Acerca de este Curso
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100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

Completion of the first two courses in this specialization; high school-level algebra

Aprox. 13 horas para completar

Sugerido: 4 weeks; 4-6 hours/week...

Inglés (English)

Subtítulos: Inglés (English), Coreano

Habilidades que obtendrás

Bayesian StatisticsPython ProgrammingStatistical Modelstatistical regression

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Nivel intermedio

Completion of the first two courses in this specialization; high school-level algebra

Aprox. 13 horas para completar

Sugerido: 4 weeks; 4-6 hours/week...

Inglés (English)

Subtítulos: Inglés (English), Coreano

Programa - Qué aprenderás en este curso

Semana
1
3 horas para completar

WEEK 1 - OVERVIEW & CONSIDERATIONS FOR STATISTICAL MODELING

7 videos (Total 67 minutos), 6 readings, 1 quiz
7 videos
Different Study Designs Generate Different Types of Data: Implications for Modeling9m
Objectives of Model Fitting: Inference vs. Prediction11m
Plotting Predictions and Prediction Uncertainty8m
Python Statistics Landscape2m
6 lecturas
Course Syllabus5m
Meet the Course Team!10m
Help Us Learn More About You!10m
About Our Datasets2m
Mixed effects models: Is it time to go Bayesian by default?15m
Python Statistics Landscape1m
1 ejercicios de práctica
Week 1 Assessment15m
Semana
2
5 horas para completar

WEEK 2 - FITTING MODELS TO INDEPENDENT DATA

6 videos (Total 85 minutos), 4 readings, 3 quizzes
6 videos
Logistic Regression Introduction15m
Logistic Regression Inference7m
NHANES Case Study Tutorial (Linear and Logistic Regression)17m
4 lecturas
Linear Regression Models: Notation, Parameters, Estimation Methods30m
Try It Out: Continuous Data Scatterplot App15m
Importance of Data Visualization: The Datasaurus Dozen10m
Logistic Regression Models: Notation, Parameters, Estimation Methods30m
3 ejercicios de práctica
Linear Regression Quiz20m
Logistic Regression Quiz15m
Week 2 Python Assessment20m
Semana
3
4 horas para completar

WEEK 3 - FITTING MODELS TO DEPENDENT DATA

8 videos (Total 121 minutos), 2 readings, 2 quizzes
8 videos
Practice with Multilevel Modeling: The Cal Poly App12m
What are Marginal Models and Why Do We Fit Them?13m
Marginal Linear Regression Models19m
Marginal Logistic Regression11m
NHANES Case Study Tutorial (Marginal and Multilevel Regression)10m
2 lecturas
Visualizing Multilevel Models10m
Likelihood Ratio Tests for Fixed Effects and Variance Components10m
2 ejercicios de práctica
Name That Model15m
Week 3 Python Assessment20m
Semana
4
3 horas para completar

WEEK 4: Special Topics

6 videos (Total 105 minutos), 3 readings, 1 quiz
6 videos
Bayesian Approaches Case Study: Part II19m
Bayesian Approaches Case Study - Part III23m
Bayesian in Python19m
3 lecturas
Other Types of Dependent Variables20m
Optional: A Visual Introduction to Machine Learning20m
Course Feedback10m
1 ejercicios de práctica
Week 4 Python Assessment20m
4.3
14 revisionesChevron Right

Principales revisiones sobre Fitting Statistical Models to Data with Python

por AFMar 12th 2019

The course is actually pretty good, however the mix between basic subjects (like univariate linear regression) and relatively advanced topics (marginal models) may discourage some students.

por JXJun 30th 2019

Really thorough and in-depth material about statistical models with python.

Instructores

Avatar

Brenda Gunderson

Lecturer IV and Research Fellow
Department of Statistics
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Brady T. West

Research Associate Professor
Institute for Social Research
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Kerby Shedden

Professor
Department of Statistics

Acerca de Universidad de Míchigan

The mission of the University of Michigan is to serve the people of Michigan and the world through preeminence in creating, communicating, preserving and applying knowledge, art, and academic values, and in developing leaders and citizens who will challenge the present and enrich the future....

Acerca de Programa especializado Statistics with Python

This specialization is designed to teach learners beginning and intermediate concepts of statistical analysis using the Python programming language. Learners will learn where data come from, what types of data can be collected, study data design, data management, and how to effectively carry out data exploration and visualization. They will be able to utilize data for estimation and assessing theories, construct confidence intervals, interpret inferential results, and apply more advanced statistical modeling procedures. Finally, they will learn the importance of and be able to connect research questions to the statistical and data analysis methods taught to them....
Statistics with Python

Preguntas Frecuentes

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  • Cuando te inscribes en un curso, obtienes acceso a todos los cursos que forman parte del Programa especializado y te darán un Certificado cuando completes el trabajo. Se añadirá tu Certificado electrónico a la página Logros. Desde allí, puedes imprimir tu Certificado o añadirlo a tu perfil de LinkedIn. Si solo quieres leer y visualizar el contenido del curso, puedes auditar el curso sin costo.

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