Business Process & Quality Management

Six Sigma Way for Making Business Decisions with Statistical Inference

Participants will learn the concept of statistical inference, that is, how we draw a business decision and conclusion about an unknown population based on evidence from a sample (such as survey data, customer data, product quality information, etc.), and how we incorporate the uncertainty inherent whenever a sample is used.

This program covers the different elements of statistical inference including random sampling, sampling error, normal populations, confidence intervals, and hypothesis testing.

We develop confidence intervals for proportions, means and the difference between two means. Lastly, we see how hypothesis testing may be used as an alternative to confidence intervals to provide valid statistical inferences from a sample.

Course Outlines

• Population, Variable, Parameter, Sample, and Estimate.
• Simple Random Sample.
• Normal Population Model.
• NORMDIST and NORMINV
• Uncertainty in a Point Estimate.
• Confidence Interval and its Meaning.
• Hypothesis Testing: Confidence Intervals, p-values and its business applications.

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