Biostatistics and Microbiology

by Paulson, Daryl S.

• ISBN13: 9780387772813
• ISBN10: 0387772812
• Edition: 1st
• Format: Paperback
• Copyright: 2008-10-01
• Publisher: Springer Verlag

Summary

"Biostatistics and Microbiology enables the reader to access and apply statistical methods that generally frustrate and intimidate the uninitiated. Statistics, like chemistry, microbiology, woodworking, or sewing, requires that the individual put some time into learning the concepts and methods. This book presents a step-by-step manner that eliminates the greatest obstacle to the learner, which is applying the many processes that comprise a statistical method. The author counters the fear of statistical methods by describing early in the book a step-by-step procedure to perform a statistical method - a process that we will term "the six-step procedure." All of the testing will be performed adhering to six well-defined steps, which will greatly simplify the statistical process. Each step in the sequence must be completed before moving on to the next step. In the context of microbiology, statistics can be extremely useful in making interpretations and decisions concerning collected data. Statistics, then, is a way of formally communicating the interpretation of clinical or experimental data and is particularly important when a treatment result is not clearly differentiable from another treatment"--BOOK JACKET.

Author Biography

Daryl S. Paulson BioScience Laboratories, Inc. Bozeman, MT, USA

Table of Contents

Acknowledgements	p. v
BioStatistics and Microbiology: Introduction	p. 1
Normal Distribution	p. 2
Mean	p. 6
Variance and Standard Deviation	p. 7
Mode of Sample Data	p. 8
Median of Sample Data	p. 8
Using Normal Distribution Tables	p. 8
Standard Error of the Mean	p. 12
Confidence Intervals	p. 13
Hypothesis Testing	p. 14
One-Sample Tests	p. 15
Estimation of a One-Sample Mean	p. 15
Comparing One Sample Group Mean to a Standard Value	p. 20
Confidence Interval Approach	p. 20
Use of the Student's t Test to Make the Determination of a Sample Mean Different, Less than, or Greater than a Standard Value	p. 24
Determining Adequate Sample Sizes for One-Sample Statistical Tests	p. 28
Quick Sample Size Formula: Sample Set Mean Versus a Standard Value	p. 29
Detection Level	p. 30
A More Accurate Method of Sample Size Determination	p. 30
(Optional) Equivalency Testing	p. 32
Nonsuperiority Test	p. 35
Confidence Interval Approach to Superiority/Inferiority Testing	p. 37
Two-Sample Statistical Tests, Normal Distribution	p. 41
Requirements of all t Tests	p. 42
Two-Sample Independent t Test: Variances are not Assumed Equivalent, [sigma subscript 1 superscript 2 not equal sigma subscript 2 superscript 2]	p. 42
Two-Sample Pooled t Test: Variances are Equivalent, [sigma subscript 1 superscript 2] = [sigma subscript 2 superscript 2]	p. 45
Paired t Test	p. 48
Sample Size Determination	p. 52
Other Topics	p. 55
Proportions	p. 55
Optional Two-Sample Bioequivalency Testing	p. 57
Two Independent Samples: Sample Variances Assumed Equal	p. 58
Confidence Interval Approach	p. 61
Analysis of Variance	p. 63
The Completely Randomized One-Factor ANOVA	p. 64
Contrasts	p. 71
Confidence Intervals	p. 72
Sample Size Calculation	p. 73
Randomized Block Design	p. 74
Pair-wise Contrasts	p. 79
100 (1 - a) Confidence Intervals	p. 79
Sample Size Calculation	p. 81
Regression and Correlation Analysis	p. 83
Least Squares Equation	p. 85
Strategy for Linearizing Data	p. 89
The Power Scale	p. 90
Using Regression Analysis	p. 90
Predicting the Average y from an x Value	p. 91
Predicting a Specific y Value from an x Value	p. 92
Correlation	p. 93
Correlation Coefficient: r	p. 94
Coefficient of Determination: r[superscript 2]	p. 96
Predicting an x Value from a y Value	p. 97
Confidence Interval for a Specific x	p. 99
Confidence Interval for the Average x Value	p. 100
D-Value Calculation	p. 100
Qualitative Data Analysis	p. 101
Binomial Distribution	p. 101
Version I: Mean, Variance, and Standard Deviation Estimates for Predicting Outcome Events	p. 101
Version II: Mean, Variance, and Standard Deviation Estimates for Predicting Proportions or Percentages	p. 102
Confidence Interval Estimation	p. 102
Confidence Intervals on Proportions that are not Extreme (Not Close to 0 or 1): The Yates Adjustment	p. 104
Confidence Intervals on Proportions that are Extreme (Close to 0 or 1)	p. 104
Comparing Two Samples	p. 105
Proportions: One Sample Compared to a Standard Value	p. 105
Confidence Interval Approach	p. 107
Comparing Two Sample Proportions	p. 109
Equivalence Testing: Proportions	p. 112
Equivalence Testing: One Proportion Sample Compared to a Standard	p. 112
Confidence Interval Approach	p. 114
Nonsuperiority	p. 114
Two-Tail Test: Equivalence	p. 115
Confidence Interval	p. 116
Two-Sample Equivalence: Proportions	p. 116
Nonparametric Statistical Methods	p. 121
Comparing Two Independent Samples: Nominal Scale Data	p. 123
Comparing Two Independent Samples: 2 x 2 Chi Square Test	p. 123
Comparing Two Related Samples: Nominal Scale Data	p. 126
Comparing More than Two Independent Samples: Nominal Scale Data	p. 129
Comparing More than Two Related Samples: Nominal Scale Data	p. 132
Ordinal Scale Data: Rankable	p. 133
Comparing Two Independent Sample Sets: Ordinal Data	p. 133
Comparing Two Related Sample Sets: Ordinal Data	p. 138
Comparing More than Two Independent Samples: Ordinal or Interval Data	p. 142
Multiple Contrasts	p. 146
Comparing More than Two Related Samples: Ordinal Data	p. 147
Interval-Ratio Scale Data	p. 152
Comparing Two Independent Samples: Interval-Ratio Data	p. 152
Comparing Two Related or Paired Samples: Interval-Ratio Data	p. 154
Independent Samples, n > 2: Interval-Ratio Data	p. 157
Related Samples, n > 2: Interval-Ratio Data	p. 157
Tables of Mathematical Values	p. 163
Student's t table (percentage points of the t distribution)	p. 164
Z-table (normal curve areas [entries in the body of the table give the area under the standard normal curve from 0 to z])	p. 165
Studentized range table	p. 166
F distribution tables	p. 168
Chi square table	p. 173
Quantiles of the Mann-Whitney test statistic	p. 174
Binomial probability distribution	p. 178
Critical values of the Kruskal-Wallis test	p. 207
Friedman ANOVA table	p. 209
Wilcoxon table	p. 211
Index	p. 213
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