module 1 : 2025_ITC_Module 1_DATA COMPRESSION_Need, Types, Measuring Parameters VLC1.pptx - Google Drive

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Q1. How the probability of event relates to the degree of uncertainty CO1 Understanding and information contents?

The probability of an event is directly connected with the uncertainty of its occurrence. If an event has a high probability (close to 1), there is little uncertainty associated with it. Conversely, if the probability is low (close to 0), the uncertainty is high.

In Information Theory, the information content of an event is measured by the negative logarithm of its probability, i.e.,

I(x)=−log⁡2P(x)I(x) = -\log_2 P(x)

• If the probability is high (e.g., 0.9), then information content is low since the event is almost certain.
• If the probability is low (e.g., 0.01), then information content is very high since the event is surprising.

Thus, information is inversely related to probability and directly related to uncertainty. This concept is the foundation of entropy and coding efficiency in Information Theory.

📖 Reference: ITC M1 Part 2, pg. on Variable Size Codes & Entropy explanation.

Q2. Justify the statement “Information is the key to success” CO1 Evaluating

Information plays a vital role in decision-making, planning, and control. In every field, success depends on making the right decisions at the right time, and this is only possible when accurate and relevant information is available.