Practical Statistics for Pharmaceutical Analysis

1. Front Matter

   Pages i-xvii

   PDF

2. Essential Elements and Statistical Terms

   • James E. De Muth

   Pages 1-17

3. Descriptive Statistics and Univariate Analysis

   • James E. De Muth

   Pages 19-36

4. Statistical Inference and Making Estimates of the Truth

   • James E. De Muth

   Pages 37-53

5. Dealing with Inherent Statistical Error

   • James E. De Muth

   Pages 55-71

6. Multivariate Analysis: Tests to Identify Differences

   • James E. De Muth

   Pages 73-135

7. Multivariate Analysis: Tests to Evaluate Relationships

   • James E. De Muth

   Pages 137-177

8. Tests to Identify Similarities

   • James E. De Muth

   Pages 179-196

9. Tests to Evaluate Potential Outliers

   • James E. De Muth

   Pages 197-210

10. Back Matter

    Pages 211-245

    PDF

This is an introductory statistics book designed to provide scientists with practical information needed to apply the most common statistical tests to laboratory research data. The book is designed to be practical and applicable, so only minimal information is devoted to theory or equations. Emphasis is placed on the underlying principles for effective data analysis and survey the statistical tests. It is of special value for scientists who have access to Minitab software. Examples are provides for all the statistical tests and explanation of the interpretation of these results presented with Minitab (similar to results for any common software package).

The book is specifically designed to contribute to the AAPS series on advances in the pharmaceutical sciences. It benefits professional scientists or graduate students who have not had a formal statistics class, who had bad experiences in such classes, or who just fear/don’t understand statistics.

            Chapter 1 focuses on terminology and essential elements of statistical testing. Statistics is often complicated by synonyms and this chapter established the terms used in the book and how rudiments interact to create statistical tests. Chapter 2 discussed descriptive statistics that are used to organize and summarize sample results. Chapter 3 discussed basic assumptions of probability, characteristics of a normal distribution, alternative approaches for non-normal distributions and introduces the topic of making inferences about a larger population based on a small sample from that population. Chapter 4 discussed hypothesis testing where computer output is interpreted and decisions are made regarding statistical significance. This chapter also deasl with the determination of appropriate sample sizes.

            The next three chapters focus on tests that make decisions about a population base on a small subset of information. Chapter 5 looks at statistical tests that evaluate where a significant difference exists. In Chapter 6 the tests try to determine the extent and importance of relationships. In contrast to fifth chapter, Chapter 7 presents tests that evaluate the equivalence, not the difference between levels being tested. The last chapter deals with potential outlier or aberrant values and how to statistically determine if they should be removed from the sample data.

Each statistical test presented includes an example problem with the resultant software output and how to interpret the results.  Minimal time is spent on the mathematical calculations or theory. For those interested in the associated equations, supplemental figures are presented for each test with respective formulas. In addition, Appendix D presents the equations and proof for every output result for the various examples.

Examples and results from the appropriate statistical results are displayed using Minitab 18^Ò. In addition to the results, the required steps to analyze data using Minitab are presented with the examples for those having access to this software. Numerous other software packages are available, including based data analysis with Excel. 

• descriptive statistics
• Inferential statistices
• Hypothesis testing
• Minitab
• multivariate analysis

• School of Pharmacy, University of Wisconsin-Madison, Madison, USA

  James E. De Muth

JAMES E. De MUTH, PhD, RPh is an Emeritus professor ,School of Pharmacy at the University of Wisconsin-Madison. He received the BS in Pharmacy degree from Drake University and the MS and PhD degrees in Pharmacy Continuing Education from the University of Wisconsin-Madison. His primary responsibilities were the development, implementation and evaluation (relying heavily on statistical methodology) of continuing education offerings for individuals in the pharmaceutical industry and pharmacists within the United States. Dr. De Muth has authored over 50 research articles in the pharmacy and adult education literature. He has taught over 175 statistical short courses in the United States, Brazil, Canada, China, India, Puerto Rico, Western Europe and the Middle East. Dr. De Muth received the  Rufus A. Lyman Award for most notable original research and/or scholarly work published in the American Journal of Pharmaceutical Education,  William A. Blockstein Award from the American Association of Colleges of Pharmacy for contributions to the field of continuing pharmaceutical education and Drake University College of Pharmacy and Health Sciences Alumni Achievement Award. For over 20 years he served on the Institutional Review Board of Covance Laboratories in Madison. He served as the chair of the Biostatistics Expert Committee , General Chapters Expert Committee and is currently chair of General Chapters Dosage Forms Expert Committee for the United States Pharmacopeia. In USP recognized the work of the General Chapters Expert Committee with its first Award for Outstanding Contributions to the USP Standard Setting Process.

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