By Sanford Bolton

By using sensible examples and suggestions, this well timed 5th version has been up to date and increased to supply the main whole and accomplished consultant to many of the statistical functions and examine matters within the pharmaceutical undefined, fairly scientific trials and bioequivalence stories. New to the 5th variation:

**Read Online or Download Pharmaceutical Statistics: Practical and Clinical Applications, Fifth Edition (Drugs and the Pharmaceutical Sciences) PDF**

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**Extra resources for Pharmaceutical Statistics: Practical and Clinical Applications, Fifth Edition (Drugs and the Pharmaceutical Sciences)**

**Sample text**

7 PRECISION, ACCURACY, AND BIAS When dealing with variable measurements, the deﬁnitions of precision and accuracy, often obscure and not distinguished in ordinary usage, should be clearly deﬁned from a statistical point of view. 1 Precision In the vocabulary of statistics, precision refers to the extent of variability of a group of measurements observed under similar experimental conditions. A precise set of measurements is compact. d. ) An important, sometimes elusive concept is that a precise set of measurements may have the same mean as an imprecise set.

D. of 1. 7 PRECISION, ACCURACY, AND BIAS When dealing with variable measurements, the deﬁnitions of precision and accuracy, often obscure and not distinguished in ordinary usage, should be clearly deﬁned from a statistical point of view. 1 Precision In the vocabulary of statistics, precision refers to the extent of variability of a group of measurements observed under similar experimental conditions. A precise set of measurements is compact. d. ) An important, sometimes elusive concept is that a precise set of measurements may have the same mean as an imprecise set.

These relationships can range from relatively simple to very complex, and may involve only two variables or many variables. 1. Chapter 7 is devoted to the analysis of data involving variables that have a linear relationship. When analyzing and depicting data that involve relationships, we are often presented with data in pairs (X, Y pairs). 1, the optical density Y and the concentration X are the data pairs. When considering the relationship of two variables, X and Y, one variable can often be considered the response variable, which is dependent on the selection of the second or causal variable.