Week	Name	Description
	Syllabus - Theory
	Syllabus - Practical
27 February - 5 March	Learning objective
	1.1.1 Definition of statistics
	1.1.1.1 Collection.
	1.1.1.2 Organization
	1.1.1.3 Presentation
	1.1.1.4 Analysis
	1.1.1.5 Interpretation
	Definition of statistics
	1.2.1 Functions of Statistics
	1.2.2 Definiteness
	1.2.3 Condensation
	1.2.4 Comparison
	1.2.5 Formulating and Testing Hypothesis
	1.2.6 Prediction
	1.2.7 Formulation of policies
	Functions of statistics
	1.3.1 Fisheries statistics
	1.4.1 Inventory of potential resources
	1.4.2. Production
	1.4.3 Fish stock assessment
	1.4.4 Morphometric and meristic analysis
	1.4.5 Designing experiments for quantitative inferences
	1.4.6 Genetic studies
	1.4.7 Quality control
	1.4.8 Market research and business
	1.5.1 Handbook on fisheries statistics
	1.5.2 Statistics of marine products exports
	1.5.3 FAO yearbook of fishery statistics
	1.6.1 Computer and fisheries statistics
6 March - 12 March	Learning objective
	2.1.1 Introduction
	2.1.2 Primary data
	2.1.3 Secondary Data
	2.1.4 Points for Primary data
	2.1.5 Difference between primary and secondary data
	2.1.6 Advantages of secondary data
	2.1.7 Disadvantage of secondary data
	2.1.8 Choice between Primary and Secondary data
	2.1.9 Methods of collecting primary data
	2.1.9.1 Direct Personal Interviews
	2.1.9.2 Indirect Oral Interviews
	2.1.9.3 Information from Correspondents
	2.1.9.4 Mailed Questionnaire Method
	2.1.9.5 Schedules sent through Enumerators
	2.1.10 Designing the Questionnaire
	2.1.11 Pre-testing the questionnaire (or pilot survey)
	2.1.12 Sources of secondary data
	2.1.12.1 Published Sources
	2.1.12.2 Unpublished Sources
	2.1.13 Editing primary and secondary data
	2.1.14 Precautions in the use of secondary data
13 March - 19 March	Learning objective
	3.1.1 Introduction
	3.1.2 Census and sample method
	3.1.3 Theoretical basis of sampling
	3.1.4 Law of Statistical Regularity
	3.1.5 Law of Inertia of Large Numbers
	3.1.6 Essentials of sampling
	3.1.7 Methods of sampling
	3.1.7.1 Probability sampling
	3.1.7.2 Non-probability Sampling
	3.1.7.3 Advantages of Probability Sampling
	3.1.7.4 Limitations of Probability Sampling
	3.1.8 Non-probability sampling Methods
	3.1.8.1 Convenience Sampling
	3.1.8.2 Quota sampling
	3.1.9 Probability sampling methods
	3.1.9.1 Lottery Method
	3.1.9.2 Table of random Numbers
	3.1.10 Restricted Random Sampling
	3.1.10.1 How to Select Stratified Random Sample?
	3.1.10.2 Proportional and Disproportional Stratified Sample
	3.1.10.3 Systematic sampling
	3.1.10.4 Multi-stage sampling or Cluster Sampling
	3.1.11 Selection of Appropriate Method of sampling
	3.1.12 Size of sample
	3.1.12.1 Determination of sample size
	3.1.13 Merits and limitations of sampling
	3.1.14 Sampling and non-sampling errors
	3.1.14.1 Sampling errors
	3.1.14.1.1 Causes of Bias
	3.1.14.1.2 Avoidance of Bias
	3.1.14.1.3 Method of Reducing Sampling Errors
	3.1.14.2 Non-sampling Errors
	3.1.14.2.1Control of Non-Sampling Errors
	3.1.15 Reliability of samples
	Sampling methods
20 March - 26 March	Learning objective
	4.1.1 Objectives of classification
	4.1.2 Types of classification
	4.2.1 Formation of a discrete frequency distribution
	4.2.2 Formation of continuous frequency distribution
	4.2.2.1 Class limits
	4.2.2.2 Class intervals
	4.2.2.3 Class frequency
	4.2.2.4 Exclusive Method
	4.2.2.5 ‘Inclusive’ Method
	4.2.3 Considerations in the construction of Frequency distributions
	A model structure of table
27 March - 2 April	Learning objectives
	5.1.1 Significance of diagrams and graphs
	5.1.2 Comparison of Tabular and Diagrammatic Presentation
	5.1.3 Difference between Diagrams and Graphs
	5.1.4 General rules for constructing diagrams
	5.1.5 Types of diagrams
	5.1.6 . One-dimensional or Bar diagrams
	5.1.6.1 Simple Bar Diagrams
	5.1.6.2 Sub-divided Bar Diagrams
	5.1.6.3 Multiple bars
	5.1.6.4 Percentage bars
	5.1.7 Two-dimensional diagrams
	5.1.7.1 Rectangles
	5.1.7.2 Squares
	5.1.7.3 Circles
	5.1.8 Pie diagram
	5.1.8.1 Limitation of Pie Diagrams
	5.1.9 Pictograms
	5.1.10 Cartograms
	5.1.11 Choice of a Suitable diagram
	5.2.1 Graphs
	5.2.2 Technique of Constructing Graphs
	5.2.3 Graphs of Time Series or Line Graphs
	5.2.3.1 Rules for constructing the line graphs on Natural Scale
	5.2.3.2 False Base Line
	5.2.3.3 Graphs of one variable
	5.2.3. 4 Graph of Two or More variables
	5.2.3.5 Graphs having two scales
	5.2.4 Range chart
	5.2.5 Graphs of frequency distributions
	5.2.5.1. Histogram
	5.2.5.2. Frequency polygon
	5.2.5.2.1 Frequency polygon has certain advantages over the histogram
	5.2.5.3. Smoothed Frequency Curve
	5.2.5.4. Ogives or Cumulative Frequency curves
	5.2.5.4.1 Utility of Ogives
	5.2.5.5 Limitations of Diagrams and Graphs
3 April - 9 April	Learning objectives
	6.1.1 Averages or Measures of Central Tendency or Measures of Location
	6.1.2 Requisites for an Ideal Measure or Central Tendency
	Averges or measures of central tendency
	6.2.1 Arithmetic Mean
	6.2.2 Merits and Demerits of Arithmetic Mean
	6.2.3 Weighted Mean
	6.3.1 Median
	6.3.2 Merits and Demerits of Median
	6.4.1 Mode
	6.4.2 Merits and Demerits of Mode
	6.5.1 Geometric Mean
	6.5.2 Merits and Demerits of Geometric Mean
	6.5.3 Harmonic Mean
	6.5.4 Merits and Demerits of Harmonic Mean
10 April - 16 April	Learning objectives
	7.1.1 Dispersion
	7.1.2 Measures of Dispersion
	7.1.3 Range
	7.1.4 Quartile Deviation
	7.1.5 Mean Deviation
	7.1.6 Standard Deviation and Root Mean Square Deviation
17 April - 23 April	Learning objectives
	8.1.1 Skewness
	8.1.2 Measures of skewness
	8.2.1 Kurtosis
24 April - 30 April	Draw a line diagram
	How to draw Bar Diagram?
	Draw a bar diagram
	How to draw Adjacent/ Multiple Bar diagram?
	Draw Adjacent Bar diagram
	Compartmental/ Sub divided Bar diagram
	compartmental bar diagram
	Percentage Bar Diagram
1 May - 7 May	Problem 1:Calculate the measures of central tendency
	Problem 2:Calculate all the measures of central tendency
	Problem – 3.
	Problem – 4:
8 May - 14 May	Calculate all the measures of dispersion
	Problem 2:
15 May - 21 May	Calculate all the measures of variation
22 May - 28 May	Calculate all the measures of dispersion
29 May - 4 June	How to draw Histogram?
	Draw Histogram
	Draw Frequency Polygon
	Draw frequency polygon
	Frequency curve
	Frequency curve Two
	Draw the frequency curve
	Less than Ogive
	More than Ogive
	Draw ogives for the following
	Draw pie diagram
	Pie Diagram
	Draw pictogram
5 June - 11 June	Calculate the Skewness value, coefficient of skewness and kurtosis value
12 June - 18 June	Calculate the Skewness and Kurtosis is values