En este curso adquirirás los métodos estadísticos para la toma de decisiones en los negocios, así como herramientas tecnológicas para desarrollar habilidades cuantitativas.
Welcome to the advanced course on "Statistical Foundations for Data Science and Decision Making"! This comprehensive program is designed to equip you with essential statistical skills crucial for data analysis and informed decision-making in today's data-driven world. Through a blend of theoretical concepts and practical applications, you'll develop a strong foundation in descriptive statistics, probability distributions, and interval estimation techniques.
1.1 Data types; Measurement scales; Organization of qualitative and quantitative data; Graphical representation
1.2 Measures of central tendency; Position measures; Dispersion measures; Descriptive statistics on your laptop
2.1 Discrete random variable; Density and cumulative probability functions; Mean and variance of a discrete random variable; Fundamental properties
2.2 Poisson distribution; Binomial distribution
3.1 Continuous random variable; Density and cumulative probability functions; Mean and variance of a continuous random variable; Fundamental properties
3.2 Uniform distribution; Normal distribution
4.1 Calculation of confidence intervals; Calculation of sample size necessary for a given estimation error
4.2 Student's t-distribution
This course offers a perfect blend of theoretical knowledge and practical skills, preparing you to tackle real-world data challenges with confidence. Don't miss this opportunity to elevate your statistical expertise and become a more effective decision-maker in the age of big data!
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'Statistical and Probabilistic Foundations of AI' provides an accessible overview of the mathematics and statistics behind fundamental concepts of data science, machine learning, and artificial intelligence. It covers descriptive and exploratory data analysis and a brief introduction to inferential statistics. It provides the principles of probability necessary to understand the methods used in inferential statistics and machine learning at an introductory level.
This course introduces the basic tools and methods of statistical analysis, which can be applied to a wide variety of situations and data encountered in the areas of business and economics. Topics discussed include descriptive statistics, probability, sampling distributions, estimation, and hypothesis testing. By the end of the semester students should be able to compute and interpret basic descriptive statistical measures, understand the basic concepts of probability, and apply techniques of statistical inference.
The first in a series of four courses which help you to master statistics fundamentals and build your quantitative skillset for progression in high-growth careers, or to use as step towards further study at undergraduate level.
This course provides an introduction to basic statistical concepts. We begin by walking through a library of probability distributions – including the normal distribution, which in turn leads to the Central Limit Theorem. We then discuss elementary descriptive statistics and estimation methods.
En este curso adquirirás los métodos estadísticos para la toma de decisiones en los negocios, así como herramientas tecnológicas para desarrollar habilidades cuantitativas.
Áreas como el “big data” requieren un conocimiento muy claro de la estadística; en las áreas de negocios, la tecnología pone a nuestro alcance diversas aplicaciones que requieren una sólida formación en estadística para su correcto uso e interpretación.
