Career Path: Statistics

This roadmap builds strong statistical thinking required for data analysis, data science, machine learning, and research-oriented roles.

Phase 1: Mathematical Foundations

Build the math fundamentals required for statistics.

Mathematics

Phase 2: Descriptive Statistics

Summarize and understand data using statistical measures.

Statistics Descriptive Analysis

Phase 3: Probability Theory

Understand randomness, distributions, and probability models.

Probability Random Variables

Phase 4: Statistical Inference

Draw conclusions from data using inference techniques.

Hypothesis Testing Confidence Intervals

Phase 5: Regression & Modeling

Model relationships between variables.

Regression Analysis Statistical Modeling

Phase 6: Applied Statistics

Apply statistics to real-world datasets and problems.

EDA Case Studies

Phase 7: Statistical Tools & Practice

Use tools to apply statistical concepts effectively.

Excel (Statistics) SPSS

Phase 8: Projects & Career Readiness

Build statistical projects and prepare for analytical roles.

Statistics Projects Portfolio Interview Prep