Statistics for Aquaculture

1. Introduction
   1.1 Background
   1.2 History and definition of statistics
   1.3 Scope and application
       1.3.1 In general
       1.3.2 In aquaculture
   1.4 Questions
   1.5 Practical exercise
2. Experimental units in aquaculture
   2.1 Background
   2.2 Earth ponds
   2.3 Hapas and cages in ponds
   2.4 Cages in lakes or reservoirs
   2.5 Tanks
   2.6 Aquaria
   2.7 Farmer’s field: participatory research
   2.8 Conclusion
   2.9 Questions
   2.10 Practical exercises
3. Sampling and data collection
   3.1 Sampling principles and methods
   3.2 Parameters or variables
       3.2.1 Variable types
       3.2.2 Variables of aquaculture
   3.3 Fish sampling
   3.4 Sampling of feed and feed ingredients
   3.5 Water sampling and monitoring
   3.6 Sampling of eggs, muscles, blood, and others
   3.7 Sample size (volume/number)
       3.7.1 Simple method for sample size estimation
       3.7.2 Comprehensive method for sample size estimation
       3.7.3 Sample size estimation for survey research
   3.8 Questions
   3.9 Practical exercises
4. Data accuracy and exploratory analysis
   4.1 Importance
   4.2 Data accuracy and precision
   4.3 Significant numbers
   4.4 Errors and their sources
       4.4.1 Gross errors
       4.4.2 Systematic errors
       4.4.3 Random or residual errors (unsystematic)
   4.5 Error minimization and separation
       4.5.1 Experimental conditions and procedures
       4.5.2 Materials, methods, and equipment
       4.5.3 Randomization
       4.5.4 Pairing
       4.5.5 Blocking
       4.5.6 Measurement of additional variables/factors
       4.5.7 Increasing number of treatments and replication
   4.6 Exploratory data analysis
       4.6.1 Checking for any errors
       4.6.2 Comparison with others
       4.6.3 Useful tools
       4.6.4 Basic assumptions
   4.7 Normal distribution
       4.7.1 Concept of probability
       4.7.2 Frequency distribution and probability
       4.7.3 Grouping classes
       4.7.4 Histogram and frequency curves
       4.7.5 Variance heterogeneity
       4.7.6 Data transformation
   4.8 Questions
   4.9 Practical exercises
5. Central locations and variability
   5.1 Concept and importance
   5.2 Measure of central tendency
       5.2.1 Mean
       5.2.2 Median
       5.2.3 Mode
       5.2.4 Midrange and midhinge
       5.2.5 Quartiles, percentiles, and others
   5.3 Measure of variability
       5.3.1 Range
       5.3.2 Interquartile range or quartile deviation
       5.3.3 Mean deviation
       5.3.4 Variance and standard deviation
       5.3.5 Population and sample variance/SD
       5.3.6 Standard error
       5.3.7 Coefficient of variation
       5.3.8 Implications of variability
   5.4 Questions
   5.5 Practical exercises
   
6. Basics of hypothesis formulation and testing
   6.1 Concept
   6.2 Significance level
   6.3 Confidence level, limits, and interval
   6.4 Statistical and biological significance
   6.5 Errors in hypothesis testing
   6.6 Selection of statistical tools
   6.7 Test of goodness-of-fit
       6.7.1 x 2-test
       6.7.2 One-sample K–S test
   6.8 One- and two-sample tests
       6.8.1 Parametric tests: t- and Z-tests
       6.8.2 Nonparametric tests: Mann-Whitney and Wilcoxon’s tests
   6.9 Questions
   6.10 Practical exercises
   
7. Experimental designs and analysis of variance
   7.1 Background
   7.2 Completely randomized design
       7.2.1 Parametric test
       7.2.2 Nonparametric test: Kruskal-Wallis test (H-test)
   7.3 Randomized complete block design
       7.3.1 Parametric test using ANOVA
       7.3.2 Nonparametric test: Friedman test for RCBD
   7.4 Latin square design
   7.5 Factorial experiments
   7.6 Questions
   7.7 Practical exercises
   
8. Testing and exploring relationships
   8.1 Background
   8.2 Single-factor regression
       8.2.1 Simple linear regression
       8.2.2 Hypothesis testing
       8.2.3 Nonlinear regression
       8.2.4 Model formulation and selection
   8.3 Multiple regression
       8.3.1 Methods
       8.3.2 Example
       8.3.3 Interpretation of results
       8.3.4 Prediction
       8.3.5 Selection of method
   8.4 Correlation and parametric test
   8.5 Nonparametric tests for regression and correlation
       8.5.1 Spearman’s rank correlation
       8.5.2 Kendall’s rank correlation or Kendall’s coefficient of concordance
   8.6 Multiple correlations
   8.7 Questions
   8.8 Practical exercises
   
9. Advanced topics
   9.1 Cluster analysis
       9.1.1 Univariate cluster analysis
       9.1.2 Multivariate cluster analysis
   9.2 Analysis of Covariance
   9.3 Multivariate ANOVA
   9.4 Interpretation of results
   9.5 Questions
   9.6 Practical exercises
   

The cost of delivering this item to your selected country is detailed below: