Ir al contenido principal

Statistical Thinking for Data Science and Analytics

Learn how statistics plays a central role in the data science approach.


Hay una sesión disponible:

¡Ya se inscribieron 218,966 usuarios!
Comienza el 6 dic

Statistical Thinking for Data Science and Analytics

Learn how statistics plays a central role in the data science approach.

5 semanas
7–10 horas por semana
A tu ritmo
Avanza a tu ritmo
Verificación opcional disponible

Hay una sesión disponible:

¡Ya se inscribieron 218,966! Una vez finalizada la sesión del curso, será archivadoAbre en una pestaña nueva.
Comienza el 6 dic

Sobre este curso

Omitir Sobre este curso

This statistics and data analysis course will pave the statistical foundation for our discussion on data science.

You will learn how data scientists exercise statistical thinking in designing data collection, derive insights from visualizing data, obtain supporting evidence for data-based decisions and construct models for predicting future trends from data.

De un vistazo

  • Institución: ColumbiaX
  • Tema: Informática
  • Nivel: Introductory
  • Prerrequisitos:

    High School Math. Some exposure to computer programming.

Lo que aprenderás

Omitir Lo que aprenderás
  • Data collection, analysis and inference
  • Data classification to identify key traits and customers
  • Conditional Probability-How to judge the probability of an event, based on certain conditions
  • How to use Bayesian modeling and inference for forecasting and studying public opinion
  • Basics of Linear Regression
  • Data Visualization: How to create use data to create compelling graphics

Plan de estudios

Omitir Plan de estudios

Week 1 – Introduction to Data Science

Week 2 – Statistical Thinking

  • Examples of Statistical Thinking
  • Numerical Data, Summary Statistics
  • From Population to Sampled Data
  • Different Types of Biases
  • Introduction to Probability
  • Introduction to Statistical Inference

Week 3 – Statistical Thinking 2

  • Association and Dependence
  • Association and Causation
  • Conditional Probability and Bayes Rule
  • Simpsons Paradox, Confounding
  • Introduction to Linear Regression
  • Special Regression Models

Week 4 – Exploratory Data Analysis and Visualization

  • Goals of statistical graphics and data visualization
  • Graphs of Data
  • Graphs of Fitted Models
  • Graphs to Check Fitted Models
  • What makes a good graph?
  • Principles of graphics

Week 5 – Introduction to Bayesian Modeling

  • Bayesian inference: combining models and data in a forecasting problem
  • Bayesian hierarchical modeling for studying public opinion
  • Bayesian modeling for Big Data

Acerca de los instructores

¿Te interesa este curso para tu negocio o equipo?

Train your employees in the most in-demand topics, with edX For Business.