Cumulative Distribution Function CDF & Probability Density Function PDF in Random Variable

Cumulative Distribution Function CDF & Probability Density Function PDF in Random Variable is explained by the following outlines:

0. Random Variables
1. Cumulative Distribution Function CDF
2. Probability Density Function PDF
3. Basics of CDF
4. Basics of PDF
5. Relation in between CDF and PDF
6. Example of CDF and PDF

Chapter-wise detailed Syllabus of the Digital Communication Course is as follows:

Block Diagram of Digital communication system, Advantages, and disadvantages of digital communication system, Scrambling, Regenerative Repeater, Eye Diagram, Attention of signal, Bit rate and Baud rate.

Amplitude Shift Keying ASK, Frequency Shift Keying FSK, Phase Shift Keying PSK, Differential Phase Shift keying DPSK, Quadrature Phase Shift Keying QPSK, Binary Phase Shift Keying BPSK, M array Frequency Shift Keying MFSK, Quadrature Amplitude Modulation QAM, Comparison of QAM and PSK.

Sampling, Aliasing, Nyquist rate, Types of sampling, Performance comparison of sampling, PWM - Pulse width modulation, PPM - Pulse Position modulation, Performance comparison of PAM, PWM and PPM, Quantization and its parameters, SNR of Quantization, Uniform Quantization, Pulse Code Modulation PCM, Nonuniform Quantization, Companding basics, A law and Mu law for Nonuniform quantization, Differential Pulse Code Modulation DPCM, Delta Modulation DM, Adaptive Delta Modulation ADM.

Examples on TDM, Examples on T1 carrier system.

Basic of Line Coding Techniques, Pulse shaping techniques, NRZ, RZ & Manchester coding, PSD of NRZ unipolar line coding scheme, PSD of NRZ polar line coding scheme, PSD of NRZ bipolar line coding scheme, PSD of Manchester polar line coding scheme, Comparison of Unipolar, Polar, Bipolar and Manchester Line coding scheme.

Basics of Information, Basics of Entropy, Shannon Fano Encoding, Huffman Coding, Lempel Ziv Coding, Shannon Hartley theorem, basics of probability, Random variables, Cumulative distribution function CDF, Probability Density function PDF.

Block Codes, Hamming Codes, Linear Block Codes, Cyclic Codes, Convolutional Codes, Code Trellis, Viterbi Algorithm, Block Codes for single parity checks, Block Codes for product codes, Block Codes for Repetition codes, Cyclic codes for a systematic codeword, Cyclic codes for nonsystematic codeword.

Basics of Spread Spectrum Modulation, Frequency Hoping Spread Spectrum FHSS, Direct Sequence Spread Spectrum DSSS.

Engineering Funda channel is all about Engineering, Technology, and Science. This video is a part of Digital communication.

#RandomVariables #CDF #DigitalCommunication @EngineeringFunda

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[hamzasaeed]

Your explaining method is very easy to understand. At first attempt i understood the concept of PDF and CDF. Thanks 😊 a lot Sir

[danishmehboob]

I have been striking my head into the wall for a long time but could not get this point that how differentiation of CDF is equal to PDF. Finally, I got this point. Thank you so much.

[savaneenirasha]

Very clear your presentation.any one can understand easily. I had a problem about this two concepts. Now I have clear idea about it.thank you.

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[dottosebastianophilipo]

Thanks a lot
You make me more strong in this topic
From TANZANIA🇹🇿🇹🇿

[ArunKumar-nggb]

Have watched many videos but understood the concept here only.. thanks

[kvs]

Thank you soo much sir... After 4-5 videos I got this perfect video! And also understanding the funda of differentiation and integration...solid..🙏

[Omprakash-whrb]

cdf is integration of pdf if graph is continuous and if graph is discrete then cdf is addition of pdf
Thank u sir

[navinj]

nice teaching sir. I really understand what you explain.

[hemantpatro]

i watched so many videos of this topic but i understood by this video. Thanks sir

[danastantasaoufmridula]

best video ! Thank you sir for your excellent explanation.

[kasturiahir]

Engineer fun k sbhi video bhot ache hai sir notes bhi provide kriye sth m Taki Hum marks bhi le ske

[adimulamdevarajulu]

Thank you so much sir
This video clears my doubts 🙏👍

[hinarehman]

Amazing explanation and presentation as well, 👌👌
Easily understandable.
Keep it up👍👍
Thank you
JazakAllahu khair..

[discoverdevops]

probability density function and probability distribution function are not same

[ajaykarthik]

Thank you sir! You've helped me a lot!

[edwinr]

it was very much easy sir...i'm impressed with our steps

[rishabhjain]

Nice explanation but it would have been great if you could add subtitles /captions to the video.

[sandeep]

wrong at time 0:36, Probability distribution functions are defined for the discrete random variables while probability density functions are defined for the continuous random variables.