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Download the Agriculture E-Course pdf of Elementary Statistics for B.Sc. Agriculture. PDF of Elementary Statistics e-Krishi Shiksha pdf for B.Sc. Agriculture is systematically arranged with a content index.

Name of Topic in E-Course pdf of Elementary Statistics for B.Sc. Agriculture.

1. Data – definition – Collection of data – Primary and secondary data – Classification of data – Qualitative and quantitative data
2. Diagrammatic representation of data – uses and limitations – simple, Multiple, Component and percentage bar diagrams – pie chart
3. Graphical representation – Histogram – Frequency polygon and Frequency curve
4. Measures of averages – Mean – median – mode – geometric mean – harmonic mean – computation of the above statistics for raw and grouped data – merits and demerits – measures of location – percentiles – quartiles – computation of the above statistics for raw and grouped data
5. Measures of dispersion – Range, Variance -Standard deviation – co-efficient of variation – computation of the above statistics
   for raw and grouped data
6. Probability – Basic concepts-trial- event-equally likely mutually exclusive – independent event, additive and multiplicative laws. Theoretical distributions discrete and continuous distributions, Binomial distributions-properties
7. Poisson Distributions – properties, Normal Distributionsproperties
8. Sampling-basic concepts- sampling vs complete enumeration parameter and statistic-sampling methods-simple random sampling and stratified random sampling
9. Test of significance – Basic concepts – null hypothesis – alternative hypothesis – level of significance – Standard error and its importance – steps in testing
10. T-test – definition – assumptions – test for equality of two means-independent and paired t-test
11. Attributes- Contingency table – 2×2 contingency table – Test for the independence of attributes – test for goodness of fit of mendelian ratio
12. Correlation – definition – Scatter diagram -Pearson’s correlation co-efficient – properties of the correlation coefficient
13. Regression – definition – fitting of simple linear regression equation – testing the significance of the regression coefficient
14. Design of experiments – basic concepts – treatment – experimental unit – experimental error – basic principle – replication, randomization and local control
15. Completely randomized design – description – layout – analysis – advantages and disadvantages
16. Randomized blocks design – description – layout – analysis – advantages and disadvantages
17. Latin square design – description – layout – analysis – advantages and disadvantages.
18. Factorial experiments – factor and levels – types – symmetrical and asymmetrical – simple, main and interaction effects – advantages and disadvantages
19. Factorial Experiments in RBD – lay out – analysis
20. Factorial experiments in RBD – lay out – analysis
21. Split plot design – layout – ANOVA Table
22. Long term experiments – ANOVA table – guard rows – optimum plot size – determination methods.

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