# Statistics & Mathematics for Data Science & Data Analytics

### Statistics & Mathematics for Data Science & Data Analytics

*This course is the one course you take in statistic that is equipping you with the actual knowledge you need in statistics if you work with data.*

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Statistics and mathematics are fundamental to the field of data science and data analytics. A strong foundation in these subjects is essential for understanding and working with data.

Statistics is the science of collecting, analyzing, and interpreting data. It involves using statistical methods and techniques to understand patterns and trends in data, and to make predictions and decisions based on that data. Some key areas of statistics that are important for data science and data analytics include descriptive statistics, probability theory, hypothesis testing, and regression analysis.

Mathematics, on the other hand, is the study of quantities, shapes, and relationships. It is a broad field that encompasses a wide range of subdisciplines, including algebra, geometry, calculus, and linear algebra. In data science and data analytics, mathematics is used to model and analyze data, and to develop algorithms and machine learning models.

Both statistics and mathematics are essential for data science and data analytics. A strong background in these subjects can help you understand and work with data more effectively, and can also make you a more competitive job candidate in the field. If you're interested in pursuing a career in data science or data analytics, it's important to have a solid foundation in both statistics and mathematics.

#### What you'll learn

- Master the fundamentals of statistics for data science & data analytics
- Master descriptive statistics & probability theory
- Machine learning methods like Decision Trees and Decision Forests
- Probability distributions such as Normal distribution, Poisson Distribution and more
- Hypothesis testing, p-value, type I & type II error
- Logistic Regressions, Multiple Linear Regression, Regression Trees
- Correlation, R-Square, RMSE, MAE, coefficient of determination and more