Este curso forma parte de Programa especializado: Statistics with Python

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838 calificaciones

93 %

Brenda Gunderson +2 instructores más

37.675 ya inscrito

Ofrecido Por

Programa especializado: Statistics with PythonUniversidad de Míchigan

Acerca de este Curso

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In this course, we will explore basic principles behind using data for estimation and for assessing theories. We will analyze both categorical data and quantitative data, starting with one population techniques and expanding to handle comparisons of two populations. We will learn how to construct confidence intervals. We will also use sample data to assess whether or not a theory about the value of a parameter is consistent with the data. A major focus will be on interpreting inferential results appropriately.  
At the end of each week, learners will apply what they’ve learned using Python within the course environment. 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.

Fechas límite flexibles

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100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Curso 2 de 3 en

Programa especializado: Statistics with Python

Nivel intermedio

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

Aprox. 19 horas para completar

Inglés (English)

Qué aprenderás

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 obtendrás

Confidence Interval
Python Programming
Statistical Inference
Statistical Hypothesis Testing

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.

Certificado para compartir

Obtén un certificado al finalizar

100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.

Curso 2 de 3 en

Programa especializado: Statistics with Python

Nivel intermedio

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

Aprox. 19 horas para completar

Inglés (English)

Instructores

Calificación del instructor

4,68/5 (131 calificaciones)

Ofrecido por

Universidad de Míchigan

Programa - Qué aprenderás en este curso

Calificación del contenido93%(4,801 calificaciones)

Semana

Semana 1

3 horas para completar

WEEK 1 - OVERVIEW & INFERENCE PROCEDURES

In this first week, we’ll review the course syllabus and discover the various concepts and objectives to be mastered in weeks to come. You’ll be introduced to inference methods and some of the research questions we’ll discuss in the course, as well as an overall framework for making decisions using data, considerations for how you make those decisions, and evaluating errors that you may have made.

3 horas para completar

9 videos (Total 67 minutos), 6 lecturas, 1 cuestionario

9 videos

Welcome to the Course!2m

Inferential Statistical Analysis with Python Guidelines4m

Introduction to Inference Methods: Oh the Things You Will See!3m

Bag A or Bag B?13m

Introduction to Bayesian4m

This or That? Language and Notation13m

The Python Statistics Landscape2m

Intermediate Python Concepts: Lists vs Numpy Arrays10m

Functions and Lambda Functions, Reading Help Files11m

6 lecturas

Course Syllabus5m

Meet the Course Team!10m

About Our Datasets2m

Help Us Learn More About You!10m

Course Syllabus10m

This or That Reference10m

1 ejercicio de práctica

Python Basics Assessment15m

Semana

Semana 2

7 horas para completar

WEEK 2 - CONFIDENCE INTERVALS

In this second week, we will learn about estimating population parameters via confidence intervals. You will be introduced to five different types of population parameters, assumptions needed to calculate a confidence interval for each of these five parameters, and how to calculate confidence intervals. Quizzes will appear throughout the week to test your understanding. In addition, you’ll learn how to create confidence intervals in Python.

7 horas para completar

12 videos (Total 118 minutos), 5 lecturas, 3 cuestionarios

12 videos

Estimating a Population Proportion with Confidence6m

Understanding Confidence Intervals10m

Demo: Seeing Theory5m

Assumptions for a Single Population Proportion Confidence Interval3m

Conservative Approach & Sample Size Consideration8m

Estimating a Difference in Population Proportions with Confidence6m

Interpretations & Assumptions for Two Population Proportion Intervals4m

Estimating a Population Mean with Confidence14m

Estimating a Mean Difference for Paired Data10m

Estimating a Difference in Population Means with Confidence (for Independent Groups)14m

Introduction to Confidence Intervals in Python12m

Confidence Intervals for Differences between Population Parameters21m

5 lecturas

Confidence Intervals: Other Considerations15m

What Affects the Standard Error of an Estimate?10m

Additional Practice: An Introductory Guide to PDFs and CDFs10m

Additional Practice: Confidence Intervals1m

Napping and Non-Napping Toddlers Article for Python Assessment10m

3 ejercicios de práctica

Practice Quiz: All About Confidence Intervals30m

Sample Size & Assumptions30m

Confidence Intervals Assessment1h

Semana

Semana 3

7 horas para completar

WEEK 3 - HYPOTHESIS TESTING

In week three, we’ll learn how to test various hypotheses - using the five different analysis methods covered in the previous week. We’ll discuss the importance of various factors and assumptions with hypothesis testing and learn to interpret our results. We will also review how to distinguish which procedure is appropriate for the research question at hand. Quizzes and a peer assessment will appear throughout the week to test your understanding.

7 horas para completar

12 videos (Total 138 minutos), 4 lecturas, 3 cuestionarios

12 videos

Setting Up a Test for a Population Proportion5m

Testing a One Population Proportion8m

Setting Up a Test of Difference in Population Proportions7m

Testing a Difference in Population Proportions8m

Interview: P-Values, P-Hacking and More24m

One Mean: Testing about a Population Mean with Confidence17m

Testing a Population Mean Difference13m

Testing for a Difference in Population Means (for Independent Groups)12m

Demo: Name That Scenario2m

Chocolate & Cycling Assignment2m

Introduction to Hypothesis Testing in Python20m

Walk-Through: Hypothesis Testing with NHANES13m

4 lecturas

Hypothesis Testing: Other Considerations10m

The Relationship between Confidence Intervals & Hypothesis Testing5m

Chocolate & Cycling Assignment Instructions5m

Additional Practice: Hypothesis Testing1m

2 ejercicios de práctica

Name That Scenario15m

Hypothesis Testing in Python Assessment1h

Semana

Semana 4

2 horas para completar

WEEK 4 - LEARNER APPLICATION

In the final week of this course, we will walk through several examples and case studies that illustrate applications of the inferential procedures discussed in prior weeks. Learners will see examples of well-formulated research questions related to the study designs and data sets that we have discussed thus far, and via both confidence interval estimation and formal hypothesis testing, we will formulate inferential responses to those questions.

2 horas para completar

6 videos (Total 77 minutos), 4 lecturas, 1 cuestionario

6 videos

The Importance of Good Research Questions for Sound Inference10m

Descriptive Inference Examples for Single Variables Using Confidence Intervals12m

Descriptive Inference Examples for Single Variables Using Hypothesis Testing12m

Comparing Means for Two Independent Samples: An Example14m

Comparing Means for Two Paired Samples: An Example12m

Comparing Proportions for Two Independent Samples: An Example13m

4 lecturas

Assumptions Consistency5m

Revisiting Examples: Accounting for Complex Samples10m

Course Feedback10m

Keep Learning with Michigan Online10m

1 ejercicio de práctica

Assessment30m

Reseñas

4.6

153 reseña

5 stars
74,10 %
4 stars
17,30 %
3 stars
5,60 %
2 stars
1,55 %
1 star
1,43 %

Principales reseñas sobre INFERENTIAL STATISTICAL ANALYSIS WITH PYTHON

por XJ21 de jun. de 2019

A very in-depth learning material for inferential statistics. Very good explanation of p-value which clarifies some of the prevailing misunderstandings.

por ST31 de may. de 2021

Do you want to have an in-depth understanding of statistics in data science? Take the full specialization and you won't regret it. Fantastic course

por AB5 de nov. de 2020

Great course with practical experience with Python. There are many courses that teach statistics with R but this is the first one to do so in Python.

por RZ1 de abr. de 2020

This is a very great course. Statistics by itself is a very powerful tool for solving real world problems. Combine it with the knowledge of Python, there no limit to what you can achieve.

Ver todas las reseñas

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.

Preguntas Frecuentes

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El acceso a las clases y las asignaciones depende del tipo de inscripción que tengas. Si tomas un curso en modo de oyente, verás la mayoría de los materiales del curso en forma gratuita. Para acceder a asignaciones calificadas y obtener un certificado, deberás comprar la experiencia de Certificado, ya sea durante o después de participar como oyente. Si no ves la opción de oyente:
es posible que el curso no ofrezca la opción de participar como oyente. En cambio, puedes intentar con una Prueba gratis o postularte para recibir ayuda económica.
Es posible que el curso ofrezca la opción 'Curso completo, sin certificado'. Esta opción te permite ver todos los materiales del curso, enviar las evaluaciones requeridas y obtener una calificación final. También significa que no podrás comprar una experiencia de Certificado.
¿Qué recibiré si me suscribo a este Programa especializado?
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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Sí. En ciertos programas de aprendizaje, puedes postularte para recibir ayuda económica o una beca en caso de no poder costear los gastos de la tarifa de inscripción. Si hay ayuda económica o becas disponibles para tu selección de programa de aprendizaje, verás un enlace para postularte en la página de descripción.

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Inferential Statistical Analysis with Python

Acerca de este Curso

Qué aprenderás

Habilidades que obtendrás

Instructores

Brenda Gunderson

Brady T. West

Kerby Shedden

Ofrecido por

Universidad de Míchigan

Programa - Qué aprenderás en este curso

WEEK 1 - OVERVIEW & INFERENCE PROCEDURES

WEEK 2 - CONFIDENCE INTERVALS

WEEK 3 - HYPOTHESIS TESTING

WEEK 4 - LEARNER APPLICATION

Reseñas

Principales reseñas sobre INFERENTIAL STATISTICAL ANALYSIS WITH PYTHON

Acerca de Programa especializado: Statistics with Python

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Inferential Statistical Analysis with Python

Acerca de este Curso

Qué aprenderás

Habilidades que obtendrás

Instructores

Brenda Gunderson

Brady T. West

Kerby Shedden

Ofrecido por

Universidad de Míchigan

Programa - Qué aprenderás en este curso

WEEK 1 - OVERVIEW & INFERENCE PROCEDURES

WEEK 2 - CONFIDENCE INTERVALS

WEEK 3 - HYPOTHESIS TESTING

WEEK 4 - LEARNER APPLICATION

Reseñas

Principales reseñas sobre INFERENTIAL STATISTICAL ANALYSIS WITH PYTHON

Acerca de Programa especializado: Statistics with Python

Preguntas Frecuentes

Coursera Footer

Comienza o impulsa tu carrera profesional

Cursos y certificaciones populares

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