Acerca de este Curso

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Certificado para compartir
Obtén un certificado al finalizar
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. 15 horas para completar
Inglés (English)

Habilidades que obtendrás

Bayesian StatisticsPython ProgrammingStatistical Modelstatistical regression
Certificado para compartir
Obtén un certificado al finalizar
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. 15 horas para completar
Inglés (English)

ofrecido por

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Universidad de Míchigan

Programa - Qué aprenderás en este curso

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Semana
1

Semana 1

3 horas para completar

WEEK 1 - OVERVIEW & CONSIDERATIONS FOR STATISTICAL MODELING

3 horas para completar
8 videos (Total 73 minutos), 6 lecturas, 1 cuestionario
8 videos
Fitting Statistical Models to Data with Python Guidelines5m
What Do We Mean by Fitting Models to Data?18m
Types of Variables in Statistical Modeling13m
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 ejercicio de práctica
Week 1 Assessment15m
Semana
2

Semana 2

5 horas para completar

WEEK 2 - FITTING MODELS TO INDEPENDENT DATA

5 horas para completar
6 videos (Total 85 minutos), 4 lecturas, 3 cuestionarios
6 videos
Linear Regression Inference15m
Interview: Causation vs Correlation18m
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

Semana 3

4 horas para completar

WEEK 3 - FITTING MODELS TO DEPENDENT DATA

4 horas para completar
8 videos (Total 121 minutos), 2 lecturas, 2 cuestionarios
8 videos
Multilevel Linear Regression Models21m
Multilevel Logistic Regression models14m
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

Semana 4

3 horas para completar

WEEK 4: Special Topics

3 horas para completar
6 videos (Total 105 minutos), 3 lecturas, 1 cuestionario
6 videos
Bayesian Approaches to Statistics and Modeling15m
Bayesian Approaches Case Study: Part I13m
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 ejercicio de práctica
Week 4 Python Assessment20m

Reseñas

Principales reseñas sobre FITTING STATISTICAL MODELS TO DATA WITH PYTHON

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Acerca de Programa especializado: Statistics with Python

Statistics with Python

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