No Prior Statistical Knowledge Required: Learn Analytical Method Validation Statistical Analysis with Excel

This course carefully explains basic concepts through demo analysis using Excel, regardless of prior statistical knowledge. The goal is to enable participants to perform calculations themselves and explain theoretical rationality.

In the practical work of analytical method validation, basic statistical concepts such as variability, error, and estimation are indispensable. However, statistics often takes time to reach the necessary understanding in the field due to reasons such as being "formula-centric and difficult" or "definitions are strict and understanding does not progress." As a result, it can lead to challenges such as lacking confidence in explaining the basis of experimental design and evaluation, or relying on external parties for calculations and interpretations.

Seminar Overview Seminar Name: Statistical Analysis for Analytical Method Validation: Learning from Basics Format: Online participation (Zoom LIVE streaming / Archive streaming) Dates: [LIVE streaming participation] June 24, 2026 (Wednesday) 10:00-16:30 (Zoom) [Archive streaming] June 26 - July 10, 2026 Participation Fee: 49,500 JPY (tax included) / per person (group discount available for multiple participants) Instructor: Akihisa Fukuda, Lecturer (Representative of Stat Imaging Lab)

Course Details This seminar is not about "special statistics for analytical method validation," but rather structured to progressively understand how general statistical principles are applied to validation. The four goals are: (1) acquire statistical basics, (2) be able to conduct correct experiments, (3) be able to perform calculations independently, and (4) be able to explain theoretical rationality.

Seminar Program Thoroughly understand the very basics "Standard Deviation" = quantification of variability / concept of standardization (relative positioning) / conversion to representation by normal distribution table Deep dive into confidence intervals Meaning of "mean value" / standard error and variability of the mean / understanding of t-distribution table, 95% confidence interval / verification with Monte Carlo simulation Repeatability Basics of repeatability / image and analysis of experiments with 3 concentrations x 3 measurements each Accuracy Basics of accuracy and the concept of confidence intervals / analysis method for multiple concentration experiments / relationship between accuracy and repeatability Intermediate Precision Key points of experimental design and analysis / calculation from one-way ANOVA table / concept of confidence intervals, cases without repetition / comparison of branching designs, structural models Linearity Understanding linearity in validation / interpretation of regression analysis results / handling cases where saturation is observed Detection Limit Calculation method / concept of setting criteria

Target Audience Practitioners and managers of analytical method validation Those who perform precision control of measurements in laboratories Those who want to learn from pharmaceutical examples (those outside pharmaceutical analysis are also welcome) Those who want to relearn statistical basics (no statistical knowledge required)

*Click here for more details on this seminar https://nihon-ir.jp/seminar/basic_analytical-method-validation_statistical-analysis/

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