Statistics and Data Analysis
Introduction
Data analysis is collecting, interpreting and assessing data using analytical and statistical tools to come up with useful information that will help in decision making. Statistics is a branch of mathematics that deals with collecting, interpreting and analyzing numerical data. Statistical analysis is a subdivision of data analysis that involves collecting and examining samples.
A number of methods are used in data analysis. These include data mining, business intelligence, data visualization, and text analytics. Business intelligence is making data a reality by transforming it into actions, for example, finding markets. Texts analytics is deriving beneficial information from texts. Data visualization refers to representing information using pivotal tables, graphs and other tools of statistics. Data mining is a technique for discovering patterns using statistical methods.
Geo-spatial data
Geo-spatial data is data related to geography. It has a location on the surface of the earth. There are two types of spatial data; vector and raster. Vector uses points, lines, and polygons to represent streams, roads, and cities. Raster data uses cells to represent them. Cities are a single cell, roads a sequence of cells and streams adjacent cells.
Geo-spatial data analysis
Geo-spatial data analysis involves collecting, manipulating and analyzing data that has some geographical information. The data is collected using satellites, GPS and drones. It is later analyzed using GIS which means Geographic Information System. It is a technology-based system that integrates geo-spatial data and tabular data to map, analyze and access real-world problems.
Tabular data is additional information about geo-spatial data. It is also known as attribute data. For instance, if company X is based in New York. New York is the geo-spatial information. The name of the company, the products it offers and the number of customers are attribute data.
GIS uses analytical tools and statistical methods to analyze attribute and geographical information. It is an essential problem-solving tool. It aids in identifying areas affected by natural disasters and predicting areas prone to the crisis. For instance, if there is a disease outbreak in a region. Geo-spatial data analysis help in identifying the regions where the disease is likely to spread.
GIS also assists companies in choosing a strategic point. It identifies locations saturated with companies supplying the same products. This helps start-ups in choosing areas that are less flooded. In case the company is dealing with long-distance trucks, geo- spatial data analysis is essential for identifying the best routes.
Geo-spatial data can detect areas that will experience disasters and climate change. This aids in early preparation and putting necessary measures to mitigate it. In addition, the analysis helps in discovering wet-lands, where agricultural practices can thrive. The public and the government should prevent pollution in such areas.
There are four components in GIS that are essential in making spatial data analysis effective. These include people, hardware, software, and data. People represent the staff members who handle the application, they should not only be effective but also competent and able to deliver quality results.
Data is information on the database. GIS database has two types of data vector and raster, and attribute data. Recording of GIS data sets is known as metadata. It has information such as who created the information, when, how to contact them, explanations of any code of attribute data and coordinate systems.
GIS software is essential in data analysis. It comes in three forms GIS application package, component GIS software, and web GIS software. The GIS application package is the best for geo- spatial editing and analysis. Web GIS software creates interactive maps that can be searched using web browsers.
Dr. John Snow was the first man in the world to conduct a geo-spatial data analysis in London in 1984. This was after a section of people in Soho Town died after a cholera outbreak. Through analysis and some few interviews he conducted. He was able to trace the cause of the disease and predict areas where it was likely to spread. The source was contaminated water in major pumps. The government used the data to prevent the spreading of the disease.
GIS uses some of the methods of data analyses such as data visualization. This comes in the form of cells, points, and lines to represent cities, roads, and streams. It is easy to identify areas with these features on GPS. Tabular data is represented using tables. For instance, if a school is located at a certain point and it is represented using a dot clinking on it will show all the attribute information in table format.
Conclusion
In conclusion, data analysis is the collection, interpretation, and evaluation of data for better decision making. Geo-spatial data is a type of information with a geographical aspect. It is analyzed using GIS. GIS is a technology-based system that incorporates geo-spatial information and tabular data to map and analyze information using analytical and statistical methods.
It is used for identifying disaster-stricken areas, humanitarian crisis, climate change, and predicting areas prone to catastrophes. Information garnered from GIS is crucial for the management of government institutions, businesses, and organizations.
