For a Poisson distribution, if mean (m) = 1, then P(1) is: | Agrigyan

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ICAR AIEEA PG Statistical Science 14 July 2023 Shift-1 Paper (Q.59)

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For a Poisson distribution, if mean ($m$) = $1$, then $P(1)$ is:

एक प्वासों बंटन के लिए, यदि माध्य ($m$) = $1$ है, तो $P(1)$ का मान क्या होगा?

$1$ $1$ $1/e$ $1/e$ $e$ $e$ $e/2$ $e/2$

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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 Active 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

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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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