• Online, Self-Paced
Course Description

To master data science, you must learn the techniques around data research. In this course you will discover how to apply essential data research techniques, including JMP measurement, and how to valuate data using descriptive and inferential methods.

Learning Objectives

Data Science 9: Data Research Techniques

  • recall the fundamental concepts of data research that can be applied on data inference
  • identify implementation steps for drawing data hypothesis conclusions
  • define the values, variables, and observations that are associated with data from the perspective of quantitative and classification variables
  • specify the different scales of standard measurements with a critical comparison between the Generic and JMP model
  • identify the key features of non-experimental and experimental research approaches using real-time scenarios
  • compare the differences between the descriptive and inferential statistical analysis
  • illustrate the prominent usages of the different types of inferential tests
  • describe the approaches and the steps involved in the implementation of clinical data research using real-time scenarios
  • describe the approaches and the steps involved in the implementation of sales data research using real-time scenarios
  • specify the key features of experimental and non-experimental research and recall the differences between descriptive and inferential statistical analysis

Framework Connections

The materials within this course focus on the Knowledge Skills and Abilities (KSAs) identified within the Specialty Areas listed below. Click to view Specialty Area details within the interactive National Cybersecurity Workforce Framework.

Feedback

If you would like to provide feedback for this course, please e-mail the NICCS SO at NICCS@hq.dhs.gov.