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Statistics is the science and practice of developing human knowledge through the use of empirical data expressed in quantitative form.It is based on statistical theory which is supposed to be a branch of applied mathematics.Within statistical theory, randomness and uncertainty are modeled by probability theory.
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Topics for Probability and Statistics in Engineering Assignment help :
- Calculus-based introduction to probability , statistics with an emphasis on practical problem-solving, Basic combinatorics. Additive and multiplicative principles, permutations, combinations, binomial coefficients and Pascal’s triangle, multinomial coefficients, Kolmogorov’s axioms of probability, Events, outcomes, sample spaces, basic properties of probability, Finite uniform probabilities, Philosophies of probability, Conditional probability, Bayes’ formula, independent events, Markov chains, Random variables
- Discrete random variables/distributions, expectation, variance, Bernoulli and binomial distributions, geometric distribution, negative binomial distribution, expectation of a sum, cumulative distribution functions, Continuous random variables, expectation and variance, Uniform continuous distributions, normal distributions, Poisson processes, exponential distributions; gamma, Weibull, Cauchy, and beta distributions, Joint random variables, Their distributions, independent random variables, and their sums
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Complex topics covered by Probability and Statistics in Engineering Assignment online experts :
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- Bayes' Theorems, discrete random variables , continuous random variables , vectors, Bernoulli trial sequence , Poisson process models, conditional distributions, functions of random variables , statistical moments, second-moment uncertainty propagation, second-moment conditional analysis, exponential probability model, gamma probability model, normal probability model, lognormal probability model, uniform probability model, beta probability model, extreme-type distributions, Sample Spaces , Events, Probability Axioms Rules, Conditional Probability, Total Probability, Independence, Bayes’ Theorem, Discrete Random Variables, PMF, CDF, Expected Values, Discrete Distributions
- Continuous Random Variables, Continuous Distributions, Multiple Discrete Random Variables, Multiple Continuous Random Variables, Covariate, Correlation, Bivariate Normal Distribution, Functions of Random Variables, Sampling, Central Limit Theorem, Confidence Intervals , Hypothesis Testing, Linear Regression, concepts in probability,combinatorics,independence,conditional probability,Bayes’ rule,discrete and continuous probability distributions,statistical concepts,means,variances,types of graphs,R,statistical inference,hypothesis testing and regression,The Role of Statistics in Engineering ,Probability ,Discrete Random Variables and Probability Distributions ,Continuous Random Variables and Probability Distributions,Joint Probability Distributions ,Descriptive Statistics,Sampling Distributions and Point Estimation of Parameters ,Statistical Intervals for a Single Sample
Applied Linear Regression
Regression and correlation Analysis