Coursera
Catálogo
  • Explorar
  • Buscar
  • For Enterprise
  • Inicia Sesión
  • Regístrarse

Inferential Statistics

Un vistazoProgramaPreguntas FrecuentesCreadoresTarifaCalificaciones y revisiones

InicioCiencia de DatosProbabilidad y Estadística

Inferential Statistics

Universidad Duke

Acerca de este curso: This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data


Creada por:  Universidad Duke
Universidad Duke

  • Mine Çetinkaya-Rundel

    Enseñado por:  Mine Çetinkaya-Rundel, Associate Professor of the Practice

    Department of Statistical Science
Información básica
Curso 2 de 5 en Statistics with R Specialization
NivelBeginner
Compromiso5 weeks of study, 5-7 hours/week
Idioma
English
Cómo aprobarAprueba todas las tareas calificadas para completar el curso.
Calificaciones del usuario
4.8 estrellas
Calificación promedio del usuario 4.8Ve los que los estudiantes dijeron
Programa
SEMANA 1
About the Specialization and the Course
This short module introduces basics about Coursera specializations and courses in general, this specialization: Statistics with R, and this course: Inferential Statistics. Please take several minutes to browse them through. Thanks for joining us in this course!
2 readings
  1. Reading: About Statistics with R Specialization
  2. Reading: More about Inferential Statistics
Central Limit Theorem and Confidence Interval
Welcome to Inferential Statistics! In this course we will discuss Foundations for Inference. Check out the learning objectives, start watching the videos, and finally work on the quiz and the labs of this week. In addition to videos that introduce new concepts, you will also see a few videos that walk you through application examples related to the week's topics. In the first week we will introduce Central Limit Theorem (CLT) and confidence interval.
7 videos, 4 readings, 1 practice quiz
  1. Reading: Lesson Learning Objectives
  2. Vídeo: Introduction
  3. Vídeo: Sampling Variability and CLT
  4. Vídeo: CLT (for the mean) examples
  5. Reading: Lesson Learning Objectives
  6. Vídeo: Confidence Interval (for a mean)
  7. Vídeo: Accuracy vs. Precision
  8. Vídeo: Required Sample Size for ME
  9. Vídeo: CI (for the mean) examples
  10. Reading: Week 1 Suggested Readings and Practice Exercises
  11. Practice Quiz: Week 1 Practice Quiz
  12. Reading: Week 1 Lab Instructions
Calificado: Week 1 Quiz
Calificado: Week 1 Lab
SEMANA 2
Inference and Significance
Welcome to Week Two! This week we will discuss formal hypothesis testing and relate testing procedures back to estimation via confidence intervals. These topics will be introduced within the context of working with a population mean, however we will also give you a brief peek at what's to come in the next two weeks by discussing how the methods we're learning can be extended to other estimators. We will also discuss crucial considerations like decision errors and statistical vs. practical significance. The labs for this week will illustrate concepts of sampling distributions and confidence levels.
7 videos, 4 readings, 1 practice quiz
  1. Reading: Lesson Learning Objectives
  2. Vídeo: Another Introduction to Inference
  3. Vídeo: Hypothesis Testing (for a mean)
  4. Vídeo: HT (for the mean) examples
  5. Reading: Lesson Learning Objectives
  6. Vídeo: Inference for Other Estimators
  7. Vídeo: Decision Errors
  8. Vídeo: Significance vs. Confidence Level
  9. Vídeo: Statistical vs. Practical Significance
  10. Reading: Week 2 Suggested Readings and Practice Exercises
  11. Practice Quiz: Week 2 Practice Quiz
  12. Reading: Week 2 Lab Instructions
Calificado: Week 2 Quiz
Calificado: Week 2 Lab
SEMANA 3
Inference for Comparing Means
Welcome to Week Three of the course! This week we will introduce the t-distribution and comparing means as well as a simulation based method for creating a confidence interval: bootstrapping. If you have questions or discussions, please use this week's forum to ask/discuss with peers.
11 videos, 4 readings, 1 practice quiz
  1. Reading: Lesson Learning Objectives
  2. Vídeo: Introduction
  3. Vídeo: t-distribution
  4. Vídeo: Inference for a mean
  5. Vídeo: Inference for comparing two independent means
  6. Vídeo: Inference for comparing two paired means
  7. Vídeo: Power
  8. Reading: Lesson Learning Objectives
  9. Vídeo: Comparing more than two means
  10. Vídeo: ANOVA
  11. Vídeo: Conditions for ANOVA
  12. Vídeo: Multiple comparisons
  13. Vídeo: Bootstrapping
  14. Reading: Week 3 Suggested Readings and Practice Exercises
  15. Practice Quiz: Week 3 Practice Quiz
  16. Reading: Week 3 Lab Instructions
Calificado: Week 3 Quiz
Calificado: Week 3 Lab
SEMANA 4
Inference for Proportions
Welcome to Week Four of our course! In this unit, we’ll discuss inference for categorical data. We use methods introduced this week to answer questions like “What proportion of the American public approves of the job of the Supreme Court is doing?”.
11 videos, 4 readings, 1 practice quiz
  1. Reading: Lesson Learning Objectives
  2. Vídeo: Introduction
  3. Vídeo: Sampling Variability and CLT for Proportions
  4. Vídeo: Confidence Interval for a Proportion
  5. Vídeo: Hypothesis Test for a Proportion
  6. Vídeo: Estimating the Difference Between Two Proportions
  7. Vídeo: Hypothesis Test for Comparing Two Proportions
  8. Reading: Lesson Learning Objectives
  9. Vídeo: Small Sample Proportions
  10. Vídeo: Examples
  11. Vídeo: Comparing Two Small Sample Proportions
  12. Vídeo: Chi-Square GOF Test
  13. Vídeo: The Chi-Square Independence Test
  14. Reading: Week 4 Suggested Readings and Practice Exercises
  15. Practice Quiz: Week 4 Practice Quiz
  16. Reading: Week 4 Lab Instructions
Calificado: Week 4 Quiz
Calificado: Week 4 Lab
SEMANA 5
Data Analysis Project
In this week you will use the data set provided to complete and report on a data analysis question. Please read the background information, review the report template (downloaded from the link in Lesson Project Information), and then complete the peer review assignment.
1 reading
  1. Reading: Project Information
Calificado: Data Analysis Project

Preguntas Frecuentes
Cómo funciona
Coursework
Coursework

Each course is like an interactive textbook, featuring pre-recorded videos, quizzes and projects.

Help from Your Peers
Help from Your Peers

Connect with thousands of other learners and debate ideas, discuss course material, and get help mastering concepts.

Certificates
Certificates

Earn official recognition for your work, and share your success with friends, colleagues, and employers.

Creadores
Universidad Duke
Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world.
Tarifa
Comprar curso
Accede a los materiales del curso

Disponible

Accede a los materiales con calificación

Disponible

Recibe una calificación final

Disponible

Obtén un Certificado de curso para compartir

Disponible

Calificaciones y revisiones
Calificado 4.8 de 5 901 calificaciones

r

Excellent Lecture, Thanks

Victorita Dolean

Excellent course with a lot of real life examples.

BR

Good course, gives you a solid foundation.

张

我认为是一个非常棒的课程,明了清晰。但是如果会在最后来一些总结的话就更好了



También te podría gustar
Johns Hopkins University
Regression Models
1 course
Johns Hopkins University
Regression Models
Ver curso
Johns Hopkins University
Statistical Inference
1 course
Johns Hopkins University
Statistical Inference
Ver curso
Johns Hopkins University
Exploratory Data Analysis
1 course
Johns Hopkins University
Exploratory Data Analysis
Ver curso
Johns Hopkins University
Getting and Cleaning Data
1 course
Johns Hopkins University
Getting and Cleaning Data
Ver curso
University of Amsterdam
Inferential Statistics
1 course
University of Amsterdam
Inferential Statistics
Ver curso
Coursera
Coursera brinda acceso universal a la mejor educación del mundo, al asociarse con las mejores universidades y organizaciones, para ofrecer cursos en línea.
© 2018 Coursera Inc. Todos los derechos reservados.
Descargar en la App StoreConsíguelo en Google Play
  • Coursera
  • Acerca de
  • Liderazgo
  • Empleo
  • Catálogo
  • Certificados
  • Grados
  • Para negocios
  • For Government
  • Comunidad
  • instituciones
  • Mentores
  • Traductores
  • Desarrolladores
  • Probador beta
  • Conectar
  • Blog
  • Facebook
  • LinkedIn
  • Twitter
  • Google+
  • Blog de Tecnología
  • Más
  • Términos
  • Privacidad
  • Ayuda
  • Accesibilidad
  • Prensa
  • Contacto
  • Directorio
  • Afiliados