Predictive Statistics focuses on using historical data to forecast future outcomes and trends. It employs regression analysis, including linear, multiple, and logistic regression, to model relationships between variables. Time series analysis techniques like ARIMA and exponential smoothing predict trends and seasonal patterns. Classification methods such as decision trees, random forests, and support vector machines aid in categorizing data. Predictive statistics also incorporates clustering techniques like K-means for pattern recognition and feature engineering to enhance model accuracy.
Certification Exam Code | : | DA-CL-STS-26 |
Certification Name | : | Associate Certificate in Predictive Statistics & Machine Learning |
Difficulty Level | : | Associate |
Mode | : | Online |
Exam Proctoring | : | AI Proctored |
No. of Questions | : | 35-45 |
Online Exam Duration | : | 35-50 Minutes |