Data Visualization
Statisticians, data miners, and business analysts are finding important patterns by visualizing their data.
Statisticians, data miners, and business analysts are finding important patterns by visualizing their data.
Software
JMP, SAS, STATA, R, EXCEL
JMP, SAS, STATA, R, EXCEL
Humans have an amazing ability to use their eyes to detect small and suble patterns. Data analysts
are now focussing more and more on ways to visualize data and information as a way to explore hypotheses, detect strange patterns, and draw meaningful conclusions. Although complex statistical models are often useful, clear graphical presentations of data often are more valuable for interpreting data. Visualization tools also are also becoming more sophisticated in software applications
intended for non-analysts. For example, healthcare providers can be given visual "dashboards" that depict patient-level data, and allow them to make comparisons between clinical lab values and
normal ranges.
Computer scientists, statisticians, and business intellgence analysts are becoming increasingly interested in novel ways to visualize complex data to find meaningful patterns. The science of visualization offers many important guidelines for visualizing data. Edward Tufte, a leading
researcher in the field, stresses the importance of clear charts and figures free of "chart junk"
that enable the eyes to compare the data. The graphics, however, can contain a large amount of information in small area given the power of the human eye. For example, heat maps and "spark lines" can be used to summarize a huge amount of data within a page-size graphic.
I have many years of experience producing effective charts, tables, and graphs using a variety of software packages to help people better understand their data.
are now focussing more and more on ways to visualize data and information as a way to explore hypotheses, detect strange patterns, and draw meaningful conclusions. Although complex statistical models are often useful, clear graphical presentations of data often are more valuable for interpreting data. Visualization tools also are also becoming more sophisticated in software applications
intended for non-analysts. For example, healthcare providers can be given visual "dashboards" that depict patient-level data, and allow them to make comparisons between clinical lab values and
normal ranges.
Computer scientists, statisticians, and business intellgence analysts are becoming increasingly interested in novel ways to visualize complex data to find meaningful patterns. The science of visualization offers many important guidelines for visualizing data. Edward Tufte, a leading
researcher in the field, stresses the importance of clear charts and figures free of "chart junk"
that enable the eyes to compare the data. The graphics, however, can contain a large amount of information in small area given the power of the human eye. For example, heat maps and "spark lines" can be used to summarize a huge amount of data within a page-size graphic.
I have many years of experience producing effective charts, tables, and graphs using a variety of software packages to help people better understand their data.
