Working With Numbers Statistics PDF Download

Size Matters: How Visual Analytics Will Bring Numbers to Life The increasing volume of quantitative data in modern communication is calling for more effective visualization design techniques to improve clarity and decision-making. The LAVA visual analytic design language proposes a new vernacular to take big data to big audiences. Big Data. The Internet of Things. Cloud Computing. Predictive Analytics. Any trip through today's information technology news will surely include some of these terms. Just as the Web and social media allow more people and institutions to connect with each other to exchange sentiment and ideas, a parallel system exists to do the same thing with quantitative facts. An ever-more automated array of sensors and monitors embedded in our businesses, governments, physical infrastructures, vehicles, the environment, and even our bodies, are being added to the more traditional practice of manual observation and data entry in the effort to record and store the daily up-and-down states of stuff we care about. The variables are called Measures, and include things like sales, windspeed, steps taken, or heart rate. The things being measured are called Entities, such as a car model, an airport, your family, or your heart. Combining Measures with Entities creates Metrics - Sales at a cash register or of a car model, windspeed at the airport, steps taken by your family today, your resting heart rate. Metrics are how we understand quantitative data from the world around us. Analytics is the science of working with metrics to make better, more informed decisions in our work and lives. Visual Analytics is the expression of metrics geometrically - with lines and shapes versus with numbers in spreadsheets - so as to make them easier to understand and interpret. As more metrics are made available and relevant to more people, presenting them visually is a key aspect of ensuring that audiences find them legible - or clear and able to be read - and readable - or enticing and likely to be read. While these dual masters of function and elegance are present in all design practice, visual analytics require a balance skewed in favor of clarity, efficiency, mathematical precision, and measureable audience cognition.