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Confidence Intervals provides the participant with the knowledge and skills necessary to compute statistical confidence intervals for various measures of central tendency and variability (with known degrees of risk and confidence). Specifically, the participant will learn how to compute, interpret and report statistical confidence intervals for virtually any application involving the use of continuous or discrete data, such as the confidence intervals that would embody the true mean and variance of a continuous product performance characteristic or the confidence intervals around a given defect rate.
As most experienced process improvement experts will agree, a basic understanding of the theory and application of confidence intervals is essential for the sufficient characterization, improvement and control of commercial and industrial products, services and processes. From this perspective, it is easy to see why this course is a crucial backdrop for the intermediate practice of many process improvement activities, like Statistical Process Control (SPC) and Design of Experiments (DOE). Reinforcement of major concepts, techniques, and application is realized through exercises, scenarios, and case studies. The following prerequisite topics are listed in sequential learning order: Basic Statistics and Hypothesis Testing. Total instructional is time for the topic is 2 hours and 47 minutes.
- Mean Distribution - Comprehend and characterize the distribution of sampling averages
- Mean Interval - Compute and interpret the confidence interval of a mean
- Variance Distribution - Comprehend and characterize the distribution of sampling variances
- Variance Interval - Compute and interpret the confidence interval of a variance
- Proportion Distribution - Comprehend and characterize the distribution of sampling proportions
- Proportion Interval - Compute and interpret the confidence interval of a proportion
- Frequency Interval - Describe how frequency of defects is related to confidence intervals