Informações sobre o curso

116,136 visualizações recentes

Resultados de carreira do aprendiz

50%

consegui um benefício significativo de carreira com este curso

50%

recebi um aumento ou promoção
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário

High school algebra, successful completion of Course 1 in this specialization or equivalent background

Aprox. 18 horas para completar
Inglês
Legendas: Inglês, Coreano

O que você vai aprender

  • Determine assumptions needed to calculate confidence intervals for their respective population parameters.

  • Create confidence intervals in Python and interpret the results.

  • Review how inferential procedures are applied and interpreted step by step when analyzing real data.

  • Run hypothesis tests in Python and interpret the results.

Habilidades que você terá

Confidence IntervalPython ProgrammingStatistical InferenceStatistical Hypothesis Testing

Resultados de carreira do aprendiz

50%

consegui um benefício significativo de carreira com este curso

50%

recebi um aumento ou promoção
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Prazos flexíveis
Redefinir os prazos de acordo com sua programação.
Nível intermediário

High school algebra, successful completion of Course 1 in this specialization or equivalent background

Aprox. 18 horas para completar
Inglês
Legendas: Inglês, Coreano

oferecido por

Logotipo de Universidade de Michigan

Universidade de Michigan

Programa - O que você aprenderá com este curso

Classificação do conteúdoThumbs Up91%(1,754 classificações)Info
Semana
1

Semana 1

3 horas para concluir

WEEK 1 - OVERVIEW & INFERENCE PROCEDURES

3 horas para concluir
9 vídeos (Total 67 mín.), 5 leituras, 1 teste
9 videos
Inferential Statistical Analysis with Python Guidelines4min
Introduction to Inference Methods: Oh the Things You Will See!3min
Bag A or Bag B?13min
Introduction to Bayesian4min
This or That? Language and Notation13min
The Python Statistics Landscape2min
Intermediate Python Concepts: Lists vs Numpy Arrays10min
Functions and Lambda Functions, Reading Help Files11min
5 leituras
Course Syllabus5min
Meet the Course Team!10min
About Our Datasets2min
Help Us Learn More About You!10min
This or That Reference10min
1 exercício prático
Python Basics Assessment15min
Semana
2

Semana 2

5 horas para concluir

WEEK 2 - CONFIDENCE INTERVALS

5 horas para concluir
12 vídeos (Total 118 mín.), 3 leituras, 3 testes
12 videos
Understanding Confidence Intervals10min
Demo: Seeing Theory5min
Assumptions for a Single Population Proportion Confidence Interval3min
Conservative Approach & Sample Size Consideration8min
Estimating a Difference in Population Proportions with Confidence6min
Interpretations & Assumptions for Two Population Proportion Intervals4min
Estimating a Population Mean with Confidence14min
Estimating a Mean Difference for Paired Data10min
Estimating a Difference in Population Means with Confidence (for Independent Groups)14min
Introduction to Confidence Intervals in Python12min
Confidence Intervals for Differences between Population Parameters21min
3 leituras
Confidence Intervals: Other Considerations15min
What Affects the Standard Error of an Estimate?10min
Additional Practice: Confidence Intervals1min
3 exercícios práticos
Practice Quiz: All About Confidence Intervals30min
Sample Size & Assumptions
Confidence Intervals Assessment1h
Semana
3

Semana 3

6 horas para concluir

WEEK 3 - HYPOTHESIS TESTING

6 horas para concluir
12 vídeos (Total 138 mín.), 4 leituras, 3 testes
12 videos
Testing a One Population Proportion8min
Setting Up a Test of Difference in Population Proportions7min
Testing a Difference in Population Proportions8min
Interview: P-Values, P-Hacking and More24min
One Mean: Testing about a Population Mean with Confidence17min
Testing a Population Mean Difference13min
Testing for a Difference in Population Means (for Independent Groups)12min
Demo: Name That Scenario2min
Chocolate & Cycling Assignment2min
Introduction to Hypothesis Testing in Python20min
Walk-Through: Hypothesis Testing with NHANES13min
4 leituras
Hypothesis Testing: Other Considerations10min
The Relationship between Confidence Intervals & Hypothesis Testing5min
Chocolate & Cycling Assignment Instructions5min
Additional Practice: Hypothesis Testing1min
2 exercícios práticos
Name That Scenario15min
Hypothesis Testing in Python Assessment1h
Semana
4

Semana 4

4 horas para concluir

WEEK 4 - LEARNER APPLICATION

4 horas para concluir
6 vídeos (Total 77 mín.), 3 leituras, 1 teste
6 videos
Descriptive Inference Examples for Single Variables Using Confidence Intervals12min
Descriptive Inference Examples for Single Variables Using Hypothesis Testing12min
Comparing Means for Two Independent Samples: An Example14min
Comparing Means for Two Paired Samples: An Example12min
Comparing Proportions for Two Independent Samples: An Example13min
3 leituras
Assumptions Consistency5min
Revisiting Examples: Accounting for Complex Samples10min
Course Feedback10min
1 exercício prático
Assessment30min

Avaliações

Principais avaliações do INFERENTIAL STATISTICAL ANALYSIS WITH PYTHON

Visualizar todas as avaliações

Sobre Programa de cursos integrados 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

Perguntas Frequentes – FAQ

  • Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:

    • The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.

    • The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.

  • When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. Your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

  • If you subscribed, you get a 7-day free trial during which you can cancel at no penalty. After that, we don’t give refunds, but you can cancel your subscription at any time. See our full refund policy.

  • Yes, Coursera provides financial aid to learners who cannot afford the fee. Apply for it by clicking on the Financial Aid link beneath the "Enroll" button on the left. You'll be prompted to complete an application and will be notified if you are approved. You'll need to complete this step for each course in the Specialization, including the Capstone Project. Learn more.

Mais dúvidas? Visite o Central de Ajuda ao Aprendiz.