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For many biologists, statistics are an anathema; but statistical analysis of quantitative and qualitative data is of considerable importance. Although spreadsheet software… Read more
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LIST OF TABLES
LIST OF FIGURES
LIST OF EXAMPLES
PREFACE
Chapter 1: INTRODUCTION
Chapter 2: SOME BASIC STATISTICAL CONCEPTS
POPULATIONS
LOTS AND SAMPLES
AVERAGE SAMPLE POPULATIONS
STATISTICS AND PARAMETERS
VARIANCE AND ERROR
THE CENTRAL LIMIT THEOREM
Chapter 3: FREQUENCY DISTRIBUTIONS
TYPES OF FREQUENCY DISTRIBUTION
STATISTICAL PROBABILITY
THE BINOMIAL DISTRIBUTION (σ2 < μ)
THE NORMAL DISTRIBUTION
THE POISSON DISTRIBUTION (σ2 = μ)
THE NEGATIVE BINOMIAL DISTRIBUTION (σ2 > μ)
RELATIONSHIP BETWEEN THE FREQUENCY DISTRIBUTIONS
TRANSFORMATIONS
Chapter 4: THE DISTRIBUTION OF MICROORGANISMS IN FOODS IN RELATION TO SAMPLING
RANDOM DISTRIBUTION
REGULAR DISTRIBUTION
CONTAGIOUS (HETEROGENEOUS) DISTRIBUTIONS
EFFECTS OF SAMPLE SIZE
Chapter 5: STATISTICAL ASPECTS OF SAMPLING FOR MICROBIOLOGICAL ANALYSIS
ATTRIBUTES AND VARIABLES SAMPLING
BINOMIAL AND TRINOMIAL DISTRIBUTIONS
ACCURACY OF THE SAMPLE ESTIMATE
ACCEPTANCE SAMPLING BY ATTRIBUTES
ACCEPTANCE SAMPLING BY VARIABLES
Chapter 6: ERRORS IN THE PREPARATION OF LABORATORY SAMPLES FOR ANALYSIS
LABORATORY SAMPLING ERRORS
DILUENT VOLUME ERRORS
PIPETTE VOLUME ERRORS
OTHER SOURCES OF ERROR
CALCULATION OF THE RELATIVE DILUTION ERROR
EFFECTS OF GROSS DILUTION SERIES ERRORS ON THE DERIVED COLONY COUNT
Chapter 7: ERRORS ASSOCIATED WITH COLONY COUNT PROCEDURES
SPECIFIC TECHNICAL ERRORS
PIPETTING AND DISTRIBUTION ERRORS
LIMITING PRECISION AND CONFIDENCE LIMITS OF THE COLONY COUNT
GENERAL TECHNICAL ERRORS
COMPARABILITY OF COLONY COUNT METHODS
OVERALL ERROR OF COLONY COUNT METHODS
Chapter 8: ERRORS ASSOCIATED WITH QUANTAL RESPONSE METHODS
DILUTION SERIES AND ITS MOST PROBABLE NUMBER COUNTS
MULTIPLE TEST DILUTION SERIES
QUANTIFICATION BASED ON RELATIVE PREVALENCE OF DEFECTIVES
SOME STATISTICAL ASPECTS OF MULTI-STAGE TESTS
Chapter 9: STATISTICAL CONSIDERATIONS OF OTHER METHODS IN QUANTITATIVE MICROBIOLOGY
DIRECT MICROSCOPIC METHODS
Howard Mould Count
INDIRECT METHODS
Chapter 10: MEASUREMENT UNCERTAINTY IN MICROBIOLOGICAL ANALYSIS
ACCURACY AND PRECISION
MEASUREMENT UNCERTAINTY
HOW IS UNCERTAINTY ESTIMATED?
REPORTING OF UNCERTAINTY
SAMPLING UNCERTAINTY
THE USE OF UNCERTAINTY MEASURES IN ASSESSING COMPLIANCE
Chapter 11: ESTIMATION OF MEASUREMENT UNCERTAINTY
THE ‘GENERALIZED UNCERTAINTY METHOD’ (GUM) OR BOTTOM-UP PROCEDURE
THE TOP-DOWN APPROACH TO ESTIMATION OF UNCERTAINTY
ANALYSIS OF VARIANCE (ANOVA)
ROBUST METHODS OF ANOVA
MEASUREMENT OF INTERMEDIATE REPRODUCIBILITY
ESTIMATION OF UNCERTAINTY ASSOCIATED WITH QUANTAL METHODS
Chapter 12: STATISTICAL PROCESS CONTROL USING MICROBIOLOGICAL DATA
WHAT IS SPC?
TREND ANALYSIS
TOOLS FOR SPC
SETTING CONTROL LIMITS
SHEWHART’S CONTROL CHARTS FOR VARIABLES DATA
CONCLUSION
Chapter 13: VALIDATION OF MICROBIOLOGICAL METHODS FOR FOOD
THE STAGES OF METHOD DEVELOPMENT
WHAT IS VALIDATION?
FUTURE DIRECTIONS
Chapter 14: RISK ASSESSMENT, FOOD SAFETY OBJECTIVES AND MICROBIOLOGICAL CRITERIA FOR FOODS
FOOD SAFETY OBJECTIVES AND RISK ASSESSMENT
MICROBIOLOGICAL CRITERIA
THE RELEVANCE OF MICROBIAL MEASUREMENT UNCERTAINTY TO MICROBIOLOGICAL CRITERIA
CONCLUSION
INDEX
BJ
He has served on numerous official advisory groups, including the statistics group of the AOAC Presidential Taskforce on ‘Best Practices in Microbiological Methods’. He is also a member of the ISO working group on Microbiological Statistics. He is a Past President and Honorary Member of the Society for Applied Microbiology, a Fellow of the Royal Society of Biology and a Fellow of the Institute for Food Science and Technology. Although now retired, he retains his interests in teaching students and considers statistics to be a relaxing hobby, especially when accompanied by a glass of fine wine!