Effective Components of Data Literacy
Understanding what data is, the different types (structured and unstructed), and how it is generated, collected and stored.
Knowing where to find data, whether in internal databases, public repositories or third-party sources.
Skills in collecting data ethically, accurately, and efficiently, including designing surveys, setting up data collection systems, etc.
Ability to clean, preprocess, and wrangle raw data into usable formats for analysis, including dealing with missing values, outliers and inconsistencies.
Skills in using tools like Excel, SQL, Python, or R to analyze data, perform statistical tests, create visualizations, and derive insights.
Communicating data insights effectively though charts, graphs, dashboards and other visual means to make complex information more understandable.
Interpreting data results accurately, understanding correlations, causation, statistical significance, and limitations of the data.
Knowledge of ethical considerations in handling data, including privacy, security, bias, and responsible data use.
Ability to communicate data findings and insights to different stakeholders, translating technical jargon into layman's terms.
A mindset of continous learning and adaptation as data technologies, tools and practices evolve.
These components collectively empower individuals to leverage data effectively for decision-making, problem-solving, innovation and creating data-informed strategies. Below are resources that are available to our Lehigh community.
This page is constantly being updated, bookmark it and check often for new additional resources.