The Global Forecasting System (GFS) atmospheric model is a dataset from the National Oceanic and Atmospheric Administration (NOAA) and National Centers for Environmental Prediction (NCEP). In this database, wind is stored as velocity vector components (U: eastward_wind and V: northward_wind) at 10 m above the Earth’s surface. The resolution of the data is 0.5 degrees, approximately 50 km. Wind velocities have been registered six times per day (00:00 – 03:00 – 06:00 – 09:00 – 12:00 – 15:00 – 18:00 – 21:00 (UTC)), since 6th May 2011 and is updated daily.
Introduction This post offers some technique on how to analyse data from a surveys and questionnaires in R, provides tips on visualizing survey data, and exemplifies how survey and questionnaire data can be analyzed.
Questionnaires and surveys are widely used in research and thus one of the most common research designs. Questionnaires elicit three types of data:
Factual Behavioral Attitudinal While factual and behavioral questions are about what the respondent is and does, attitudinal questions tap into what the respondent thinks or feels.
Often times when w are working with data, there always a geospatial component to the data—the locations. Most of us have used static maps to reveal information that other plots can not. And interactive maps can enliven geographic information to new insights. The most important type of interactivity, is the display of geographic data on interactive or ‘slippy’ web maps. Interactivity can take many forms, the most common and useful of which is the ability to pan around and zoom into any part of a geographic dataset overlaid on a ‘web map’ to show context.
