課程信息
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第 3 門課程(共 3 門)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

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

完成時間大約為12 小時

建議:4 weeks; 4-6 hours/week...

英語(English)

字幕:英語(English), 韓語

您將獲得的技能

Bayesian StatisticsPython ProgrammingStatistical Modelstatistical regression

第 3 門課程(共 3 門)

100% 在線

立即開始,按照自己的計劃學習。

可靈活調整截止日期

根據您的日程表重置截止日期。

中級

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

完成時間大約為12 小時

建議:4 weeks; 4-6 hours/week...

英語(English)

字幕:英語(English), 韓語

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 3 小時

WEEK 1 - OVERVIEW & CONSIDERATIONS FOR STATISTICAL MODELING

We begin this third course of the Statistics with Python specialization with an overview of what is meant by “fitting statistical models to data.” In this first week, we will introduce key model fitting concepts, including the distinction between dependent and independent variables, how to account for study designs when fitting models, assessing the quality of model fit, exploring how different types of variables are handled in statistical modeling, and clearly defining the objectives of fitting models.

...
7 個視頻 (總計 67 分鐘), 6 個閱讀材料, 1 個測驗
7 個視頻
Different Study Designs Generate Different Types of Data: Implications for Modeling9分鐘
Objectives of Model Fitting: Inference vs. Prediction11分鐘
Plotting Predictions and Prediction Uncertainty8分鐘
Python Statistics Landscape2分鐘
6 個閱讀材料
Course Syllabus5分鐘
Meet the Course Team!10分鐘
Help Us Learn More About You!10分鐘
About Our Datasets2分鐘
Mixed effects models: Is it time to go Bayesian by default?15分鐘
Python Statistics Landscape1分鐘
1 個練習
Week 1 Assessment15分鐘
2
完成時間為 5 小時

WEEK 2 - FITTING MODELS TO INDEPENDENT DATA

In this second week, we’ll introduce you to the basics of two types of regression: linear regression and logistic regression. You’ll get the chance to think about how to fit models, how to assess how well those models fit, and to consider how to interpret those models in the context of the data. You’ll also learn how to implement those models within Python.

...
6 個視頻 (總計 85 分鐘), 4 個閱讀材料, 3 個測驗
6 個視頻
Logistic Regression Introduction15分鐘
Logistic Regression Inference7分鐘
NHANES Case Study Tutorial (Linear and Logistic Regression)17分鐘
4 個閱讀材料
Linear Regression Models: Notation, Parameters, Estimation Methods30分鐘
Try It Out: Continuous Data Scatterplot App15分鐘
Importance of Data Visualization: The Datasaurus Dozen10分鐘
Logistic Regression Models: Notation, Parameters, Estimation Methods30分鐘
3 個練習
Linear Regression Quiz20分鐘
Logistic Regression Quiz15分鐘
Week 2 Python Assessment20分鐘
3
完成時間為 4 小時

WEEK 3 - FITTING MODELS TO DEPENDENT DATA

In the third week of this course, we will be building upon the modeling concepts discussed in Week 2. Multilevel and marginal models will be our main topic of discussion, as these models enable researchers to account for dependencies in variables of interest introduced by study designs. We’ll be covering why and when we fit these alternative models, likelihood ratio tests, as well as fixed effects and their interpretations.

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8 個視頻 (總計 121 分鐘), 2 個閱讀材料, 2 個測驗
8 個視頻
Practice with Multilevel Modeling: The Cal Poly App12分鐘
What are Marginal Models and Why Do We Fit Them?13分鐘
Marginal Linear Regression Models19分鐘
Marginal Logistic Regression11分鐘
NHANES Case Study Tutorial (Marginal and Multilevel Regression)10分鐘
2 個閱讀材料
Visualizing Multilevel Models10分鐘
Likelihood Ratio Tests for Fixed Effects and Variance Components10分鐘
2 個練習
Name That Model15分鐘
Week 3 Python Assessment20分鐘
4
完成時間為 3 小時

WEEK 4: Special Topics

In this final week, we introduce special topics that extend the curriculum from previous weeks and courses further. We will cover a broad range of topics such as various types of dependent variables, exploring sampling methods and whether or not to use survey weights when fitting models, and in-depth case studies utilizing Bayesian techniques to derive insights from data. You’ll also have the opportunity to apply Bayesian techniques in Python.

...
6 個視頻 (總計 105 分鐘), 3 個閱讀材料, 1 個測驗
6 個視頻
Bayesian Approaches Case Study: Part II19分鐘
Bayesian Approaches Case Study - Part III23分鐘
Bayesian in Python19分鐘
3 個閱讀材料
Other Types of Dependent Variables20分鐘
Optional: A Visual Introduction to Machine Learning20分鐘
Course Feedback10分鐘
1 個練習
Week 4 Python Assessment20分鐘
4.2
12 個審閱Chevron Right

來自Fitting Statistical Models to Data with Python的熱門評論

創建者 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.

創建者 JXJun 30th 2019

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

講師

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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

關於 密歇根大学

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....

關於 Statistics with Python 專項課程

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

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