Statistics with Python Using NumPy, Pandas, and SciPy

“Statistics with Python Using NumPy, Pandas, and SciPy” explores how to apply statistical and mathematical techniques to data science problems. Throughout the first half of the course, you’ll work on reviewing vector dot products, interpreting text as vectors, and matrix multiplication. You’ll also explore the basics of probability, laying the groundwork for statistical analysis. In the second half, you’ll cover how to interpret data distributions, reason about probability, explore the special properties of normal distributions, understand linear relationships in data, and the connection between probability and uncertainty. This is the third course in the four-course series “Data-Oriented Python Programming and Debugging,” where you’ll work to strengthen your programming capabilities and enhance your problem-solving skills

• Use vector operations in NumPy for applied mathematics
• Visualize and analyze data distributions using NumPy and SciPy
• Describe patterns in data distributions using statistics
• Conduct statistical inference using hypothesis testing computationally

• Basic familiarity with related concepts and terminology
• Readiness to practice through applied exercises or case-based work