How do you use SAS to create effective and engaging data visualizations for your research audience?

Select a visualization type that best conveys your message. SAS offers various options like ✓bar charts, ✓scatter plots, and ✓heatmaps. Consider the nature of your data and the story you want to tell.

Begin by thoroughly understanding your data. What variables are you working with? What relationships do you want to highlight? Consider the data’s structure, distribution, and patterns. Select the Appropriate Chart or Graph: a. Use bar charts to compare categorical data or show frequency distributions. b. Line Charts: Ideal for showing trends over time or continuous data points. Use them for time series analysis or to visualize changes. c. Scatter Plots: Use scatter plots to explore relationships between two continuous variables. They reveal correlations and outliers d. Heat Maps: Effective for displaying matrix-like data, such as correlations The right visualization depends on your specific research context and the story you want to tell

Choosing the right type of visualization is like picking the perfect tool for a job. You need to match the type of visualization with the kind of data you have and the story you want to tell. If you have numbers you want to compare, like sales figures over time, a line chart might be best. If you're showing parts of a whole, like the percentage of different types of fruit sold in a grocery store, a pie chart could work well. Just remember, the goal is to make it easy for people to understand your data at a glance, so choose wisely!

✓Tailor the visual elements to enhance clarity and appeal. ✓Adjust colors, fonts, and labels to align with your audience and the context of your data. SAS provides customization options through its programming and graphical interfaces.

1. Customize filters and groups to tailor the visualization to your specific research context. 2. Change data items within your visualization to explore different angles. Adjust variables, calculations, or aggregations to dig deeper into patterns and relationships. 3. SAS Visual Analytics supports custom JavaScript (JS) projects, including D3 visualizations. Thoughtful customization ensures that your visualizations resonate with your research audience and convey insights effectively.

Customizing your visualization is like adding your own personal touch to a picture. You can change colors, labels, and styles to make it look just right. With customization, you can highlight important points and make your visualization stand out. Just play around until it looks perfect to you!

Exporting and sharing your visualization is as easy as sending a picture to a friend. Once your visualization looks great, you can save it as an image or PDF file. Then, you can share it through email, social media, or even print it out. That way, everyone can see and understand your data, no matter where they are!

✓Arrange your visualizations in a logical sequence to tell a compelling story. ✓Use annotations and captions to highlight key insights. ✓SAS allows you to incorporate narrative elements into your visualizations for effective storytelling.

1.Export Options: Image Formats: Export your visualizations as image files (PNG, JPEG, or SVG) for easy inclusion in reports, presentations, or publications. PDF: Create PDF documents containing multiple visualizations for comprehensive reports. 2.Sharing Platforms: Email: Attach visualizations directly to emails. Online Repositories: Share visualizations on platforms like GitHub, GitLab, or personal websites. Collaboration Tools: Use tools like Microsoft Teams to share within your research team. 3.Accessibility and Documentation: Accessibility: Ensure your visualizations are accessible to all audiences (colorblind-friendly, alt text for images). Documentation: Accompany visualizations with clear captions, explanations, and context.

✓Consider the audience's level of expertise. ✓Adjust the complexity of your visualizations accordingly, providing explanations where necessary.

Maintain a consistent color palette, font, and layout across your visualizations. This ensures a cohesive look and reinforces branding or research identity. Add annotations to highlight key points, trends, or outliers. Annotations can include labels, arrows, or callouts to draw attention to specific data points. Arrange your visualizations in a logical sequence to tell a compelling story. Start with an overview and gradually delve into details. Use titles and captions effectively. If sharing online, ensure your visualizations are responsive and adapt well to different screen sizes (e.g., mobile devices). Seek feedback from colleagues or potential research audience members. Iterate based on their input to improve clarity and impact.

Here's what else to consider: Make sure to choose the right format for sharing your visualization. If you're sharing it online, consider using a format like PNG or JPEG for images, or PDF for documents. If you're printing it, make sure the resolution is high enough for clarity. Also, think about who your audience is and how they'll be viewing the visualization. You might need to adjust the size or orientation to make sure it looks good on different devices. Finally, don't forget to include a brief explanation or caption to provide context and help your audience understand what they're seeing.