Become a data-driven manager. Master the basics of data interpretation.
Suggested by: Coursera (What is Coursera?)
No prior knowledge required
No unnecessary risks
This specialization is designed for professionals who want to develop a skill set in interpreting statistical results. Through four courses + a final project, you will cover theoretical statistics, data visualization, measurement, regression modeling, probability, and uncertainty, preparing you to critically interpret and evaluate quantitative analysis.
Learners will develop expertise in the calculation and interpretation of statistical quantities, such as causal effects and uncertainty measures. Learners will apply their knowledge to evaluate quantitative results and solve statistical problems. For the final project, learners will select and critically evaluate published quantitative research work.
This course introduces students to the concepts of data and statistics. By the end of the course, students should be able to interpret theoretical statistics, causal analyses, and visualizations to formulate meaningful insights.
This course provides a framework for how analysts can create and evaluate quantitative metrics. The course begins with an overview of the different levels of measurement and ways to convert variables.
This course will introduce you to the linear regression model, which is a powerful tool for measuring the relationship between multiple variables. We will discuss how to create and interpret a multivariate model.
This course focuses on how analysts can measure and describe the confidence in their findings. We will discuss how to conduct hypothesis tests using test statistics and confidence levels.
This is the final course in the Data Skills specialization. In this course, you will apply the skills and knowledge you have gained to critically evaluate original quantitative analysis.
