Let V and W be vector spaces and T: V W be a linear... | Agrigyan

General Agriculture, Economics & Extension Mathematics Statistical Methods & Experimental Designs Computer Applications & Bioinformatics
78
ICAR AIEEA PG Statistical Science 14 July 2023 Shift-1 Paper
MCQ (Single Correct)
English हिन्दी
Let $V$ and $W$ be vector spaces and $T: V \to W$ be a linear transformation. Then:
मान लीजिए $V$ और $W$ सदिश समष्टियां हैं तथा $T: V \to W$ एक रैखिक रूपांतरण है। तब:

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General Agriculture, Economics & Extension

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Agronomy, Agro-Climatic Zones, Cropping Systems, Tillage and Soil Fertility Management Major Plant Diseases, Insect Pests, Weeds and Integrated Pest Management (IPM) Plant Physiology, Mineral Nutrition, Genetics and Plant Breeding Fundamentals Historical Milestones, Agricultural Research Infrastructure and ICAR Institutes Micro & Macro Economics: Demand, Supply, Production Costs and Market Structures Agricultural Marketing, Market Intermediaries, Price Policy, MSP and Buffer Stocking Agricultural Finance, Credit Institutions (NABARD, RRBs, Commercial Banks) and KCC Extension Education Principles, Rural Development Programs and Community Reconstruction

Mathematics

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Differential Calculus: Limits, Continuity, Differentiability, Successive Differentiation and Expansion of Functions Sequences and Series: Arithmetic, Geometric, Harmonic Progressions and Infinite Series Convergence Matrices and Determinants: Matrix Operations, Rank, Inverse, Systems of Linear Equations and Eigenvalues Active Sets, Relations, Functions, Mathematical Induction and Theory of Equations Integral Calculus: Definite and Indefinite Integrals, Reduction Formulas and Areas Under Curves Differential Equations: First Order Ordinary Differential Equations, Linear Differential Equations with Constant Coefficients Applications of Derivatives: Tangents, Normals, Maxima-Minima, Mean Value Theorems and Indeterminate Forms Numerical Methods: Interpolation, Numerical Differentiation, Integration (Trapezoidal, Simpson) and Root Finding Coordinate Geometry: Straight Lines, Circles, Parabola, Ellipse and Hyperbola in Two Dimensions

Statistical Methods & Experimental Designs

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Theoretical Discrete Probability Distributions: Bernoulli, Binomial, Poisson, Geometric and Hypergeometric Design of Experiments: Principles of Experimentation, CRD, RBD, Latin Square Design (LSD) and Factorial Experiments Probability Theory: Classical, Axiomatic Definitions, Addition, Multiplication Theorems and Bayes Theorem Small Sample Tests: Students t-test, Snedecors F-test, Chi-Square Test of Goodness of Fit and Contingency Tables Measures of Central Tendency: Arithmetic Mean, Geometric Mean, Harmonic Mean, Median and Mode Theoretical Continuous Probability Distributions: Uniform, Normal, Exponential, Beta and Gamma Distributions Sampling Theory: Census vs Sample Survey, Sampling Errors, SRSWOR, SRSWR, Stratified, Systematic and Cluster Sampling Measures of Dispersion: Range, Quartile Deviation, Mean Deviation, Standard Deviation and Coefficient of Variation Testing of Hypotheses: Null and Alternative Hypotheses, Type I and II Errors, Significance Level, Large Sample Tests (Z-test) Collection, Classification and Tabulation of Data, Frequency Distributions and Graphical Representations Regression Analysis: Simple and Multiple Linear Regression, Least Squares Principle, Properties and R-Squared Random Variables, Probability Mass and Density Functions, Expectation and Moment Generating Functions Correlation Analysis: Simple, Partial, Multiple Correlation, Pearson Coefficient and Rank Correlation Moments, Skewness (Karl Pearson, Bowley) and Kurtosis

Computer Applications & Bioinformatics

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Computer Networks and Internet: Topologies (LAN, WAN, MAN), OSI Model, TCP/IP, Protocols (HTTP, FTP) and Web Computer Architecture and Hardware: Generations of Computers, CPU, Memory Hierarchy (RAM, ROM, Cache), Input-Output System Software and Operating Systems: Functions of OS, DOS Commands, Windows OS, Linux/Unix Architecture Application Software: Word Processing, Spreadsheets (MS Excel Formulas, Functions, Charts), DBMS Basics Number Systems and Boolean Algebra: Binary, Octal, Hexadecimal Conversions, Logic Gates and Truth Tables Sequence Alignment and Computational Genomics: Pairwise and Multiple Alignment (BLAST, FASTA, Clustal), Scoring Matrices Cyber Security and Data Protection: Computer Viruses, Malware, Firewalls, Cryptography Basics and IPR Programming Fundamentals: Algorithms, Flowcharts, Control Structures, Loops, Functions, Arrays and Pointers in C/C++ Object-Oriented Programming and Modern Languages: Concepts of OOP (Classes, Objects, Inheritance), Python and R Introduction to Bioinformatics: Scope, Biological Databases (NCBI, GenBank, EMBL, UniProt, PDB) and Data Retrieval
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