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学生对 University of Michigan 提供的 Fitting Statistical Models to Data with Python 的评价和反馈

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710 个评分

课程概述

In this course, we will expand our exploration of statistical inference techniques by focusing on the science and art of fitting statistical models to data. We will build on the concepts presented in the Statistical Inference course (Course 2) to emphasize the importance of connecting research questions to our data analysis methods. We will also focus on various modeling objectives, including making inference about relationships between variables and generating predictions for future observations. This course will introduce and explore various statistical modeling techniques, including linear regression, logistic regression, generalized linear models, hierarchical and mixed effects (or multilevel) models, and Bayesian inference techniques. All techniques will be illustrated using a variety of real data sets, and the course will emphasize different modeling approaches for different types of data sets, depending on the study design underlying the data (referring back to Course 1, Understanding and Visualizing Data with Python). During these lab-based sessions, learners will work through tutorials focusing on specific case studies to help solidify the week’s statistical concepts, which will include further deep dives into Python libraries including Statsmodels, Pandas, and Seaborn. This course utilizes the Jupyter Notebook environment within Coursera....

热门审阅

BS

Jan 17, 2020

I am very thankful to you sir.. i have learned so much great things through this course.this course is very helpful for my career. i would like to learn more courses from you. thank you so much.

AF

Mar 11, 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.

筛选依据：

51 - Fitting Statistical Models to Data with Python 的 75 个评论（共 142 个）

创建者 Nicky D

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Jan 22, 2020

Excellent course, really enjoyed the section on Bayesian statistics.

创建者 Nipunjeet S G

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May 25, 2019

Very informative and the example

applications are extremely detailed

创建者 Prabakaran C

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Mar 17, 2020

Have given me CLearcut idea about Mixed-effects and Marginal Models

创建者 Ryan C D

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Nov 10, 2022

My 4th specialization in data science, and the best taught so far.

创建者 Erhan K

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Jan 17, 2022

Especially the part on Bayesian Statistics are very informative.

创建者 Gerardo C P

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Sep 26, 2024

El curso despertó mi curiosidad por los modelos multinivel.

创建者 Hrishi P

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Jun 11, 2020

Great practical applications of statistics with Python!

创建者 DIBYA P S

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Jun 21, 2020

good conceptual development , helped lot in learning

创建者 Harish S

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Jan 27, 2019

Content of course was good. Some issue with quiz.

创建者 Appi

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Sep 23, 2019

Very good instructors and very good workload!

创建者 Debabrata A K S

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Feb 19, 2020

Very nice course. Well explained kudos.

创建者 Sumit M

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Mar 30, 2020

Very Very Good For learning Statistics

创建者 JamieLiu

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Sep 8, 2021

Great course ,I learned a lot from it

创建者 SHIVAM A

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Jun 1, 2021

awesome course teaching and materials

创建者 Emory F

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Apr 13, 2020

The classes and mentors are amazing.

创建者 wissam m

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Jan 3, 2022

very advance and helpful course

创建者 Jorge L C T

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May 18, 2023

Nice as an introductory course

创建者 Álvaro M R

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Mar 22, 2021

Amazing course! Really good.

创建者 Jiang X

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Mar 17, 2024

Very useful and practical!

创建者 Yiyi Z

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Aug 17, 2021

This course is very good

创建者 Jose H C

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Sep 2, 2019

It was good - Thanks.!

创建者 Leonadi “ D

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Oct 31, 2025

Simplemente excelente

创建者 João G T B

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Sep 23, 2020

Very good statistics!

创建者 Aniket S

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Apr 18, 2020

Detailed and Precise.

创建者 Edgar L

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May 9, 2023

great course overall