What are the best ways to improve your statistical literacy at work?

1 Identify your goals

Before you dive into learning statistics, you need to have a clear idea of why you want to improve your statistical literacy and what you hope to achieve. Do you want to use data to support your arguments, proposals, or projects? Do you want to understand the trends and patterns in your industry or market? Do you want to evaluate the quality and reliability of data sources and reports? Do you want to learn new tools or methods to analyze data? By identifying your specific goals, you can focus your learning on the topics and skills that are most relevant and useful for your work.

2 Learn the basics

You don't need to master advanced statistics to improve your statistical literacy, but you do need to know some fundamental concepts and terms. These include data types, variables, distributions, measures of central tendency and variability, sampling, hypothesis testing, confidence intervals, and correlation and causation. These concepts will help you understand how data is collected, organized, summarized, and interpreted, and how to avoid common errors and biases. You can learn the basics from online resources, such as Khan Academy, Coursera, or Stat Trek, or from books, such as Naked Statistics by Charles Wheelan or Statistics in a Nutshell by Sarah Boslaugh.

3 Practice with real data

One of the best ways to improve your statistical literacy is to practice with real data that is relevant and interesting for you. You can find data sets from various sources, such as government websites, research organizations, or online platforms, such as Kaggle, DataCamp, or Dataquest. You can also use your own data from your work or personal projects. The key is to ask questions, explore the data, and look for patterns, trends, outliers, and relationships. You can use tools, such as Excel, Google Sheets, R, or Python, to perform calculations, create charts, and run analyses. You can also compare your results with others and learn from their feedback and insights.

4 Read and critique data stories

Another way to improve your statistical literacy is to read and critique data stories from various sources, such as newspapers, magazines, blogs, podcasts, or videos. Data stories are narratives that use data to inform, persuade, or entertain an audience. They can be about any topic, such as politics, health, sports, or business. By reading and critiquing data stories, you can learn how to communicate data effectively, how to use visualizations and statistics appropriately, and how to spot errors, flaws, or biases in data presentation and interpretation. You can also apply the same skills to your own data stories and improve your data storytelling abilities.

5 Seek feedback and support

Improving your statistical literacy is not a solo endeavor. You can benefit from seeking feedback and support from others who share your interest or expertise in statistics. You can join online communities, such as Reddit, Quora, or Stack Exchange, where you can ask questions, answer questions, or discuss topics related to statistics. You can also find mentors, tutors, or peers who can help you with your learning goals, challenges, or projects. You can also participate in online courses, webinars, or workshops that offer interactive and engaging learning experiences and opportunities to network with other learners and instructors.

6 Keep learning and improving

Statistical literacy is not a fixed or static skill. It is a dynamic and ongoing process that requires curiosity, creativity, and critical thinking. You can always learn new things, improve your skills, and expand your knowledge in statistics. You can keep learning and improving by following the latest trends, developments, and innovations in statistics and data science. You can also challenge yourself with new data sets, tools, methods, or problems that require you to apply or extend your statistical skills. You can also review your progress, reflect on your learning, and celebrate your achievements.

7 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?