Applied Statistics for Scientists and Engineers (Boston, MA, United States - December 7-8, 2017) - Research and Markets

The "Applied Statistics for Scientists and Engineers" conference has been added to Research and Markets' offering.

Throughout 21 CFR and guidance documents for the pharmaceutical, biopharmaceutical, and medical device industries, the application of statistical methods are specified for: setting validation criteria and specifications, performing measurement systems analysis (MSA), conducting stability analysis, using design of experiment (DOE) for process development and validation, developing process control charts, and determining process capability indices.

Different statistical methods are required for each of these particular applications. Data and tolerance intervals are common tools used for setting acceptance criteria and specifications. Simple linear regression and analysis-of-covariance (ANCOVA) are used for setting expiries and conducting stability analysis studies. Two-sample hypothesis tests, analysis-of-variance (ANOVA), regression, and ANCOVA are methods used for analyzing designed experiment for process development and validation studies. Descriptive statistics (distribution, summary statistics), run charts, and probability (distributions) are used for developing process control charts and developing process capability indices.

This course provides instruction on how to apply the appropriate statistical approaches: descriptive statistics, data intervals, hypothesis testing, ANOVA, regression, ANCOVA, and model building. Once competence in each of these areas is established, industry-specific applications are presented for the participants.

Objectives:

• Describe and analyze the distribution of data
• Develop summary statistics
• Generate and analyze statistical intervals and hypothesis tests to make data-driven decisions
• Describe the relationship between and among two or more factors or responses
• Understand issues related to sampling and calculate appropriate sample sizes
• Use statistical intervals to setting specifications/develop acceptance criteria
• Use Measurement Systems Analysis (MSA) to estimate variance associated with: repeatability, intermediate precision, and reproducibility
• Ensure your process is in (statistical) control and capable

For more information about this conference visit https://www.researchandmarkets.com/research/68qppd/applied

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