What is Statistics and its distributions?

• Statistics is the practice of collecting, analyzing, interpreting and presenting data to discover findings that are useful.
• A statistical distribution is a mathematical function that describes the probabilities of occurrence of different possible values for a random variable. In other words, it tells us how a set of data is spread out. They allow us to understand and quantify the uncertainty inherent in the world around us.
• It can be thought of as a graph of the data, showing where the values are concentrated and where they are more dispersed.

Understanding distributions is crucial in both statistics and machine learning for several reasons:

1. Understanding Data Patterns and Relationships
2. Choosing Appropriate Statistical Methods
3. Dealing with Uncertainty and Risk
4. Hypothesis Testing
5. Model Selection and Evaluation
6. Outlier Detection
7. Data Visualization

Statistics can be divided into two main branches: descriptive statistics and inferential statistics.

Inferential statistics

• Inferential statistics involve making predictions, inferences, or generalizations about a population based on a sample of data.
• Uses sample data to draw conclusions about a larger population.

Descriptive Statistics:

• Descriptive statistics aim to describe and summarize the main features of a dataset.
• It involves measures like mean, median, mode, range, variance, standard deviation, and percentiles.