Statistics with Excel Examples Training
|Commitment||2 days, 7-8 hours a day.|
|How To Pass||Pass all graded assignments to complete the course.|
|User Ratings||Average User Rating 4.8 See what learners said|
|Delivery Options||Instructor-Led Onsite, Online, and Classroom Live|
Statistics with Excel Examples Training Course – Hands-on
Statistics with Excel Examples Training Course – Customize it
- We can adapt this training course to your group’s background and work requirements at little to no added cost.
- If you are familiar with some aspects of this training course, we can omit or shorten their discussion.
- We can adjust the emphasis placed on the various topics or build the training around the mix of technologies of interest to you (including technologies other than those included in this outline).
- If your background is nontechnical, we can exclude the more technical topics, include the topics that may be of special interest to you (e.g., as a manager or policy-maker), and present the training course in manner understandable to lay audiences.
Statistics with Excel Examples Training Course – Audience/Target Group
The target audience for this training course:
Statistics with Excel Examples Training – Course Content
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.