麻省理工学院 生物材料课程 lecture 15 Statistical Analysis in Biomaterials Research.pdfVIP

3.051J/20.340J 1 Lecture 15 Statistical Analysis in Biomaterials Research 1. Rationale: Why is statistical analysis needed in biomaterials research? ™Many error sources in measurements on living systems! Examples of Measured Values and Error in Biomaterials Data Graphs removed for copyright reasons. 3.051J/20.340J 2 Case Example: cell sedimentation assay of % of cells adhering to a biomaterial vs. control (the simplest cell assay) Sources of data variation: ¾Contamination of surface ⇒ cytotoxicity or modified surface chemistry ¾Variations in the number of cells seeded on each surface ¾Variations in biomaterial synthesis (reagent amounts, T, time, etc.) ¾Variations in cells (different cell passages) ¾Variations in media (e.g., different concentrations, proteins agglomerated) ¾Variations in sterilization procedure ¾Researcher error (e.g., sneezing on samples) ™ Behavior is best characterized by a population or distibution of values Case Example: Titration of HCl solution with equimolar NaOH solution. Graphs removed for copyright reasons. 3.051J/20.340J 3 Data converge to a population as N → ∞: Graph removed for copyright reasons. ™Our Goal: to make enough measurements to accurately characterize the distribution of behaviors, via ¾The mean of the data distribution = x from N measurements N ∑xi i 1 x N ¾The width of the distribution, or standard deviation, S : N ∑ (x − x )2 Note that the standard