課程信息

250,171 次近期查看

學生職業成果

33%

完成這些課程後已開始新的職業生涯

22%

通過此課程獲得實實在在的工作福利
可分享的證書
完成後獲得證書
100% 在線
立即開始,按照自己的計劃學習。
第 2 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15 小時
英語(English)
字幕:英語(English), 韓語

您將獲得的技能

Statistical InferenceStatistical Hypothesis TestingR Programming

學生職業成果

33%

完成這些課程後已開始新的職業生涯

22%

通過此課程獲得實實在在的工作福利
可分享的證書
完成後獲得證書
100% 在線
立即開始,按照自己的計劃學習。
第 2 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15 小時
英語(English)
字幕:英語(English), 韓語

提供方

杜克大学 徽標

杜克大学

教學大綱 - 您將從這門課程中學到什麼

內容評分Thumbs Up93%(5,845 個評分)Info
1

1

完成時間為 20 分鐘

About the Specialization and the Course

完成時間為 20 分鐘
2 個閱讀材料
2 個閱讀材料
About Statistics with R Specialization10分鐘
More about Inferential Statistics10分鐘
完成時間為 3 小時

Central Limit Theorem and Confidence Interval

完成時間為 3 小時
7 個視頻 (總計 65 分鐘), 6 個閱讀材料, 3 個測驗
7 個視頻
Sampling Variability and CLT20分鐘
CLT (for the mean) examples10分鐘
Confidence Interval (for a mean)11分鐘
Accuracy vs. Precision7分鐘
Required Sample Size for ME4分鐘
CI (for the mean) examples5分鐘
6 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Week 1 Suggested Readings and Practice Exercises10分鐘
About Lab Choices10分鐘
Week 1 Lab Instructions (RStudio)10分鐘
Week 1 Lab Instructions (RStudio Cloud)10分鐘
3 個練習
Week 1 Practice Quiz12分鐘
Week 1 Quiz14分鐘
Week 1 Lab12分鐘
2

2

完成時間為 2 小時

Inference and Significance

完成時間為 2 小時
7 個視頻 (總計 59 分鐘), 5 個閱讀材料, 3 個測驗
7 個視頻
Hypothesis Testing (for a mean)14分鐘
HT (for the mean) examples9分鐘
Inference for Other Estimators10分鐘
Decision Errors8分鐘
Significance vs. Confidence Level6分鐘
Statistical vs. Practical Significance7分鐘
5 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Week 2 Suggested Readings and Practice Exercises10分鐘
Week 2 Lab Instructions (RStudio)10分鐘
Week 2 Lab Instructions (RStudio Cloud)10分鐘
3 個練習
Week 2 Practice Quiz10分鐘
Week 2 Quiz16分鐘
Week 2 Lab12分鐘
3

3

完成時間為 3 小時

Inference for Comparing Means

完成時間為 3 小時
11 個視頻 (總計 84 分鐘), 5 個閱讀材料, 3 個測驗
11 個視頻
t-distribution7分鐘
Inference for a mean9分鐘
Inference for comparing two independent means8分鐘
Inference for comparing two paired means9分鐘
Power11分鐘
Comparing more than two means6分鐘
ANOVA9分鐘
Conditions for ANOVA2分鐘
Multiple comparisons6分鐘
Bootstrapping8分鐘
5 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Week 3 Suggested Readings and Practice Exercises10分鐘
Week 3 Lab Instructions (RStudio)10分鐘
Week 3 Lab Instructions (RStudio Cloud)10分鐘
3 個練習
Week 3 Practice Quiz16分鐘
Week 3 Quiz28分鐘
Week 3 Lab14分鐘
4

4

完成時間為 4 小時

Inference for Proportions

完成時間為 4 小時
11 個視頻 (總計 118 分鐘), 5 個閱讀材料, 3 個測驗
11 個視頻
Sampling Variability and CLT for Proportions15分鐘
Confidence Interval for a Proportion9分鐘
Hypothesis Test for a Proportion9分鐘
Estimating the Difference Between Two Proportions17分鐘
Hypothesis Test for Comparing Two Proportions13分鐘
Small Sample Proportions10分鐘
Examples4分鐘
Comparing Two Small Sample Proportions5分鐘
Chi-Square GOF Test14分鐘
The Chi-Square Independence Test11分鐘
5 個閱讀材料
Lesson Learning Objectives10分鐘
Lesson Learning Objectives10分鐘
Week 4 Suggested Readings and Practice Exercises10分鐘
Week 4 Lab Instructions (RStudio)10分鐘
Week 4 Lab Instructions (RStudio Cloud)10分鐘
3 個練習
Week 4 Practice Quiz18分鐘
Week 4 Quiz24分鐘
Week 4 Lab26分鐘

審閱

來自推论统计的熱門評論

查看所有評論

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

常見問題

  • 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.

  • If you want to complete the course and earn a Course Certificate by submitting assignments for a grade, you can upgrade your experience by subscribing to the course for $49/month. You can also apply for financial aid if you can't afford the course fee.

    When you enroll in a course that is part of a Specialization (which this course is), you will automatically be enrolled in the entire Specialization. You can unenroll from the Specialization if you’re not interested in the other courses or cancel your subscription once you complete the single course.

  • To enroll in an individual course, search for the course title in the catalog.

    To get full access to a course, including the option to earn grades and a Course Certificate, you'll need to subscribe. New subscribers will start with a full access subscription, which includes full access to every course in the Coursera catalog. Existing Specialization subscribers will be given the option to update to a full access subscription when enrolling in a new Specialization or course.

    When you enroll in a course that is part of a Specialization, you will automatically be enrolled in the entire Specialization. You can unenroll from the Specialization if you’re not interested in the other courses.

  • 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.

還有其他問題嗎?請訪問 學生幫助中心