## About this Video

The world of computers is **digital **in nature, but the quantities around us are **analog**! We’ll have to perform **analog-to-digital conversion **to effectively store, manipulate, and transmit analog information.

**Sampling **– The act of taking readings of analog information at intervals, is the strategy in which this can be achieved, but sampling comes with its own set of considerations. For example, how often should we sample?

This **sample rate **should be well chosen to prevent **aliasing **– Getting poor results from sampling too infrequently. Thankfully, we can make use of the **Nyquist-Shannon Sampling Theorem**, which tells us what sample rate to use to prevent aliasing from happening!

## Key Learning Points

- What is
**Sampling**and the meaning of**Sampling Rate** - What is
**Aliasing** - The
**Nyquist-Shannon Sampling Theorem** - Application of the Nyquist-Shannon Sampling Theorem

## Resources

Use the **NERDfirst Nyquist Theorem Simulator** to try it for yourself! See how a sampled signal is reconstructed as you adjust the **sampling rate** and signal frequency.