Statistical Testing Training

Do you use or abuse statistical testing? The pharmaceutical industry makes widespread use of statistical tests, from clinical trials to comparing results when transferring test methods or processes from one site to another. It is essential that the right test is correctly applied to each situation, and this pharmaceutical statistics training course details some of the common tests and how they should be correctly applied and interpreted.

The course also includes a wide range of case studies and delegates will have the opportunity to use statistical software to perform tests and interpret the results.

This course is approved by the Royal Society of Chemistry as suitable for its members’ continuing professional development (CPD).

On completion of this course, delegates will:

• Understand the basic concept of statistical testing; the hypothesis and the null-hypothesis
• Understand the range of statistical tests applicable to the pharmaceutical industry
• Have hands-on experience in using statistical software to perform statistical testing and to interpret the output

Statistical Testing With Two Groups

• Use of the t-test and paired t-test to compare two normally distributed groups

Statistical Testing With Three or More Groups

• Use of analysis of variance (ANOVA) to compare three or more normally distributed groups

Nonparametric Tests

• Tests that can be used when the data is not normally distributed: normality, Mann-Whitney, Wilcoxon and Kruskal-Wallis tests

Tests for Categorical Data

• Use of the chi-squared test to determine whether there is a significant difference between the expected and observed frequencies in one or more categories

Statistical Power and Sample Size

• Relationship between the sample size and discriminating power, including discussion of the question “How big does your sample have to be to give you the answer you need?”

Correlation and Outliers

• Use of correlation coefficients and outlier tests

• Managers wishing to drive quality and other improvements based on an objective analysis of data
• Personnel involved in the design, maintenance and operation of quality systems, both at sites and corporate locations
• QPs and other quality professionals supporting regulatory filings and GMP inspection activities