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Introduction to Photostability
A Practical Introduction to
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Statistical Analysis of Laboratory Data
| Type | Course |
|---|---|
| Language | English |
| Date |
July 20, 2009
to July 22, 2009 |
| Venue |
University of South Florida, Downtown Center 1101 Channelside Drive - Suite 100 Tampa, FL 33602 US |
| Chemistry Specialties |
|
| Chemistry Techniques |
|
| Contact |
American Chemical Society 1155 Sixteenth Street, NW Washington, DC 20036 US (800) 227-5558 shortcourses@acs.org |
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Master the fundamentals of laboratory data treatment to solve data analysis problems. Through a combination of lectures and problem-solving sessions, this course will teach statistical techniques that can be put to immediate use in the workplace. Participants will learn how to understand the strengths and weaknesses of data, recognize and reduce different types of errors, carry out significance tests, correctly use outlier tests, and more.
Key Topics
* How to apply statistical process control charts to measurement processes.
* How to correctly use outlier tests and when not to use them.
* How to know what statistical test to use when.
* How to recognize and reduce different types of errors.
* How to set in-house specifications.
* How to understand the influence of sample size on statistical significance and power.
* How to understand the strengths and weaknesses of data.
* Ways to carry out significance tests.
* Ways to define the limits of detection, determination, and quantification.
* Why pooling variances gives stability to analytical results.
Session titles
* Measurement
* Accuracy and Precision
* Mean
* Standard Deviation
* Pooling
* z Decisions
* Confidence Intervals
* Statistical Samples
* Means
* One-Way ANOVA
* How to Carry Out a One-Way ANOVA
* Outliers
* Central Limit Theorem
* Standard Deviations
* Student's t
* Statistical Testing
* p Values and Power
* Algebra and Logic
* Hypothesis Testing
* Formal Statistical Tests
* One-Sample t Test
* Two-Sample t Test
* Paired T Test
* Fisher's F Test
* Duncan's Multiple Range Test
* Optional Topics: Detection Limits; Statistical Process Control; Bioassays