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第 1 門課程(共 5 門)

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初級

完成時間大約為22 小時

建議:5 weeks of study, 5-7 hours/week...

英語(English)

字幕:英語(English), 韓語

您將獲得的技能

StatisticsR ProgrammingRstudioExploratory Data Analysis

100% 在線

立即開始,按照自己的計劃學習。

第 1 門課程(共 5 門)

可靈活調整截止日期

根據您的日程表重置截止日期。

初級

完成時間大約為22 小時

建議:5 weeks of study, 5-7 hours/week...

英語(English)

字幕:英語(English), 韓語

教學大綱 - 您將從這門課程中學到什麼

1
完成時間為 12 分鐘

About Introduction to Probability and Data

1 個視頻 (總計 2 分鐘), 1 個閱讀材料
1 個視頻
1 個閱讀材料
More about Introduction to Probability and Data10分鐘
完成時間為 1 小時

Introduction to Data

6 個視頻 (總計 28 分鐘), 2 個閱讀材料, 2 個測驗
6 個視頻
Data Basics5分鐘
Observational Studies & Experiments4分鐘
Sampling and sources of bias8分鐘
Experimental Design2分鐘
(Spotlight) Random Sample Assignment3分鐘
2 個閱讀材料
Lesson Learning Objectives10分鐘
Suggested Readings and Practice10分鐘
2 個練習
Week 1 Practice Quiz10分鐘
Week 1 Quiz14分鐘
完成時間為 1 小時

Introduction to Data Project

2 個閱讀材料, 1 個測驗
2 個閱讀材料
About Lab Choices (Read Before Selection)10分鐘
Week 1 Lab Instructions (RStudio)10分鐘
1 個練習
Week 1 Lab: Introduction to R and RStudio16分鐘
2
完成時間為 2 小時

Exploratory Data Analysis and Introduction to Inference

7 個視頻 (總計 46 分鐘), 3 個閱讀材料, 2 個測驗
7 個視頻
Measures of Center4分鐘
Measures of Spread6分鐘
Robust Statistics1分鐘
Transforming Data3分鐘
Exploring Categorical Variables8分鐘
Introduction to Inference12分鐘
3 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Suggested Readings and Practice10分鐘
2 個練習
Week 2 Practice Quiz10分鐘
Week 2 Quiz12分鐘
完成時間為 1 小時

Exploratory Data Analysis and Introduction to Inference Project

2 個閱讀材料, 1 個測驗
2 個閱讀材料
Week 2 Lab Instructions (RStudio)10分鐘
Week 2 Lab Instructions (RStudio Cloud)10分鐘
1 個練習
Week 2 Lab: Introduction to Data20分鐘
3
完成時間為 2 小時

Introduction to Probability

9 個視頻 (總計 82 分鐘), 3 個閱讀材料, 2 個測驗
9 個視頻
Disjoint Events + General Addition Rule9分鐘
Independence9分鐘
Probability Examples9分鐘
(Spotlight) Disjoint vs. Independent2分鐘
Conditional Probability12分鐘
Probability Trees10分鐘
Bayesian Inference14分鐘
Examples of Bayesian Inference7分鐘
3 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Suggested Readings and Practice10分鐘
2 個練習
Week 3 Practice Quiz6分鐘
Week 3 Quiz10分鐘
完成時間為 1 小時

Introduction to Probability Project

2 個閱讀材料, 1 個測驗
2 個閱讀材料
Week 3 Lab Instructions (RStudio)10分鐘
Week 3 Lab Instructions (RStudio Cloud)10分鐘
1 個練習
Week 3 Lab: Probability10分鐘
4
完成時間為 2 小時

Probability Distributions

6 個視頻 (總計 67 分鐘), 4 個閱讀材料, 2 個測驗
6 個視頻
Evaluating the Normal Distribution2分鐘
Working with the Normal Distribution5分鐘
Binomial Distribution17分鐘
Normal Approximation to Binomial14分鐘
Working with the Binomial Distribution9分鐘
4 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Suggested Readings and Practice10分鐘
Data Analysis Project Example10分鐘
2 個練習
Week 4 Practice Quiz14分鐘
Week 4 Quiz14分鐘
4.7
762 條評論Chevron Right

33%

完成這些課程後已開始新的職業生涯

30%

通過此課程獲得實實在在的工作福利

11%

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來自Introduction to Probability and Data的熱門評論

創建者 AAJan 24th 2018

This course literally taught me a lot, the concepts were beautifully explained but the way it was delivered and overall exercises and the difficulty of problems made it more challenging and enjoying.

創建者 BBSep 4th 2019

Very clearly explained and the pace is awesome! I really enjoy each deadline and l can already see how it is impacting my day to day work and life. I ook forward to completing the course! Thank you.

講師

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Mine Çetinkaya-Rundel

Associate Professor of the Practice
Department of Statistical Science

關於 杜克大学

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....

關於 Statistics with R 專項課程

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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  • No. Completion of a Coursera course does not earn you academic credit from Duke; therefore, Duke is not able to provide you with a university transcript. However, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile.

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