Insights into Uncertainty: Probability Distributions for Data Scientists

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In data science, several probability distributions play crucial roles in modeling and analyzing different types of data. Understanding these distributions is essential for making informed decisions, building statistical models, and drawing valid conclusions from data. Here are some important probability distributions in data science:

I. TYPES OF DISTRIBUTIONS:

1. Discrete Probability Distribution:

• In a discrete distribution, the random variable takes on a countable number of distinct values.
• Probability mass function (PMF) describes the probability of each possible outcome.
• Examples include the binomial distribution, Poisson distribution, and hypergeometric distribution.

2. Continuous Probability Distribution:

• In a continuous distribution, the random variable can take any value within a given range.
• Probability density function (PDF) represents the likelihood of the variable falling within a particular interval.
• Examples include the normal distribution, exponential distribution, and uniform distribution.

II. Key Probability…