 Statistical Methods Teacher

Chinmayee Patra Category

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Code(Credit) : ASAS-1101(1-1-0)

Course Objectives

• To impart knowledge to the students on basic concepts and statistical techniques applied in agriculture and allied sciences.

Learning Outcomes

• To enable the students to analyze data and draw appropriate statistical conclusions.
• To recognize and examine the relationships between inputs and outputs in their agricultural field to make effective and profitable decisions.
• Students will demonstrate an ability to engage in critical thinking by analyzing situations and constructing and selecting viable solutions to solve problems.

Course Syllabus

Theory
Introduction to Statistics and its Applications in Agriculture, Graphical Representation of Data, Measures of Central Tendency & Dispersion, Definition of Probability, Addition, and Multiplication Theorem (without proof). Simple Problems Based on Probability. Binomial & Poisson Distributions, Definition of Correlation, Scatter Diagram.Karl Pearson’s Coefficient of Correlation. Linear Regression Equations. Introduction to Test of Significance, One sample & two-sample test t for Means, Chi-Square Test of Independence of Attributes in 2 × 2 Contingency Table. Introduction to Analysis of Variance, Analysis of One Way Classification. Introduction to Sampling Methods, Sampling versus Complete Enumeration, Simple Random Sampling with and without replacement, Use of Random Number Tables for selection of Simple Random Sample.
Practical
Graphical Representation of Data.Measures of Central Tendency (Ungrouped data) with Calculation of Quartiles, Deciles & Percentiles.Measures of Central Tendency (Grouped data) with Calculation of Quartiles, Deciles & Percentiles.Measures of Dispersion (Ungrouped Data).Measures of Dispersion (Grouped Data).Moments, Measures of Skewness & Kurtosis (Ungrouped Data).Moments, Measures of Skewness & Kurtosis (Grouped Data).Correlation  & Regression Analysis.Application of a One-Sample t-test. Application of Two Sample Fisher’s t-test.Chi-Square test of Goodness of Fit.Chi-Square test of Independence of Attributes for 2×2 contingency table. Analysis of Variance One Way Classification. Analysis of Variance Two Way Classification.Selection of random sample using Simple Random Sampling.
Reference
• Rangaswamy, R 1995. A Text-Book of Agricultural Statistics. New Age International (P) Ltd., Publishers, Hyderabad.
• Nageswara Rao, G 2007. Statistics for Agricultural Sciences. B.S Publications, Hyderabad
• Agrawal, B.L. programmed Statistics. 3rd Edition, New Age International Publishers, Hyderabad.
• Gupta, S.C and Kapoor, V.K. Fundamental of Mathematical Statistics, Sultan Chand & Sons publication.

Session 1

Introduction to statistics, Definition, Advantages, and Limitation, Frequency distribution: Construction of Frequency distribution

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Session 2

Measures of Central tendency: Definition, Arithmetic mean, Median, Mode for grouped and ungrouped data- Merits, and demerits. Measures of Dispersion

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Session 3

Probabilities: Definition, Addition and multiplication theorem, problems based on probabilities, Binomial & Poisson Distributions, Normal distribution, and its properties

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Session 4

Introduction to Sampling Methods, Sampling versus Complete Enumeration, Simple Random Sampling with and without replacement, Use of Random Number Tables for selection of Simple Random Sample

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Session 5

Introduction to Test of Significance, One sample & two-sample test t for Means

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Session 6

Chi-Square Test of Independence of Attributes in 2 ×2 Contingency Table

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Session 7

Correlation: Definition, Types, properties, scatter diagram and testing

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Session 8

Regression: Definition, Fitting of regression lines, properties, the relation between correlation and regression

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Session 9

Introduction to experimental design, basic principles, ANOVA & its assumption

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Session 10

Completely Randomized Design: layout and analysis

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Session 11

Randomized Block Design: Layout and Analysis

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Session 12

Latin Square Design: layout and Analysis

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Question bank

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