Statistical Hypothesis Tests: Concepts & Applications

Many engineers, scientists, and business analysts struggle with the application of statistical methods when analyzing data to making decisions.

Non-statisticians frequently seek help in tasks such as determining appropriate sample sizes, interpreting tests results, and distinguishing statistical differences from practical differences.

This webinar will lay the groundwork for a deeper understanding of statistical hypothesis tests. Key concepts and terminology underlying statistical hypothesis tests are clearly explained.

Then, the applications of various, different hypothesis tests along with important assumptions are presented. The focus will be on the correct interpretation and presentation of results rather than mathematical details.

Why you should Attend:

• Understand Hypothesis Testing definitions and methodology
• Select appropriate hypothesis tests for specific applications
• Understand key assumptions in specific tests
• Interpret results of hypothesis tests
• Determine appropriate sample sizes for conducting studies
• Learn how to supplement statistical results with graphical methods to illustrate conclusions
• Use correct language when presenting results

• Statistical Hypothesis Testing Concepts
• Null and Alternate Hypotheses
• Test Statistics
• p-values
• confidence intervals
• confidence levels
• test power
• power curves
• sample sizes
• 1 and 2-sample means tests
• Tests of variances
• Test of proportions
• Equivalence Tests

• • Product Development Personnel
  • Research and Development Personnel
  • Quality Personnel
  • Product/Process Engineers
  • Personnel utilizing data to make decisions and improve processes