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Bootstrapping: Measuring the Uncertainty in Inspection Results

Bootstrapping: Measuring the Uncertainty in Inspection Results

by Dr. Shawn P. Capser, Ph.D., P.E., PStat®, CRE | Oct 16, 2026 | Statistical Analysis

Consider a litigation matter involving allegations of defects among a large population of units. The units might be homes within a residential development, manufactured products, building components, insurance claims, or other items relevant to the matter. Inspecting...
Surviving a Daubert Challenge: The Role of a Statistical Expert Witness

Surviving a Daubert Challenge: The Role of a Statistical Expert Witness

by Dr. Shawn P. Capser, Ph.D., P.E., PStat®, CRE | Sep 1, 2026 | Statistical Analysis

Preparing Expert Testimony to Withstand a Daubert Challenge In many product liability, manufacturing defect, and warranty disputes, expert testimony plays an important role in explaining technical evidence and supporting opinions regarding product performance,...
Statistical Expert Witness for Product Liability: Ensuring Defensible Analysis

Statistical Expert Witness for Product Liability: Ensuring Defensible Analysis

by Dr. Shawn P. Capser, Ph.D., P.E., PStat®, CRE | Jul 13, 2026 | Statistical Analysis

The main takeaway: In complex product liability lawsuits, relying solely on “common sense” or traditional engineering testimony isn’t enough. Legal teams need a statistical expert witness to turn messy data into a defensible, objective narrative that...
Simpson’s Paradox: When the Data Appears to Change Its Mind

Simpson’s Paradox: When the Data Appears to Change Its Mind

by Dr. Shawn P. Capser, Ph.D., P.E., PStat®, CRE | Jun 26, 2026 | Statistical Analysis

One of the more surprising concepts in statistical analysis is Simpson’s Paradox. It occurs when a relationship observed in aggregated (or marginal) data reverses direction after the data are separated into meaningful subgroups (or conditional data). In simple...
What is Stratified Random Sampling?

What is Stratified Random Sampling?

by Dr. Shawn P. Capser, Ph.D., P.E., PStat®, CRE | May 29, 2026 | Statistical Analysis

In statistics and data analysis, stratified random sampling is a method used to select a sample from a larger population by first dividing that population into smaller groups, called strata, and then randomly selecting observations from each group. The purpose of...

Recent Posts

  • Bootstrapping: Measuring the Uncertainty in Inspection Results
  • Surviving a Daubert Challenge: The Role of a Statistical Expert Witness
  • Statistical Expert Witness for Product Liability: Ensuring Defensible Analysis
  • Simpson’s Paradox: When the Data Appears to Change Its Mind
  • What is Stratified Random Sampling?

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