- Data Science
- Process Engineering
- Data Analysis
- Quality Improvement
- Rstudio
- analyzing data
- describing data
- using R
- graphing data
- Make decisions about process improvement
- Analyzing a process for stability
- Analyzing a process for capability
Data Science Methods for Quality Improvement専門講座
データサイエンスでのキャリアをスタート. Master strategies in data science methods for quality improvement.
学習内容
Manage, describe, and analyze data using applied statistics
Apply continuous and/or discrete data methods for process analysis, improvement, and ongoing management in a business or workplace
Analyze measurement systems to ensure their stability and capability
Calculate descriptive statistics and create graphical representations using R software
習得するスキル
この専門講座について
応用学習プロジェクト
Learners develop an understanding of how to manage, describe, and analyze continuous and discrete data using examples from business and industry. They explore how to assess processes for sources of variation through time as well as determine process capability with respect to customer requirements. Learners gain familiarity with the analysis procedures to assess measurement systems for continuous and discrete data in order to make decisions regarding the capability and acceptability of the measurement system. Assignments require learners to perform analyses for various data types and scenarios, interpret results, and make appropriate decisions.
Familiarity with RStudio and applied statistics is recommended.
Familiarity with RStudio and applied statistics is recommended.
専門講座の仕組み
コースを受講しましょう。
Courseraの専門講座は、一連のコース群であり、技術を身に付ける手助けとなります。開始するには、専門講座に直接登録するか、コースを確認して受講したいコースを選択してください。専門講座の一部であるコースにサブスクライブすると、自動的にすべての専門講座にサブスクライブされます。1つのコースを修了するだけでも結構です。いつでも、学習を一時停止したり、サブスクリプションを終了することができます。コースの登録状況や進捗を追跡するには、受講生のダッシュボードにアクセスしてください。
実践型プロジェクト
すべての専門講座には、実践型プロジェクトが含まれています。専門講座を完了して修了証を獲得するには、成功裏にプロジェクトを終了させる必要があります。専門講座に実践型プロジェクトに関する別のコースが含まれている場合、専門講座を開始するには、それら他のコースをそれぞれ終了させる必要があります。
修了証を取得
すべてのコースを終了し、実践型プロジェクトを完了すると、修了証を獲得します。この修了証は、今後採用企業やあなたの職業ネットワークと共有できます。

この専門講座には3コースあります。
Managing, Describing, and Analyzing Data
In this course, you will learn the basics of understanding the data you have and why correctly classifying data is the first step to making correct decisions. You will describe data both graphically and numerically using descriptive statistics and R software. You will learn four probability distributions commonly used in the analysis of data. You will analyze data sets using the appropriate probability distribution. Finally, you will learn the basics of sampling error, sampling distributions, and errors in decision-making.
Stability and Capability in Quality Improvement
In this course, you will learn to analyze data in terms of process stability and statistical control and why having a stable process is imperative prior to perform statistical hypothesis testing. You will create statistical process control charts for both continuous and discrete data using R software. You will analyze data sets for statistical control using control rules based on probability. Additionally, you will learn how to assess a process with respect to how capable it is of meeting specifications, either internal or external, and make decisions about process improvement.
Measurement Systems Analysis
In this course, you will learn to analyze measurement systems for process stability and capability and why having a stable measurement process is imperative prior to performing any statistical analysis. You will analyze continuous measurement systems and statistically characterize both accuracy and precision using R software. You will perform measurement systems analysis for potential, short-term and long-term statistical control and capability. Additionally, you will learn how to assess a discrete measurement and perform analyses for internal consistency, concordance between assessors, and concordance with a standard. Finally, you will learn how to make decisions on measurement systems process improvement.
提供:

コロラド大学ボルダー校(University of Colorado Boulder)
CU-Boulder is a dynamic community of scholars and learners on one of the most spectacular college campuses in the country. As one of 34 U.S. public institutions in the prestigious Association of American Universities (AAU), we have a proud tradition of academic excellence, with five Nobel laureates and more than 50 members of prestigious academic academies.
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よくある質問
返金ポリシーについて教えてください。
1つのコースだけに登録することは可能ですか?
学資援助はありますか?
無料でコースを受講できますか?
このコースは100%オンラインで提供されますか?実際に出席する必要のあるクラスはありますか?
専門講座を修了することで大学の単位は付与されますか?
さらに質問がある場合は、受講者ヘルプセンターにアクセスしてください。