Statistics with Excel Examples Training
Statistics with Excel Examples Training Course Description
This two-day Statistics with Excel Examples Training, Fundamentals of Statistics with Excel Examples, covers the basics of statistics and statistical analysis, using Excel.
With onsite Training, courses can be scheduled on a date that is convenient for you, and because they can be scheduled at your location, you don’t incur travel costs and students won’t be away from home. Onsite classes can also be tailored to meet your needs. You might shorten a 5-day class into a 3-day class, or combine portions of several related courses into a single course, or have the instructor vary the emphasis of topics depending on your staff’s and site’s requirements.
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.
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.
Discrete Random Variables. Bernoulli trial. Binomial distributions. Poisson distribution. Discrete probability density functions and cumulative distribution functions. Excel examples.
Continuous random variables. Normal distribution. Uniform distribution. Triangular distribution. Log-normal distributions. Discrete probability density functions and cumulative distribution functions. Excel examples.
Sampling Distributions. Sample size considerations. Central limit theorem. Student-t distribution.
Functions of Random Variables. (Propagation of errors) Sums and products of random variables. Tolerance of mechanical components. Electrical system gains.
System Reliability Failure and reliability statistics. Mean time to failure. Exponential distribution. Gamma distribution. Weibull distribution.
Confidence Level. Confidence intervals. Significance of data. Margin of error. Sample size considerations. P-values.
Hypotheses Testing. Error analysis. Decision and detection theory. Operating characteristic curves. Inferences of two-samples testing, e.g. assessment of before and after treatments.
Probability Plots and Parameter Estimation. Percentiles of data. Box whisker plots. Probability plot characteristics. Excel examples of Normal, Exponential and Weibull plots.
Regression Analysis. Introduction to linear regression, Error variance, Pearson linear correlation coefficient. Residuals pattern. Excel examples.
Other Topics of Interest to Class.
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