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MA3302 TRANSFORMS AND STATISTICS
Unit 11.Half-range Sine and cosine series2.Root mean square valueDon't share as screenshot Stuff SEctor3.Harmonic Analysis( table sums in Fourier harmonic )UNIT-21.Fourier integral theoremDon't share as screenshot Stuff SEctor2.Sine and cosine transform3, Convolution theoremUNIT-31.Binomial, Poisson, Exponential and Normal distributions 2. Discrete and continuous random variablesDon't share as screenshot Stuff SEctorUNIT-41. Covariance,Correlation . Linear regression **Don't share as screenshot Stuff SEctor2. Central limit theorem**UNIT-51.Differences between means, variations and ratio of two variances2.Robustness .Method of momentsDon't share as screenshot -Stuff sector
**Very important questions are bolded and may be asked based on this topic
MA3302 TRANSFORMS AND STATISTICS
Don't share as screenshot -Stuff sector
**Very important questions are bolded and may be asked based on this topic
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*These questions are expected for the exams This may or may not be asked for exams All the best.... from admin Santhosh
Thanks for your love and support guys keep supporting and share let the Engineers know about Us and leave a comment below for better improvements If there is any doubt feel free to ask me I will clear if I can or-else I will say some solutions ..get me through WhatsApp for instant updates ~$tuff$£ctorSYllabuSUNIT I FOURIER SERIES
Dirichlet’s conditions – General Fourier series – Odd and even functions – Half-range Sine and
cosine series – Root mean square value - Parseval’s identity – Harmonic Analysis.
UNIT II FOURIER TRANSFORM
Fourier integral theorem – Fourier transform pair - Sine and cosine transforms – Properties –
Transform of elementary functions – Convolution theorem – Parseval’s identity.
UNIT III RANDOM VARIABLES
Discrete and continuous random variables – Moments – Moment generating functions – Binomial,
Poisson, Geometric, Uniform, Exponential and Normal distributions - Functions of a random
variable.
UNIT IV TWO-DIMENSIONAL RANDOM VARIABLES
Joint distributions – Marginal and conditional distributions – Covariance – Correlation and Linear
regression – Transformation of random variables – Central limit theorem (for independent and
identically distributed random variables).
UNIT V ESTIMATION THEORY
Unbiased estimators - Efficiency - Consistency - Sufficiency - Robustness - Method of moments -
Method of maximum Likelihood - Interval estimation of Means - Differences between means,
variations and ratio of two variances.
UNIT I FOURIER SERIES Dirichlet’s conditions – General Fourier series – Odd and even functions – Half-range Sine and cosine series – Root mean square value - Parseval’s identity – Harmonic Analysis. UNIT II FOURIER TRANSFORM Fourier integral theorem – Fourier transform pair - Sine and cosine transforms – Properties – Transform of elementary functions – Convolution theorem – Parseval’s identity. UNIT III RANDOM VARIABLES Discrete and continuous random variables – Moments – Moment generating functions – Binomial, Poisson, Geometric, Uniform, Exponential and Normal distributions - Functions of a random variable. UNIT IV TWO-DIMENSIONAL RANDOM VARIABLES Joint distributions – Marginal and conditional distributions – Covariance – Correlation and Linear regression – Transformation of random variables – Central limit theorem (for independent and identically distributed random variables). UNIT V ESTIMATION THEORY Unbiased estimators - Efficiency - Consistency - Sufficiency - Robustness - Method of moments - Method of maximum Likelihood - Interval estimation of Means - Differences between means, variations and ratio of two variances.