Systems Engineering - ATI

Fundamentals of Statistics with Excel Examples
February 8-9, 2011
Beltsville, Maryland
$1040 (8:30am - 4:30pm)
NEW!
"Register 3 or More & Receive $100 00 each
Off The Course Tuition."
Summary
This two-day course covers the basics of
probability and statistic analysis. The course is selfcontained
and practical, using Excel to perform the
fundamental calculations. Students are encouraged
to bring their laptops to work provided Excel
example problems. By the end of the course you will
be comfortable with statistical concepts and able to
perform and understand statistical calculations by
hand and using Excel. You will understand
probabilities, statistical distributions, confidence
levels and hypothesis testing, using tools that are
available in Excel. Participants will receive a
complete set of notes and the textbook Statistical
Analysis with Excel.
Instructor
Dr. Alan D. Stuart, Associate Professor Emeritus
of Acoustics, Penn State, has over forty years in the
field of sound and vibration where he applied
statistics to the design of experiments and analysis
of data. He has degrees in mechanical engineering,
electrical engineering, and engineering acoustics
and has taught for over thirty years on both the
graduate and undergraduate levels. For the last
eight years, he has taught Applied Statistics courses
at government and industrial organizations
throughout the country.
What You Will Learn
• Working knowledge of statistical terms.
• Use of distribution functions to estimate
probabilities.
• How to apply confidence levels to real-world
problems.
• Applications of hypothesis testing.
• Useful ways of summarizing statistical data.
• How to use Excel to analyze statistical data.
Course Outline
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.
6. Functions of Random Variables.
(Propagation of errors) Sums and products of
random variables. Tolerance of mechanical
components. Electrical system gains.
7. System Reliability. Failure and reliability
statistics. Mean time to failure. Exponential
distribution. Gamma distribution. Weibull
distribution.
8. Confidence Level. Confidence intervals.
Significance of data. Margin of error. Sample size
considerations. P-values.
9. Hypotheses Testing. Error analysis. Decision
and detection theory. Operating characteristic
curves. Inferences of two-samples testing, e.g.
assessment of before and after treatments.
10. Probability Plots and Parameter
Estimation. Percentiles of data. Box whisker plots.
Probability plot characteristics. Excel examples of
Normal, Exponential and Weibull plots..
11. Data Analysis. Introduction to linear
regression, Error variance, Pearson linear
correlation coefficients, Residuals pattern, Principal
component analysis (PCA) of large data sets.
Excel examples.
12. Special Topics of Interest to Class.
Register online at www.ATIcourses.com or call ATI at 888.501.2100 or 410.956.8805 Vol. 104 – 29