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Fundamentals of Statistics with Excel ExamplesCourse # E219January 27-28, 2015Columbia, Maryland$1290 (8:30am - 4:30pm)"Register 3 or More & Receive $100 00 eachOff The Course Tuition."SummaryThis two-day course covers the basics ofprobability and statistic analysis. The course isself-contained and practical, using Excel toperform the fundamental calculations. Studentsare encouraged to bring their laptops to workprovided Excel example problems. By the end ofthe course you will be comfortable with statisticalconcepts and able to perform and understandstatistical calculations by hand and using Excel.You will understand probabilities, statisticaldistributions, confidence levels and hypothesistesting, using tools that are available in Excel.Participants will receive a complete set of notesand the textbook Statistical Analysis with Excel.InstructorDr. Alan D. Stuart, Associate ProfessorEmeritus of Acoustics, Penn State,has over forty years in the field ofsound and vibration where heapplied statistics to the design ofexperiments and analysis of data.He has degrees in mechanicalengineering, electrical engineering,and engineering acoustics and has taught forover thirty years on both the graduate andundergraduate levels. For the last eight years, hehas taught Applied Statistics courses atgovernment and industrial organizationsthroughout the country.What You Will Learn• Working knowledge of statistical terms.• Use of distribution functions to estimateprobabilities.• How to apply confidence levels to real-worldproblems.• Applications of hypothesis testing.• Useful ways of summarizing statistical data.• How to use Excel to analyze statistical data.Course Outline1. Introduction to Statistics. Definition ofterms and concepts with simple illustrations.Measures of central tendency: Mean, mode,medium. Measures of dispersion: Variance,standard deviation, range. Organizing randomdata. Introduction to Excel statistics tools.2. Basic Probability. Probability based on:equally likely events, frequency, axioms.Permutations and combinations of distinctobjects. Total, joint, conditional probabilities.Examples related to systems engineering.3. Discrete Random Variables. Bernoulli trial.Binomial distributions. Poisson distribution.Discrete probability density functions andcumulative distribution functions. Excelexamples.4. Continuous Random Variables. Normaldistribution. Uniform distribution. Triangulardistribution. Log-normal distributions. Discreteprobability density functions and cumulativedistribution functions. Excel examples.5. Sampling Distributions. Sample sizeconsiderations. Central limit theorem. Student-tdistribution.6. Functions of Random Variables.(Propagation of errors) Sums and products ofrandom variables. Tolerance of mechanicalcomponents. Electrical system gains.7. System Reliability. Failure and reliabilitystatistics. Mean time to failure. Exponentialdistribution. Gamma distribution. Weibulldistribution.8. Confidence Level. Confidence intervals.Significance of data. Margin of error. Sample sizeconsiderations. P-values.9. Hypotheses Testing. Error analysis.Decision and detection theory. Operatingcharacteristic curves. Inferences of two-samplestesting, e.g. assessment of before and aftertreatments.10. Probability Plots and ParameterEstimation. Percentiles of data. Box whiskerplots. Probability plot characteristics. Excelexamples of Normal, Exponential and Weibullplots.11. Data Analysis. Introduction to linearregression, Error variance, Pearson linearcorrelation coefficients, Residuals pattern,Principal component analysis (PCA) of large datasets. Excel examples.12. Special Topics of Interest to Class.42 – Vol. 119 Register online at www.ATIcourses.com or call ATI at 888.501.2100 or 410.956.8805