- visualization
- Measurement Uncertainty
- Probability
- Statistical Hypothesis Testing
- Statistics
- Causal Inference
- Data Visualization (DataViz)
- Empirical Evidence
- Cross-Sectional Analysis
- Basic Descriptive Statistics
- Survey Design
- Statistical Analysis
数据素养 专项课程
Become a Data-driven Leader. Master the Fundamentals of Interpreting Data
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您将获得的技能
关于此 专项课程
应用的学习项目
Learners will develop expertise in calculating and interpreting statistical quantities, such as causal effects and measures of uncertainty. Learners will apply their knowledge to evaluating quantitative results and solving statistical problems. For the capstone project, learners will select and critically evaluate a piece of published, quantitative research.
An interest in learning how to interpret data in an applied manner
An interest in learning how to interpret data in an applied manner
专项课程的运作方式
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实践项目
每个专项课程都包括实践项目。您需要成功完成这个(些)项目才能完成专项课程并获得证书。如果专项课程中包括单独的实践项目课程,则需要在开始之前完成其他所有课程。
获得证书
在结束每门课程并完成实践项目之后,您会获得一个证书,您可以向您的潜在雇主展示该证书并在您的职业社交网络中分享。

此专项课程包含 5 门课程
Data – What It Is, What We Can Do With It
This course introduces students to data and statistics. By the end of the course, students should be able to interpret descriptive statistics, causal analyses and visualizations to draw meaningful insights.
Measurement – Turning Concepts into Data
This course provides a framework for how analysts can create and evaluate quantitative measures. Consider the many tricky concepts that are often of interest to analysts, such as health, educational attainment and trust in government. This course will explore various approaches for quantifying these concepts. The course begins with an overview of the different levels of measurement and ways to transform variables. We’ll then discuss how to construct and build a measurement model. We’ll next examine surveys, as they are one of the most frequently used measurement tools. As part of this discussion, we’ll cover survey sampling, design and evaluation. Lastly, we’ll consider different ways to judge the quality of a measure, such as by its level of reliability or validity. By the end of this course, you should be able to develop and critically assess measures for concepts worth study. After all, a good analysis is built on good measures.
Quantifying Relationships with Regression Models
This course will introduce you to the linear regression model, which is a powerful tool that researchers can use to measure the relationship between multiple variables. We’ll begin by exploring the components of a bivariate regression model, which estimates the relationship between an independent and dependent variable. Building on this foundation, we’ll then discuss how to create and interpret a multivariate model, binary dependent variable model and interactive model. We’ll also consider how different types of variables, such as categorical and dummy variables, can be appropriately incorporated into a model. Overall, we’ll discuss some of the many different ways a regression model can be used for both descriptive and causal inference, as well as the limitations of this analytical tool. By the end of the course, you should be able to interpret and critically evaluate a multivariate regression analysis.
What are the Chances? Probability and Uncertainty in Statistics
This course focuses on how analysts can measure and describe the confidence they have in their findings. The course begins with an overview of the key probability rules and concepts that govern the calculation of uncertainty measures. We’ll then apply these ideas to variables (which are the building blocks of statistics) and their associated probability distributions. The second half of the course will delve into the computation and interpretation of uncertainty. We’ll discuss how to conduct a hypothesis test using both test statistics and confidence intervals. Finally, we’ll consider the role of hypothesis testing in a regression context, including what we can and cannot learn from the statistical significance of a coefficient. By the end of the course, you should be able to discuss statistical findings in probabilistic terms and interpret the uncertainty of a particular estimate.
提供方

约翰霍普金斯大学
The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world.
常见问题
退款政策是如何规定的?
我可以只注册一门课程吗?
有助学金吗?
我可以免费学习课程吗?
此课程是 100% 在线学习吗?是否需要现场参加课程?
完成专项课程需要多长时间?
What background knowledge is necessary?
Do I need to take the courses in a specific order?
完成专项课程后我会获得大学学分吗?
What will I be able to do upon completing the Specialization?
还有其他问题吗?请访问 学生帮助中心。