Statistical Hypothesis Tests: Concepts & Applications
In this webinar, you will learn how to supplement statistical results with graphical methods to illustrate conclusions. The focus will be on the correct interpretation and presentation of results rather than mathematical details.
March 16, 2020
10:00 AM PST | 01:00 PM EST
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Product Id : 502856
Live: One Dial-in One Attendee
Corporate Live: Any number of participants
Recorded: Access recorded version, only for one participant unlimited viewing for 6 months ( Access information will be emailed 24 hours after the completion of live webinar)
Corporate Recorded: Access recorded version, Any number of participants unlimited viewing for 6 months ( Access information will be emailed 24 hours after the completion of live webinar)
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 should you Attend:
Areas Covered in the Session:
- 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
Who Will Benefit:
- Statistical Hypothesis Testing Concepts
- Null and Alternate Hypotheses
- Test Statistics
- 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
Steven Wachs has 25 years of wide-ranging industry experience in both technical and management positions. He has worked as a statistician at Ford Motor Company where he has extensive experience in the development of statistical models, reliability analysis, designed experimentation, and statistical process control.
Mr. Wachs is currently a Principal Statistician at Integral Concepts, Inc. where he assists manufacturers in the application of statistical methods to reduce variation and improve quality and productivity. He also possesses expertise in the application of reliability methods to achieve robust and reliable products as well as estimate and reduce warranty. Mr. Wachs regularly speaks at industry conferences and provides workshops in industrial statistical methods worldwide.
He has an M.A. in Applied Statistics from the University of Michigan, an M.B.A, Katz Graduate School of Business from the University of Pittsburgh, 1992, and a B.S., Mechanical Engineering from the University of Michigan.