MapInfo Pro

Statistical analysis is helpful for data exploration and analytics. The information such as mean, median, min, max, range, standard deviation, quartiles etc. values are quite helpful to examine distribution of values and data errors, identify outliers, reclassification of data, summarize data and many more. These analysis helps extract additional information revealing characteristics/ patterns of region/zone which are helpful in spatial decision making.

So, calculating statistical information of a defined boundary (~region/zone) is quite easier using Region Inspection/Region Statistics tool of MapInfo Pro Advanced. It summarizes the values of a raster within the region of vector dataset and appends the results to vector table. Various statistical attributes which can be derived using Region Inspection/Region Statistics tools are

• Minimum
• Maximum
• Average
• Median
• Coefficient of variation
• Range
• Cell count
• Standard deviation
• Null cell count
• Sum of cells
• % Null cells
• Mode
• Lower Quartile
• Upper Quartile
• Inner Quartile Range

In the example below, statistics have been calculated for the distribution of elevation values by parcels. Based on obtained statistics information for each parcel, these can be classified falling into high, medium and low range values. Stats suggests that most parcels are lying in lower elevation range values and hence chances of flood risk with slight rise in sea water could be higher. Such kind of information is useful for insurance companies underwriting risk and premium calculation for a parcel. Similar analysis could be extended for building footprint.

There are various applications in which output derived from region statistics calculation tool can be used such as

• Insurance companies would like to know lowest or highest elevation of building for better flood risk underwriting
• Urban planner may want to know average green space per planning zone or unit
• Police personnel may want to know high crime zones in neighborhood for better deployment of security
• Hydrologist may want to know average elevation, slope and aspect per watershed
• Real Estate agents would like to know sale amount range of parcels for focused client deals
• Crop scientist may want to compute range of soil nitrogen content per paddy field

So, what are you waiting for? Analytics tool is available for you to use and make decisions. Grab a copy of MapInfo Professional and start exploring. Happy Learning!

Statistical analysis is helpful for data exploration and analytics. The information such as mean, median, min, max, range, standard deviation, quartiles etc. values are quite helpful to examine distribution of values and data errors, identify outliers, reclassification of data, summarize data and many more. These analysis helps extract additional information revealing characteristics/ patterns of region/zone which are helpful in spatial decision making.

So, calculating statistical information of a defined boundary (~region/zone) is quite easier using Region Inspection/Region Statistics tool of MapInfo Pro Advanced. It summarizes the values of a raster within the region of vector dataset and appends the results to vector table. Various statistical attributes which can be derived using Region Inspection/Region Statistics tools are

• Minimum
• Maximum
• Average
• Median
• Coefficient of variation
• Range
• Cell count
• Standard deviation
• Null cell count
• Sum of cells
• % Null cells
• Mode
• Lower Quartile
• Upper Quartile
• Inner Quartile Range

In the example below, statistics have been calculated for the distribution of elevation values by parcels. Based on obtained statistics information for each parcel, these can be classified falling into high, medium and low range values. Stats suggests that most parcels are lying in lower elevation range values and hence chances of flood risk with slight rise in sea water could be higher. Such kind of information is useful for insurance companies underwriting risk and premium calculation for a parcel. Similar analysis could be extended for building footprint.

There are various applications in which output derived from region statistics calculation tool can be used such as

• Insurance companies would like to know lowest or highest elevation of building for better flood risk underwriting
• Urban planner may want to know average green space per planning zone or unit
• Police personnel may want to know high crime zones in neighborhood for better deployment of security
• Hydrologist may want to know average elevation, slope and aspect per watershed
• Real Estate agents would like to know sale amount range of parcels for focused client deals
• Crop scientist may want to compute range of soil nitrogen content per paddy field

So, what are you waiting for? Analytics tool is available for you to use and make decisions. Grab a copy of MapInfo Professional and start exploring. Happy Learning!

Statistical analysis is helpful for data exploration and analytics. The information such as mean, median, min, max, range, standard deviation, quartiles etc. values are quite helpful to examine distribution of values and data errors, identify outliers, reclassification of data, summarize data and many more. These analysis helps extract additional information revealing characteristics/ patterns of region/zone which are helpful in spatial decision making.

So, calculating statistical information of a defined boundary (~region/zone) is quite easier using Region Inspection/Region Statistics tool of MapInfo Pro Advanced. It summarizes the values of a raster within the region of vector dataset and appends the results to vector table. Various statistical attributes which can be derived using Region Inspection/Region Statistics tools are

• Minimum
• Maximum
• Average
• Median
• Coefficient of variation
• Range
• Cell count
• Standard deviation
• Null cell count
• Sum of cells
• % Null cells
• Mode
• Lower Quartile
• Upper Quartile
• Inner Quartile Range

In the example below, statistics have been calculated for the distribution of elevation values by parcels. Based on obtained statistics information for each parcel, these can be classified falling into high, medium and low range values. Stats suggests that most parcels are lying in lower elevation range values and hence chances of flood risk with slight rise in sea water could be higher. Such kind of information is useful for insurance companies underwriting risk and premium calculation for a parcel. Similar analysis could be extended for building footprint.

There are various applications in which output derived from region statistics calculation tool can be used such as

• Insurance companies would like to know lowest or highest elevation of building for better flood risk underwriting
• Urban planner may want to know average green space per planning zone or unit
• Police personnel may want to know high crime zones in neighborhood for better deployment of security
• Hydrologist may want to know average elevation, slope and aspect per watershed
• Real Estate agents would like to know sale amount range of parcels for focused client deals
• Crop scientist may want to compute range of soil nitrogen content per paddy field

So, what are you waiting for? Analytics tool is available for you to use and make decisions. Grab a copy of MapInfo Professional and start exploring. Happy Learning!