomial distributions. Poisson distribution. Discrete probability density functions and cumulative distribution functions. Excel examples.
4. Continuous random variables. Normal distribution. Uniform distribution. Triangular distribution. Log-normal distributions. Discrete probability density functions and cumulative distribution functions. Excel examples.
5. Sampling Distributions. Sample size considerations. Central limit theorem. Student-t distribution.

Day 2:

1. Functions of Random Variables. (Propagation of errors) Sums and products of random variables. Tolerance of mechanical components. Electrical system gains.
2. System Reliability. Failure and reliability statistics. Mean time to failure. Exponential distribution. Gamma distribution. Weibull distribution.
3. Confidence Level. Confidence intervals. Significance of data. Margin of error. Sample size considerations. P-values.
4. Hypotheses Testing. Error analysis. Decision and detection theory. Operating characteristic curves. Inferences of two-samples testing, e.g. assessment of before and after treatments.
5. Probability Plots and Parameter Estimation. Percentiles of data. Box whisker plots. Probability plot characteristics. Excel examples of Normal, Exponential and Weibull plots.
6. Regression Analysis. Introduction to linear regression, Error variance, Pearson linear correlation coefficient. Residuals pattern. Excel examples.
7. Other Topics of Interest to Class.

Instructor(s):

Dr. Alan D. Stuart,Associate Professor Emeritus of Acoustics, Penn State, has over forty years experience in the field of sound and vibration. He has degrees in mechanical engineering, electrical engineering, and engineering acoustics. For over thirty years he has taught courses on the Fundamentals of Acoustics, Structural Acoustics, Applied Acoustics, Noise Control Engineering, and Sonar Engineering on both the graduate and undergraduate levels as well as at government and industrial organizations throughout the country.

Contact this instructor (please mention course name in the subject line)