Definition of statistics, Concepts of population, sample, Census and sample surveys,Classification of data, frequency and cumulative frequency table.Diagrammatic and graphicalrepresentation of data - bar diagrams, pie-diagram, histogram, frequency polygon, frequencycurve and Ogives. Important measures of central tendency - arithmetic mean median and mode.Relative merits and demerits of these measures. Important measures of dispersion, Range, MeanDeviation, Variance and Standard Deviation. Relative merits and demerits of these measures.Coefficient of variation; Normal Curve, Concepts of Skewness and kurtosis. Definitions of probability, mutually exclusive and independent events, conditional probability,addition and multiplication theorems.Random variable, concepts of theoretical distribution;Binomial, Poisson and Normal distributions and their use in fisheries. Basic concept of samplingdistribution; standard error and central limit theorem. Introduction to statistical inference, generalprinciples of testing of hypothesis, types of errors. Tests of significance based on Normal, t, andChi-square distributions. Bivariate data, scatter diagram, simple linear correlation, measure andproperties, linear regression, equation and fitting; relation between correlation and regression,Length weight relationship in fishes; applications of linear regression in fisheries. Methodologyfor estimation of marine fish landings in India, Estimation of inland fish production in India andproblems encountered.
What will i learn?
Describe and discuss the key terminology, concepts tools and techniques used in statistical analysis.
Critically evaluate the underlying assumptions of analysis tools
Understand and critically discuss the issues surrounding sampling and significance
Discuss critically the uses and limitations of statistical analysis
Solve a range of problems using the techniques covered
