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Специализация

Курс 1 из 1 в программе

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Промежуточный уровень

Промежуточный уровень

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

Часов на завершение

Прибл. 17 часа на выполнение

Предполагаемая нагрузка: 4 weeks of study, 4-6 hours/week...
Доступные языки

Английский

Субтитры: Английский

Чему вы научитесь

  • Check

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

  • Check

    Create confidence intervals in Python and interpret the results.

  • Check

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

  • Check

    Run hypothesis tests in Python and interpret the results.

Приобретаемые навыки

Confidence IntervalPython ProgrammingStatistical InferenceStatistical Hypothesis Testing
Специализация

Курс 1 из 1 в программе

100% онлайн

100% онлайн

Начните сейчас и учитесь по собственному графику.
Гибкие сроки

Гибкие сроки

Назначьте сроки сдачи в соответствии со своим графиком.
Промежуточный уровень

Промежуточный уровень

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

Часов на завершение

Прибл. 17 часа на выполнение

Предполагаемая нагрузка: 4 weeks of study, 4-6 hours/week...
Доступные языки

Английский

Субтитры: Английский

Программа курса: что вы изучите

Неделя
1
Часов на завершение
3 ч. на завершение

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. On the Python side, we’ll review some high level concepts from the first course in this series, Python’s statistics landscape, and walk through intermediate level Python concepts. All of the course information on grading, prerequisites, and expectations are on the course syllabus and you can find more information on our Course Resources page....
Reading
8 видео ((всего 62 мин.)), 5 материалов для самостоятельного изучения, 1 тест
Video8 видео
Introduction to Inference Methods: Oh the Things You Will See!3мин
Bag A or Bag B?13мин
Introduction to Bayesian4мин
This or That? Language and Notation13мин
The Python Statistics Landscape2мин
Intermediate Python Concepts: Lists vs Numpy Arrays10мин
Functions and Lambda Functions, Reading Help Files11мин
Reading5 материала для самостоятельного изучения
Course Syllabus5мин
Meet the Course Team!10мин
Help Us Learn More About You!10мин
About Our Datasets2мин
This or That Reference10мин
Quiz1 практическое упражнение
Python Basics Assessment15мин
Неделя
2
Часов на завершение
6 ч. на завершение

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 and a peer assessment will appear throughout the week to test your understanding. In addition, you’ll learn how to create confidence intervals in Python....
Reading
13 видео ((всего 121 мин.)), 4 материалов для самостоятельного изучения, 4 тестов
Video13 видео
Understanding Confidence Intervals10мин
Demo: Seeing Theory5мин
Assumptions for a Single Population Proportion Confidence Interval3мин
Conservative Approach & Sample Size Consideration8мин
Estimating a Difference in Population Proportions with Confidence6мин
Interpretations & Assumptions for Two Population Proportion Intervals4мин
Estimating a Population Mean with Confidence14мин
Estimating a Mean Difference for Paired Data10мин
Estimating a Difference in Population Means with Confidence (for Independent Groups)14мин
Chocolate & Cycling Assignment2мин
Introduction to Confidence Intervals in Python12мин
Confidence Intervals for Differences between Population Parameters21мин
Reading4 материала для самостоятельного изучения
Confidence Intervals: Other Considerations15мин
What Affects the Standard Error of an Estimate?10мин
Chocolate & Cycling Assignment Instructions5мин
Additional Practice: Confidence Intervals1мин
Quiz3 практического упражнения
Practice Quiz: All About Confidence Intervals14мин
Sample Size & Assumptions
Confidence Intervals Assessment
Неделя
3
Часов на завершение
5 ч. на завершение

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....
Reading
11 видео ((всего 136 мин.)), 3 материалов для самостоятельного изучения, 2 тестов
Video11 видео
Testing a One Population Proportion8мин
Setting Up a Test of Difference in Population Proportions7мин
Testing a Difference in Population Proportions8мин
Interview: P-Values, P-Hacking and More24мин
One Mean: Testing about a Population Mean with Confidence17мин
Testing a Population Mean Difference13мин
Testing for a Difference in Population Means (for Independent Groups)12мин
Demo: Name That Scenario2мин
Introduction to Hypothesis Testing in Python20мин
Walk-Through: Hypothesis Testing with NHANES13мин
Reading3 материала для самостоятельного изучения
Hypothesis Testing: Oher Considerations10мин
The Relationship between Confidence Intervals & Hypothesis Testing5мин
Additional Practice: Hypothesis Testing1мин
Quiz2 практического упражнения
Name That Scenario15мин
Hypothesis Testing in Python Assessment
Неделя
4
Часов на завершение
4 ч. на завершение

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....
Reading
6 видео ((всего 77 мин.)), 3 материалов для самостоятельного изучения, 1 тест
Video6 видео
Descriptive Inference Examples for Single Variables Using Hypothesis Testing12мин
Descriptive Inference Examples for Single Variables Using Confidence Intervals12мин
Comparing Means for Two Independent Samples: An Example14мин
Comparing Means for Two Paired Samples: An Example12мин
Comparing Proportions for Two Independent Samples: An Example13мин
Reading3 материала для самостоятельного изучения
Assumptions Consistency5мин
Revisiting Examples: Accounting for Complex Samples10мин
Course Feedback10мин
Quiz1 практическое упражнение
Assessment10мин

Преподавателя

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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

О University of Michigan

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....

О специализации ''Statistics with Python'

This specialization is designed to teach learners beginning and intermediate concepts of statistical analysis, and use of the Python programming language to conduct data analyses. Learners will learn where data come from, what types of data can be collected, how to effectively summarize and visualize data, how to utilize data for estimation and assessing theories, proper interpretations of inferential results, and how to apply more advanced statistical modeling procedures....
Statistics with Python

Часто задаваемые вопросы

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • 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.

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