From the course: Data Science and Analytics Career Paths and Certifications: First Steps
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Statistics
From the course: Data Science and Analytics Career Paths and Certifications: First Steps
Statistics
- [Instructor] Statistics lays a foundation for data science. In fact, statistics is where data science started. Therefore, developing a reasonable understanding of statistics is a must for a data scientist. In fact, the more you know about statistics, the better. At a minimum, a data scientist needs to be proficient with concepts such as probability, correlation, variables, distributions, regression, null hypotheses, significance tests, confidence intervals, t-tests, ANOVA, and chi-square. You also need to know how to use common statistical analysis tools, including R, Excel, and SAS. At a more advanced level, a data scientist needs to be familiar with concepts and algorithms like logistic regression, support vector machines, or SVMs, and Bayesian methods.
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