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DESCRIPTION
Hypothesis testing is a statistical procedure that helps determine if a data set, typically from a sample, is compatible with a given hypothesis. It helps detect differences from expectations or from two sets of results. This webinar focuses on hypothesis tests involving the mean, since it is one of the most common applications.
Webinar participants learn the underlying concept as well as the steps to help implement the procedure. A variety of examples illustrates how to use the procedure. In addition, the examples show how to perform the calculations in Excel, laying out the problems, and illustrating the use of built in functions. In the more complicated cases, the examples use Excel’s built-in Data Analysis ToolPak.

Areas covered in the webinar:
The basic concepts of hypothesis tests for means
When to perform a one-tailed or two-tailed test
The difference between large samples and small samples
Applications of the z-test
Applications of the t-test and when it should be used
Use of the Data Analysis ToolPak in Excel for hypothesis tests

Who will benefit:
Quality Managers
Quality Engineers
Design Engineers
Production Engineers
People who need to make statistically based decisions

Why you should attend:
Hypothesis testing is a powerful statistical technique for process improvement. It can help you compare process outputs and detect differences that may be significant. In this webinar, you will learn the concepts as well as tools available in Excel to help you implement the technique.

Webinar includes:
A summary sheet that shows the calculations as well as the relevant Excel formulas and methods.
Q/A Session with the Expert to ask your question
PDF print only copy of PowerPoint slides
90 Minutes Live Presentation
Certificate of attendance