このコースについて

250,499 最近の表示

受講生の就業成果

33%

コース終了後に新しいキャリアをスタートした

22%

コースが具体的なキャリアアップにつながった
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における5の2コース
柔軟性のある期限
スケジュールに従って期限をリセットします。
初級レベル
約15時間で修了
英語
字幕:英語, 韓国語

習得するスキル

Statistical InferenceStatistical Hypothesis TestingR Programming

受講生の就業成果

33%

コース終了後に新しいキャリアをスタートした

22%

コースが具体的なキャリアアップにつながった
共有できる証明書
修了時に証明書を取得
100%オンライン
自分のスケジュールですぐに学習を始めてください。
次における5の2コース
柔軟性のある期限
スケジュールに従って期限をリセットします。
初級レベル
約15時間で修了
英語
字幕:英語, 韓国語

提供:

デューク大学(Duke University) ロゴ

デューク大学(Duke University)

シラバス - 本コースの学習内容

コンテンツの評価Thumbs Up93%(5,879 件の評価)Info
1

1

20分で修了

About the Specialization and the Course

20分で修了
2 readings
2件の学習用教材
About Statistics with R Specialization10 分
More about Inferential Statistics10 分
3時間で修了

Central Limit Theorem and Confidence Interval

3時間で修了
7件のビデオ (合計65分), 6 readings, 3 quizzes
7件のビデオ
Sampling Variability and CLT20 分
CLT (for the mean) examples10 分
Confidence Interval (for a mean)11 分
Accuracy vs. Precision7 分
Required Sample Size for ME4 分
CI (for the mean) examples5 分
6件の学習用教材
Lesson Learning Objectives10 分
Lesson Learning Objectives10 分
Week 1 Suggested Readings and Practice Exercises10 分
About Lab Choices10 分
Week 1 Lab Instructions (RStudio)10 分
Week 1 Lab Instructions (RStudio Cloud)10 分
3の練習問題
Week 1 Practice Quiz12 分
Week 1 Quiz14 分
Week 1 Lab12 分
2

2

2時間で修了

Inference and Significance

2時間で修了
7件のビデオ (合計59分), 5 readings, 3 quizzes
7件のビデオ
Hypothesis Testing (for a mean)14 分
HT (for the mean) examples9 分
Inference for Other Estimators10 分
Decision Errors8 分
Significance vs. Confidence Level6 分
Statistical vs. Practical Significance7 分
5件の学習用教材
Lesson Learning Objectives10 分
Lesson Learning Objectives10 分
Week 2 Suggested Readings and Practice Exercises10 分
Week 2 Lab Instructions (RStudio)10 分
Week 2 Lab Instructions (RStudio Cloud)10 分
3の練習問題
Week 2 Practice Quiz10 分
Week 2 Quiz16 分
Week 2 Lab12 分
3

3

3時間で修了

Inference for Comparing Means

3時間で修了
11件のビデオ (合計84分), 5 readings, 3 quizzes
11件のビデオ
t-distribution7 分
Inference for a mean9 分
Inference for comparing two independent means8 分
Inference for comparing two paired means9 分
Power11 分
Comparing more than two means6 分
ANOVA9 分
Conditions for ANOVA2 分
Multiple comparisons6 分
Bootstrapping8 分
5件の学習用教材
Lesson Learning Objectives10 分
Lesson Learning Objectives10 分
Week 3 Suggested Readings and Practice Exercises10 分
Week 3 Lab Instructions (RStudio)10 分
Week 3 Lab Instructions (RStudio Cloud)10 分
3の練習問題
Week 3 Practice Quiz16 分
Week 3 Quiz28 分
Week 3 Lab14 分
4

4

4時間で修了

Inference for Proportions

4時間で修了
11件のビデオ (合計118分), 5 readings, 3 quizzes
11件のビデオ
Sampling Variability and CLT for Proportions15 分
Confidence Interval for a Proportion9 分
Hypothesis Test for a Proportion9 分
Estimating the Difference Between Two Proportions17 分
Hypothesis Test for Comparing Two Proportions13 分
Small Sample Proportions10 分
Examples4 分
Comparing Two Small Sample Proportions5 分
Chi-Square GOF Test14 分
The Chi-Square Independence Test11 分
5件の学習用教材
Lesson Learning Objectives10 分
Lesson Learning Objectives10 分
Week 4 Suggested Readings and Practice Exercises10 分
Week 4 Lab Instructions (RStudio)10 分
Week 4 Lab Instructions (RStudio Cloud)10 分
3の練習問題
Week 4 Practice Quiz18 分
Week 4 Quiz24 分
Week 4 Lab26 分

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Statistics with R専門講座について

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

よくある質問

  • 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.

さらに質問がある場合は、受講者向けヘルプセンターにアクセスしてください。