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Специализация

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Прибл. 25 часа на выполнение

Предполагаемая нагрузка: 5 weeks of study, 5-7 hours/week...
Доступные языки

Английский

Субтитры: Английский

Приобретаемые навыки

Statistical InferenceStatistical Hypothesis TestingR Programming
Специализация

Курс 2 из 5 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.
Начальный уровень

Начальный уровень

Часов на завершение

Прибл. 25 часа на выполнение

Предполагаемая нагрузка: 5 weeks of study, 5-7 hours/week...
Доступные языки

Английский

Субтитры: Английский

Программа курса: что вы изучите

Неделя
1
Часов на завершение
20 минуты на завершение

About the Specialization and the Course

This short module introduces basics about Coursera specializations and courses in general, this specialization: Statistics with R, and this course: Inferential Statistics. Please take several minutes to browse them through. Thanks for joining us in this course!...
Reading
2 материалов для самостоятельного изучения
Reading2 материала для самостоятельного изучения
About Statistics with R Specialization10мин
More about Inferential Statistics10мин
Часов на завершение
2 ч. на завершение

Central Limit Theorem and Confidence Interval

Welcome to Inferential Statistics! In this course we will discuss Foundations for Inference. Check out the learning objectives, start watching the videos, and finally work on the quiz and the labs of this week. In addition to videos that introduce new concepts, you will also see a few videos that walk you through application examples related to the week's topics. In the first week we will introduce Central Limit Theorem (CLT) and confidence interval....
Reading
7 видео ((всего 65 мин.)), 4 материалов для самостоятельного изучения, 3 тестов
Video7 видео
Sampling Variability and CLT20мин
CLT (for the mean) examples10мин
Confidence Interval (for a mean)11мин
Accuracy vs. Precision7мин
Required Sample Size for ME4мин
CI (for the mean) examples5мин
Reading4 материала для самостоятельного изучения
Lesson Learning Objectives10мин
Lesson Learning Objectives10мин
Week 1 Suggested Readings and Practice Exercises10мин
Week 1 Lab Instructions10мин
Quiz3 практического упражнения
Week 1 Practice Quiz12мин
Week 1 Quiz14мин
Week 1 Lab12мин
Неделя
2
Часов на завершение
2 ч. на завершение

Inference and Significance

Welcome to Week Two! This week we will discuss formal hypothesis testing and relate testing procedures back to estimation via confidence intervals. These topics will be introduced within the context of working with a population mean, however we will also give you a brief peek at what's to come in the next two weeks by discussing how the methods we're learning can be extended to other estimators. We will also discuss crucial considerations like decision errors and statistical vs. practical significance. The labs for this week will illustrate concepts of sampling distributions and confidence levels....
Reading
7 видео ((всего 59 мин.)), 4 материалов для самостоятельного изучения, 3 тестов
Video7 видео
Hypothesis Testing (for a mean)14мин
HT (for the mean) examples9мин
Inference for Other Estimators10мин
Decision Errors8мин
Significance vs. Confidence Level6мин
Statistical vs. Practical Significance7мин
Reading4 материала для самостоятельного изучения
Lesson Learning Objectives10мин
Lesson Learning Objectives10мин
Week 2 Suggested Readings and Practice Exercises10мин
Week 2 Lab Instructions10мин
Quiz3 практического упражнения
Week 2 Practice Quiz10мин
Week 2 Quiz16мин
Week 2 Lab12мин
Неделя
3
Часов на завершение
3 ч. на завершение

Inference for Comparing Means

Welcome to Week Three of the course! This week we will introduce the t-distribution and comparing means as well as a simulation based method for creating a confidence interval: bootstrapping. If you have questions or discussions, please use this week's forum to ask/discuss with peers....
Reading
11 видео ((всего 84 мин.)), 4 материалов для самостоятельного изучения, 3 тестов
Video11 видео
t-distribution7мин
Inference for a mean9мин
Inference for comparing two independent means8мин
Inference for comparing two paired means9мин
Power11мин
Comparing more than two means6мин
ANOVA9мин
Conditions for ANOVA2мин
Multiple comparisons6мин
Bootstrapping8мин
Reading4 материала для самостоятельного изучения
Lesson Learning Objectives10мин
Lesson Learning Objectives10мин
Week 3 Suggested Readings and Practice Exercises10мин
Week 3 Lab Instructions10мин
Quiz3 практического упражнения
Week 3 Practice Quiz16мин
Week 3 Quiz28мин
Week 3 Lab14мин
Неделя
4
Часов на завершение
4 ч. на завершение

Inference for Proportions

Welcome to Week Four of our course! In this unit, we’ll discuss inference for categorical data. We use methods introduced this week to answer questions like “What proportion of the American public approves of the job of the Supreme Court is doing?”....
Reading
11 видео ((всего 118 мин.)), 4 материалов для самостоятельного изучения, 3 тестов
Video11 видео
Sampling Variability and CLT for Proportions15мин
Confidence Interval for a Proportion9мин
Hypothesis Test for a Proportion9мин
Estimating the Difference Between Two Proportions17мин
Hypothesis Test for Comparing Two Proportions13мин
Small Sample Proportions10мин
Examples4мин
Comparing Two Small Sample Proportions5мин
Chi-Square GOF Test14мин
The Chi-Square Independence Test11мин
Reading4 материала для самостоятельного изучения
Lesson Learning Objectives10мин
Lesson Learning Objectives10мин
Week 4 Suggested Readings and Practice Exercises10мин
Week 4 Lab Instructions10мин
Quiz3 практического упражнения
Week 4 Practice Quiz18мин
Week 4 Quiz24мин
Week 4 Lab26мин
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автор: ZCAug 24th 2017

This course by Professor Çetinkaya-Rundel is awesome because it is taught in a very clear and vivid way. Lab section and forum are so dope that I love them so much! Definitely strong recommendation!!!

автор: MNMar 1st 2017

Great course. If you put in a little effort, you will come out with a lot of new knowledge. I recommend using the book after you have seen the movies. It gives a deeper picture of how it works. Great!

Преподаватель

Avatar

Mine Çetinkaya-Rundel

Associate Professor of the Practice
Department of Statistical Science

О Duke University

Duke University has about 13,000 undergraduate and graduate students and a world-class faculty helping to expand the frontiers of knowledge. The university has a strong commitment to applying knowledge in service to society, both near its North Carolina campus and around the world....

О специализации ''Statistics with R'

In this Specialization, you will learn to analyze and visualize data in R and create reproducible data analysis reports, demonstrate a conceptual understanding of the unified nature of statistical inference, perform frequentist and Bayesian statistical inference and modeling to understand natural phenomena and make data-based decisions, communicate statistical results correctly, effectively, and in context without relying on statistical jargon, critique data-based claims and evaluated data-based decisions, and wrangle and visualize data with R packages for data analysis. You will produce a portfolio of data analysis projects from the Specialization that demonstrates mastery of statistical data analysis from exploratory analysis to inference to modeling, suitable for applying for statistical analysis or data scientist positions....
Statistics with R

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