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Questions and Answers
What is the primary purpose of mathematical methods in data science?
What is the difference between a population and a sample in statistical analysis?
Which of the following is NOT one of the statistical models mentioned in the text?
Which mathematical concept is NOT mentioned as being part of mathematical methods in data science?
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What is the purpose of using statistical techniques in data science?
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Study Notes
Mathematical Methods in Data Science
- A set of mathematical techniques used to organize and manipulate data for decision making and testing theories
- Covers a broad range of mathematical tools, including:
- Calculus
- Linear algebra
- Optimization
- Network analysis
- Probability
- Differential equations
Statistical Techniques
- Used to report on populations and samples
- A population is a complete set of people with a specialized set of characteristics
- A sample is a subset of the population
Statistical Models
- Can be either:
- Descriptive Statistics
- Inferential Statistics
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Description
Explore a set of mathematical techniques commonly used by data scientists to analyze, organize and manipulate data. This quiz covers various tools such as calculus, linear algebra, optimization, network analysis, probability, differential equations, and statistical techniques for reporting on populations and samples.
