Right Answer: Classification analysis is a data analysis technique used to categorize data into predefined classes or groups. It works by using algorithms to learn from a training dataset, where the outcomes are known, and then applying this learned model to classify new, unseen data based on its features. Common algorithms include decision trees, logistic regression, and support vector machines.
Right Answer: Data normalization is the process of organizing data in a database to reduce redundancy and improve data integrity. It involves structuring the data into tables and defining relationships between them. Normalization is important because it helps eliminate duplicate data, ensures data consistency, and makes it easier to maintain and update the database.
Right Answer: The different types of data distributions include:
1. Normal Distribution
2. Binomial Distribution
3. Poisson Distribution
4. Uniform Distribution
5. Exponential Distribution
6. Log-Normal Distribution
7. Geometric Distribution
8. Beta Distribution
9. Chi-Squared Distribution
10. Student's t-Distribution
Right Answer: Exploratory Data Analysis (EDA) is the process of analyzing and summarizing datasets to understand their main characteristics, often using visual methods. It helps identify patterns, trends, and anomalies in the data before applying formal modeling techniques.
