{"product_id":"statistical-analysis-in-microbiology-9780470559307","title":"Statistical Analysis in Microbiology","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003eThis book is aimed primarily at microbiologists who are undertaking research, and who require a basic knowledge of statistics to analyse their experimental data. Computer software employing a wide range of data analysis methods is widely available to experimental scientists. The availability of this software, however, makes it even more essential that microbiologists understand the basic principles of statistics.  \u003cp\u003eStatistical analysis of data can be complex with many different methods of approach, each of which applies in a particular experimental circumstance. In addition, most statistical software commercially available is complex and difficult to use. Hence, it is easy to apply an incorrect statistical method to data and to draw the wrong conclusions from an experiment.\u003c\/p\u003e \u003cp\u003eThe purpose of this book is an attempt to present the basic logic of statistics as clearly as possible and therefore, to dispel some of the myths that often surround the subject. The book is presented as a \u003cbr\u003e\u003cbr\u003e\u003cb\u003eTable of Contents\u003c\/b\u003e\u003cbr\u003e\u003cb\u003ePreface.\u003c\/b\u003e  \u003c\/p\u003e\u003cp\u003e\u003cb\u003eAcknowledgments.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eNote on Statistical Software.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 ARE THE DATA NORMALLY DISTRIBUTED?\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction.\u003c\/p\u003e \u003cp\u003e1.2 Types of Data and Scores.\u003c\/p\u003e \u003cp\u003e1.3 Scenario.\u003c\/p\u003e \u003cp\u003e1.4 Data.\u003c\/p\u003e \u003cp\u003e1.5 Analysis: Fitting the Normal Distribution.\u003c\/p\u003e \u003cp\u003e1.6 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 DESCRIBING THE NORMAL DISTRIBUTION.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction.\u003c\/p\u003e \u003cp\u003e2.2 Scenario.\u003c\/p\u003e \u003cp\u003e2.3 Data.\u003c\/p\u003e \u003cp\u003e2.4 Analysis: Describing the Normal Distribution.\u003c\/p\u003e \u003cp\u003e2.5 Analysis: Is a Single Observation Typical of the Population?\u003c\/p\u003e \u003cp\u003e2.6 Analysis: Describing the Variation of Sample Means.\u003c\/p\u003e \u003cp\u003e2.7 Analysis: How to Fit Confidence Intervals to a Sample Mean.\u003c\/p\u003e \u003cp\u003e2.8 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 TESTING THE DIFFERENCE BETWEEN TWO GROUPS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction.\u003c\/p\u003e \u003cp\u003e3.2 Scenario.\u003c\/p\u003e \u003cp\u003e3.3 Data.\u003c\/p\u003e \u003cp\u003e3.4 Analysis: The Unpaired \u003ci\u003et\u003c\/i\u003e Test.\u003c\/p\u003e \u003cp\u003e3.5 One-Tail and Two-Tail Tests.\u003c\/p\u003e \u003cp\u003e3.6 Analysis: The Paired \u003ci\u003et\u003c\/i\u003e Test.\u003c\/p\u003e \u003cp\u003e3.7 Unpaired versus the Paired Design.\u003c\/p\u003e \u003cp\u003e3.8 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 WHAT IF THE DATA ARE NOT NORMALLY DISTRIBUTED?\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e4.1 Introduction.\u003c\/p\u003e \u003cp\u003e4.2 How to Recognize a Normal Distribution.\u003c\/p\u003e \u003cp\u003e4.3 Nonnormal Distributions.\u003c\/p\u003e \u003cp\u003e4.4 Data Transformation.\u003c\/p\u003e \u003cp\u003e4.5 Scenario.\u003c\/p\u003e \u003cp\u003e4.6 Data.\u003c\/p\u003e \u003cp\u003e4.7 Analysis: Mann–Whitney \u003ci\u003eU\u003c\/i\u003e test (for Unpaired Data).\u003c\/p\u003e \u003cp\u003e4.8 Analysis: Wilcoxon Signed-Rank Test (for Paired Data).\u003c\/p\u003e \u003cp\u003e4.9 Comparison of Parametric and Nonparametric Tests.\u003c\/p\u003e \u003cp\u003e4.10 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 CHI-SQUARE CONTINGENCY TABLES.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction.\u003c\/p\u003e \u003cp\u003e5.2 Scenario.\u003c\/p\u003e \u003cp\u003e5.3 Data.\u003c\/p\u003e \u003cp\u003e5.4 Analysis: 2 x 2 Contingency Table.\u003c\/p\u003e \u003cp\u003e5.5 Analysis: Fisher's 2 x 2 Exact Test.\u003c\/p\u003e \u003cp\u003e5.6 Analysis: Rows x Columns (\u003ci\u003eR\u003c\/i\u003e x \u003ci\u003eC\u003c\/i\u003e) Contingency Tables.\u003c\/p\u003e \u003cp\u003e5.7 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 ONE-WAY ANALYSIS OF VARIANCE (ANOVA).\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction.\u003c\/p\u003e \u003cp\u003e6.2 Scenario.\u003c\/p\u003e \u003cp\u003e6.3 Data.\u003c\/p\u003e \u003cp\u003e6.4 Analysis.\u003c\/p\u003e \u003cp\u003e6.5 Assumptions of ANOVA.\u003c\/p\u003e \u003cp\u003e6.6 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 POST HOC TESTS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction.\u003c\/p\u003e \u003cp\u003e7.2 Scenario.\u003c\/p\u003e \u003cp\u003e7.3 Data.\u003c\/p\u003e \u003cp\u003e7.4 Analysis: Planned Comparisons between the Means.\u003c\/p\u003e \u003cp\u003e7.5 Analysis: Post Hoc Tests.\u003c\/p\u003e \u003cp\u003e7.6 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 IS ONE SET OF DATA MORE VARIABLE THAN ANOTHER?\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction.\u003c\/p\u003e \u003cp\u003e8.2 Scenario.\u003c\/p\u003e \u003cp\u003e8.3 Data.\u003c\/p\u003e \u003cp\u003e8.4 Analysis of Two Groups: Variance Ratio Test.\u003c\/p\u003e \u003cp\u003e8.5 Analysis of Three or More Groups: Bartlett's Test.\u003c\/p\u003e \u003cp\u003e8.6 Analysis of Three or More Groups: Levene's Test.\u003c\/p\u003e \u003cp\u003e8.7 Analysis of Three or More Groups: Brown–Forsythe Test.\u003c\/p\u003e \u003cp\u003e8.8 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 STATISTICAL POWER AND SAMPLE SIZE.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction.\u003c\/p\u003e \u003cp\u003e9.2 Calculate Sample Size for Comparing Two Independent Treatments.\u003c\/p\u003e \u003cp\u003e9.3 Implications of Sample Size Calculations.\u003c\/p\u003e \u003cp\u003e9.4 Calculation of the Power (\u003ci\u003eP\u003c\/i\u003e′) of a Test.\u003c\/p\u003e \u003cp\u003e9.5 Power and Sample Size in Other Designs.\u003c\/p\u003e \u003cp\u003e9.6 Power and Sample Size in ANOVA.\u003c\/p\u003e \u003cp\u003e9.7 More Complex Experimental Designs.\u003c\/p\u003e \u003cp\u003e9.8 Simple Rule of Thumb.\u003c\/p\u003e \u003cp\u003e9.9 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 ONE-WAY ANALYSIS OF VARIANCE (RANDOM EFFECTS MODEL): THE NESTED OR HIERARCHICAL DESIGN.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction.\u003c\/p\u003e \u003cp\u003e10.2 Scenario.\u003c\/p\u003e \u003cp\u003e10.3 Data.\u003c\/p\u003e \u003cp\u003e10.4 Analysis.\u003c\/p\u003e \u003cp\u003e10.5 Distinguish Random- and Fixed-Effect Factors.\u003c\/p\u003e \u003cp\u003e10.6 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 TWO-WAY ANALYSIS OF VARIANCE.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction.\u003c\/p\u003e \u003cp\u003e11.2 Scenario.\u003c\/p\u003e \u003cp\u003e11.3 Data.\u003c\/p\u003e \u003cp\u003e11.4 Analysis.\u003c\/p\u003e \u003cp\u003e11.5 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 TWO-FACTOR ANALYSIS OF VARIANCE.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction.\u003c\/p\u003e \u003cp\u003e12.2 Scenario.\u003c\/p\u003e \u003cp\u003e12.3 Data.\u003c\/p\u003e \u003cp\u003e12.4 Analysis.\u003c\/p\u003e \u003cp\u003e12.5 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 SPLIT-PLOT ANALYSIS OF VARIANCE.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction.\u003c\/p\u003e \u003cp\u003e13.2 Scenario.\u003c\/p\u003e \u003cp\u003e13.3 Data.\u003c\/p\u003e \u003cp\u003e13.4 Analysis.\u003c\/p\u003e \u003cp\u003e13.5 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 REPEATED-MEASURES ANALYSIS OF VARIANCE.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction.\u003c\/p\u003e \u003cp\u003e14.2 Scenario.\u003c\/p\u003e \u003cp\u003e14.3 Data.\u003c\/p\u003e \u003cp\u003e14.4 Analysis.\u003c\/p\u003e \u003cp\u003e14.5 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 CORRELATION OF TWO VARIABLES.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction.\u003c\/p\u003e \u003cp\u003e15.2 Naming Variables.\u003c\/p\u003e \u003cp\u003e15.3 Scenario.\u003c\/p\u003e \u003cp\u003e15.4 Data.\u003c\/p\u003e \u003cp\u003e15.5 Analysis.\u003c\/p\u003e \u003cp\u003e15.6 Limitations of \u003ci\u003er\u003c\/i\u003e.\u003c\/p\u003e \u003cp\u003e15.7 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e16 LIMITS OF AGREEMENT.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e16.1 Introduction.\u003c\/p\u003e \u003cp\u003e16.2 Scenario.\u003c\/p\u003e \u003cp\u003e16.3 Data.\u003c\/p\u003e \u003cp\u003e16.4 Analysis.\u003c\/p\u003e \u003cp\u003e16.5 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e17 NONPARAMETRIC CORRELATION COEFFICIENTS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e17.1 Introduction.\u003c\/p\u003e \u003cp\u003e17.2 Bivariate Normal Distribution.\u003c\/p\u003e \u003cp\u003e17.3 Scenario.\u003c\/p\u003e \u003cp\u003e17.4 Data.\u003c\/p\u003e \u003cp\u003e17.5 Analysis: Spearman's Rank Correlation (ρ, \u003ci\u003ers\u003c\/i\u003e).\u003c\/p\u003e \u003cp\u003e17.6 Analysis: Kendall’s Rank Correlation (τ).\u003c\/p\u003e \u003cp\u003e17.7 Analysis: Gamma (γ).\u003c\/p\u003e \u003cp\u003e17.8 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e18 FITTING A REGRESSION LINE TO DATA.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e18.1 Introduction.\u003c\/p\u003e \u003cp\u003e18.2 Line of Best Fit.\u003c\/p\u003e \u003cp\u003e18.3 Scenario.\u003c\/p\u003e \u003cp\u003e18.4 Data.\u003c\/p\u003e \u003cp\u003e18.5 Analysis: Fitting the Line.\u003c\/p\u003e \u003cp\u003e18.6 Analysis: Goodness of Fit of the Line to the Points.\u003c\/p\u003e \u003cp\u003e18.7 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e19 USING A REGRESSION LINE FOR PREDICTION AND CALIBRATION.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e19.1 Introduction.\u003c\/p\u003e \u003cp\u003e19.2 Types of Prediction Problem.\u003c\/p\u003e \u003cp\u003e19.3 Scenario.\u003c\/p\u003e \u003cp\u003e19.4 Data.\u003c\/p\u003e \u003cp\u003e19.5 Analysis.\u003c\/p\u003e \u003cp\u003e19.6 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e20 COMPARISON OF REGRESSION LINES.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e20.1 Introduction.\u003c\/p\u003e \u003cp\u003e20.2 Scenario.\u003c\/p\u003e \u003cp\u003e20.3 Data.\u003c\/p\u003e \u003cp\u003e20.4 Analysis.\u003c\/p\u003e \u003cp\u003e20.5 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e21 NONLINEAR REGRESSION: FITTING AN EXPONENTIAL CURVE.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e21.1 Introduction.\u003c\/p\u003e \u003cp\u003e21.2 Common Types of Curve.\u003c\/p\u003e \u003cp\u003e21.3 Scenario.\u003c\/p\u003e \u003cp\u003e21.4 Data.\u003c\/p\u003e \u003cp\u003e21.5 Analysis.\u003c\/p\u003e \u003cp\u003e21.6 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e22 NONLINEAR REGRESSION: FITTING A GENERAL POLYNOMIAL-TYPE CURVE.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e22.1 Introduction.\u003c\/p\u003e \u003cp\u003e22.2 Scenario A: Does a Curve Fit Better Than a Straight Line?\u003c\/p\u003e \u003cp\u003e22.3 Data.\u003c\/p\u003e \u003cp\u003e22.4 Analysis.\u003c\/p\u003e \u003cp\u003e22.5 Scenario B: Fitting a General Polynomial-Type Curve.\u003c\/p\u003e \u003cp\u003e22.6 Data.\u003c\/p\u003e \u003cp\u003e22.7 Analysis.\u003c\/p\u003e \u003cp\u003e22.8 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e23 NONLINEAR REGRESSION: FITTING A LOGISTIC GROWTH CURVE.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e23.1 Introduction.\u003c\/p\u003e \u003cp\u003e23.2 Scenario.\u003c\/p\u003e \u003cp\u003e23.3 Data.\u003c\/p\u003e \u003cp\u003e23.4 Analysis: Nonlinear Estimation Methods.\u003c\/p\u003e \u003cp\u003e23.6 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e24 NONPARAMETRIC ANALYSIS OF VARIANCE.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e24.1 Introduction.\u003c\/p\u003e \u003cp\u003e24.2 Scenario.\u003c\/p\u003e \u003cp\u003e24.3 Analysis: Kruskal–Wallis Test.\u003c\/p\u003e \u003cp\u003e24.4 Analysis: Friedmann's Test.\u003c\/p\u003e \u003cp\u003e24.5 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e25 MULTIPLE LINEAR REGRESSION.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e25.1 Introduction.\u003c\/p\u003e \u003cp\u003e25.2 Scenario.\u003c\/p\u003e \u003cp\u003e25.3 Data.\u003c\/p\u003e \u003cp\u003e25.4 Analysis.\u003c\/p\u003e \u003cp\u003e25.5 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e26 STEPWISE MULTIPLE REGRESSION.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e26.1 Introduction.\u003c\/p\u003e \u003cp\u003e26.2 Scenario.\u003c\/p\u003e \u003cp\u003e26.3 Data.\u003c\/p\u003e \u003cp\u003e22.4 Analysis by the Step-Up Method.\u003c\/p\u003e \u003cp\u003e26.5 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e27 CLASSIFICATION AND DENDROGRAMS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e27.1 Introduction.\u003c\/p\u003e \u003cp\u003e27.2 Scenario.\u003c\/p\u003e \u003cp\u003e27.3 Data.\u003c\/p\u003e \u003cp\u003e27.4 Analysis.\u003c\/p\u003e \u003cp\u003e27.5 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003e28 FACTOR ANALYSIS AND PRINCIPAL COMPONENTS ANALYSIS.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e28.1 Introduction.\u003c\/p\u003e \u003cp\u003e28.2 Scenario.\u003c\/p\u003e \u003cp\u003e28.3 Data.\u003c\/p\u003e \u003cp\u003e28.4 Analysis: Theory.\u003c\/p\u003e \u003cp\u003e28.5 Analysis: How Is the Analysis Carried Out?\u003c\/p\u003e \u003cp\u003e28.6 Conclusion.\u003c\/p\u003e \u003cp\u003e\u003cb\u003eReferences.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix 1 Which Test to Use: Table.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix 2 Which Test to Use: Key.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix 3 Glossary of Statistical Terms and Their Abbreviations.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eAppendix 4 Summary of Sample Size Procedures for Different Statistical Tests.\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003eIndex of Statistical Tests and Procedures.\u003c\/b\u003e\u003c\/p\u003e","brand":"Wiley","offers":[{"title":"Default Title","offer_id":53515417977175,"sku":"9780470559307","price":46.76,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/statistical-analysis-in-microbiology-9780470559307","provider":"Book Curl","version":"1.0","type":"link"}