Basic Statistics and Data Mining for Data Science
Apply popular statistical methods to data science
Created by Jesus Salcedo
Explore essential statistics and data mining techniques that form the backbone of data science. Build a strong foundation in analyzing, summarizing, and interpreting data using practical, real-world examples. Gain confidence in applying statistical methods to support data-driven decisions.
Packt | Dec 2017 | 178 min
What You Will Learn
You will work through practical examples that demonstrate how to analyze and summarize data, select appropriate statistical tests, and interpret results. Each topic is explained with clear, step-by-step guidance, focusing on application rather than theory. By practicing these methods, you will develop the skills needed to tackle common data science problems.
Key Features
- Analyze and summarize data using key statistical techniques for real-world datasets
- Interpret results from t-tests, ANOVA, chi-square, and correlation analyses
- Choose and apply the right statistical method for different data science scenarios
Target Audience
Designed for developers and professionals with some experience in programming or data analysis who want to deepen their understanding of statistics for data science. If you are aiming to apply statistical techniques confidently in your projects or transition into a data science role, this course will help you achieve those goals.
