Engineering Data Analysis Simulations
A collection of interactive 3D visualizations and simulations to help you master concepts in engineering data analysis.
Introduction to Data Analysis - Theory & Concepts
Overview of statistics in engineering, data collection methods, observational studies versus experiments, and sampling techniques.
Interactive Data Sampling Simulation
Descriptive Statistics - Theory & Concepts
Measures of central tendency, dispersion, position, skewness, and kurtosis, including grouped data.
Descriptive Statistics Explorer
Dataset (5)
The sum of all values divided by the number of values.
The middle value when the data is sorted.
The most frequently occurring value(s).
Conditional Probability - Theory & Concepts
Understanding how probabilities change when new information is available, including Bayes' Theorem and Independence.
Bayes' Theorem Explorer
Initial probability of a defect.
Probability test is positive when defect is present.
Probability test is positive when NO defect is present.
Posterior Probability
$P(D|T)$ - Probability it is actually defective given a positive test.
Tests of Hypotheses - Theory & Concepts
Null and alternative hypotheses, Type I/II errors, P-values, and tests for means, proportions, variances, and Goodness-of-Fit.
Hypothesis Testing Simulator
Analysis of Variance - Theory & Concepts
One-way ANOVA, Randomized Complete Block Design (RCBD), and post-hoc tests for comparing multiple means.
One-Way ANOVA Simulation
Adjust Group Means
F-Test Result
Critical F-value (): 3.35
Fail to Reject Null (No significant difference)
Statistical Quality Control - Theory & Concepts
Control charts for variables and attributes, process capability indices, and natural tolerance limits.
Control Chart () Simulator
Simulate a process and observe how control charts detect shifts (assignable causes). The limits are calculated based on the first half of the data (in-control).
Process Parameters
Applies a sudden shift to the mean halfway through the timeline.