Introduction to Statistics and its Applications in Agriculture, Types of Data. Scales of measurements of Data. Summarization of Data

Classification of Data, Methods of Classification, Frequency Distribution, Definition of Grouped and Ungrouped Data. Definition of Class Interval Width of CI, Types of Frequency Distribution.

Diagrammatic Presentation of Data. Bar Diagrams — Simple, Multiple, Sub-divided and Percentage Bar Diagrams. Pie-diagram Graphical Presentation of Data — Histogram, Frequency Polygon and Ogives.

Measures of Central Tendency. Requisites for an Ideal Measure of Central Tendency. Different Types of Measure. Arithmetic Mean— Definition, Properties, Merits, Demerits and Uses. A.M. (examples) for Grouped and Ungrouped Data. Step-deviation Method.

Weighted Mean. Definition of Geometric Mean and Harmonic Mean. Relationship between A.M., G.M. and H.M. Median Definition, Merits, Demerits and Uses. Graphical Location of Median.

Mode- Definition, Merits, Demerits and Uses. Graphical Location of Mode. Relationship between Mean, Median and Mode. Measures of Dispersion. Characteristics for an Ideal Measure of Dispersion. Different Types of Measures of Dispersions. Definition of Range, Interquartile Range, Quartile Deviation and Mean Deviation. Standard Deviation- Definition, Properties. S.D. and Variance for Grouped and Ungrouped Data. Variance of Combined Series. Coefficients of Dispersions. Co-efficient of Variation. Measures of Skewness and Kurtosis. Definition of Symmetrical Distribution. Definition of Skewness, Measures of Skewness. Definition of Kurtosis. Measure of Kurtosis. Relationship between Mean, Median and Mode for Symmetrical and Skewed Distribution. Probability Theory and Introduction to Probability. Basic Terminologies. Classical Probability-Definition and Limitations. Empirical Probability- Definition and Limitations. Axiomatic Probability. Addition and Multiplication Theorem (without proof). Conditional Probability. Independent Events. Simple Problems based on Probability. Definition of Random Variable. Discrete and Continuous Random Variable. Binomial, Poisson and Normal Distribution – Definition, Prob. Distribution, Mean and Variance. Normal Probability Curve. Correlation and Regression. Definition of Correlation. Scatter Diagram. Karl Pearson’s Coefficient of Correlation. Types of Correlation Coefficient. Properties of Correlation Coefficient Definition of Linear Regression. Regression Equations. Regression Coefficients. Properties of Regression Coefficients Tests of Significance. Definition. Null and Alternative Hypothesis. Type I and Type II Error. Critical Region and Level of Significance. One Tailed and Two Tailed Tests. Test Statistic. One Sample, Two Sample and Paired t-test with Examples. F-test for Variance. ANOVA and Experimental Designs. Definition of ANOVA. Assignable and Non-assignable Factors. Analysis of One-way and Two-way classified data Sampling Theory. Introduction. Definition of Population, Sample, Parameter and Statistic. Sampling Vs Complete Enumeration. Sampling Methods. Simple Random Sampling with Replacement and without Replacement. Use of Random Number Table.

Diagrammatic and Graphical representation of data.

Calculation of A.M., Median and Mode (Ungrouped and Grouped data).

Calculation of S.D. and C.V. (Ungrouped and Grouped data).

Fitting of Binomial and Poisson distribution

Correlation and Regression analysis.

Application of t-test (one sample, two sample independent and dependent).

Analysis of variance one-way and two-way classification.

Completely Randomized Design

Randomized Block Design

Selection of random sample using simple random sampling