Reports

Surfer can generate several types of detailed grid reports. This table provides a snapshot of the types of information produced for each report type. Descriptions of the report sections are below the table.

If you make changes to the data selection (i.e. changing a data column or changing the data filtering method) generate a new report by repeating one of the processes listed with the report type.

Information Produced	Report Types and How to Access Them
	Cross Validation Report	Data Statistics Report	Grid Contour Vol/Area Report	Gridding Report	Grid Information Report	Variogram Data Report
	Click Report in the Cross Validation dialog	Click the Statistics button in the Grid Data dialog	Click the Grids \| Calculate \| Contour Vol/Area command	Check the Grid Report Option on the Grid Data dialog	Click the Grids \| Info \| Grid Info command; or click Options \| Grid Info in the Grid Editor	In the Variogram Properties click the Display Statistics button on the Statistics page and then click Report
Data Counts, includes Filtered and at Validation Points	X	X		X		X
Filtering, includes Breakline, Duplicate, Exclusion		X		X
Grid Information, includes Grid Geometry				X	X
Gridding Rules	X			X
Inter-Variable Correlation, Rank Correlation and Covariance	X	X		X		X
Output Grid				X
Principal Component Analysis		X		X
Polygon Used for Statistics					X
Regression, includes Planar: Z=AX+BY+C and Residual: R=AX+BY +C	X	X				X
Statistics, such as Univariate, Nearest Neighbor, and Cross-Validation	X	X		X	X	X
Variogram Grid						X
Volume and Area			X
Z Transform, includes Grid and Data				X

Information Contained in Each Report Section

Each section of the report contains information about the grid, data, or variogram.

Time Stamp

Time of report

Date and time the report was created in

Mon Oct 14 10:43:13 2013

format

Elapsed time to create grid

Seconds required when gridding. Only included in the Gridding Report.

Data Source

Source Data File Name	path and file name of the data used in gridding
X Column	X data column
Y Column	Y data column
Z Column	Z data column
Detrending	variogram data detrending method selected on the General page in the New Variogram dialog. Only included in the Variogram Grid Report.

Data Counts and Filtered Data Counts

Active Data	number of data after applying filters
Original Data	number of original data points (excludes breakline data)
Excluded Data	number of data excluded by the Data Exclusion Filter - the excluded data are listed in the Exclusion Filtering section
Deleted Duplicates	number of duplicates deleted by the Duplicate Data filter - the deleted duplicates are listed in the Duplicate Filtering section
Retained Duplicates	number of duplicates retained by the Duplicate Data filter (this statistic is not computed if the duplicate rule is ALL) - the retained duplicates are listed in the Duplicate Filtering section including any artificial data
Artificial Data	number of artificial data created by the Sum, Average, and Midrange Duplicate Data filters
Superseded Data	Superseded data are number of data eliminated by breaklines in the Data Statistics Report and the Gridding Report. Breakline data always supersede point data. If point data are on, or in the immediate vicinity of, breakline data the point data are eliminated.

Data Counts at Validation Points

The Data Counts at Validation Points section is only included in the Cross Validation Report.

Active Results	locations at which the cross validation interpolation was successfully carried out
NoData Results	The NoData results are the locations at which cross validation interpolation was attempted, but was not successful. For example, the natural neighbor gridding algorithm can only interpolate at locations within the convex hull of the active data. As such, an observation that lies on the convex hull of the original, complete, data set will lie outside of the convex hull of the active data when that observation is the cross validation point. Cross validation is not possible using the natural neighbor algorithm at such a point, so it is assigned the NoData value.
Attempted Results	reports the number of locations at which cross validation interpolation was attempted
Requested Results	contains the original number of random data

Z Data Transform

Includes the transformation method (if any) applied to the Z values. Lists the data that was unable to be transformed in a table.

The rest of the report information is calculated using the active data, including any artificial data generated by duplicate filtering. Excluded, deleted, or superseded data are not included in the following calculations.

Exclusion Filtering

Exclusion Filter String	shows the Data Exclusion Filterstring
Excluded Data	number of data excluded by the Data Exclusion Filter -
Excluded Data Table	the excluded data are listed in a table. The ID is equal to the line number in the original data file. This list is 100 data rows long by default.

Duplicate Filtering

Duplicate Points to Keep	To Keep filter used
X Duplicate Tolerance	maximum X spacing of points to be considered a duplicate
Y Duplicate Tolerance	maximum Y spacing of points to be considered a duplicate
Deleted Duplicates	number of duplicates deleted by the Duplicate Data filter - the deleted duplicates are listed in the Duplicate Filtering section
Retained Duplicates	number of duplicates retained by the Duplicate Data filter (this statistic is not computed if the duplicate rule is ALL) - the retained duplicates are listed in the Duplicate Filtering section including any artificial data
Artificial Data	number of artificial data created by the Sum, Average, and Midrange Duplicate Data filters
Duplicate Data Table	the duplicate data table lists all of the duplicate points with X, Y, Z, ID, and Status. The ID is equal to the line number in the original data file. When the status is artificial, no ID is given since this data does not come from the original data file. The Status (Retained, Deleted, or Artificial) reports how the duplicate was handled. This list is 100 data rows long by default.

Breakline Filtering

When breaklines are used, data that is within the X Tolerance and Y Tolerance, as set in the Filter dialog, of the breakline are deleted due to breakline data superseding original data.

Anisotropy Angle	the anisotropy angle reported for the default variogram
Anisotropy Ratio	the anisotropy ratio reported for the default variogram
X Tolerance	maximum X spacing of points to be considered a duplicate
Y Tolerance	maximum Y spacing of points to be considered a duplicate
Superseded Data	Superseded data are number of data eliminated by breaklines in the Data Statistics Report and the Gridding Report. Breakline data always supersede point data. If point data are on, or in the immediate vicinity of, breakline data the point data are eliminated.
Breakline Data Table	the breakline data table lists all of the superseded data points with X, Y, Z, ID, and Status. The ID is equal to the line number in the original data file. The Status (Retained, Deleted, or Artificial) reports how the duplicate was handled. This list is 100 data rows long by default.

Inter-Variable Correlation

The Inter-Variable Correlation table shows the correlation between the X, Y, and Z variables. The Cross Validation Report also contains Estimated Z and Residual Z columns and rows. The correlations are computed with

The correlation is positive when both variables increase or decrease together. The correlation is negative when one variable increases while the other variable decreases. A correlation of zero shows that there is no linear relationship between the variables.

Inter-Variable Covariance

The Inter-Variance Covariance table shows the covariance between the X, Y, and Z variables. The covariances are computed with

The covariance is positive if, on average, the variables are both above the mean. The covariance is negative if one variable is above the mean and the other variable is below the mean.

Inter-Variable Rank Correlation

The Inter-Variance Rank Correlation table shows the rank correlation between the X, Y, and Z variables. The data is ordered and then assigned a rank value from 1 to the count of values. Rank values range from -1 to +1. The correlation is positive when both variables increase or decrease together. The correlation is negative when one variable increases while the other variable decreases. A correlation of zero shows that there is no linear relationship between the variables.

Univariate Statistics

This group of statistics shows information for X, Y, and Z data. These statistics do not include breakline data.

Count	total number of points
1%-tile	1 percent of the values are smaller than this number and 99 percent of the values are larger
5%-tile	5 percent of the values are smaller than this number and 95 percent of the values are larger
10%-tile	10 percent of the values are smaller than this number and 90 percent of the values are larger
25%-tile	lower quartile; 25 percent of the values are smaller than this number and 75 percent of the values are larger
50%-tile	middle data value, 50 percent of the data values are larger than this number and 50 percent of the data are smaller than this number
75%-tile	upper quartile; 75 percent of the values are smaller than this number and 25 percent of the values are larger than this number
90%-tile	90 percent of the values are smaller than this number and 10 percent of the values are larger
95%-tile	95 percent of the values are smaller than this number and 5 percent of the values are larger
99%-tile	99 percent of the values are smaller than this number and 1 percent of the values are larger
Minimum	minimum value
Maximum	maximum value
Mean	arithmetic average of the data
Median	middle data value, 50 percent of the data values are larger than this number and 50 percent of the data are smaller than this number
Geometric Mean	geometric mean of the data
Harmonic Mean	harmonic mean of the data
Root Mean Square	square root of the mean square
Trim Mean (10%)	Trim Mean is the mean without the upper five percent and lower five percent of the data, therefore, extreme value influence is removed. If there are fewer than 20 data points, the minimum and maximum data points are removed instead of the upper and lower five percent.
Interquartile Mean	interquartile mean, or midmean, is a truncated mean using only the data in the second and third quantiles (all data beween the 25%%-tile and 75%%-tile)
Midrange	the value halfway between the minimum and maximum values Midrange = (Minimum + Maximum ) / 2
Winsorized Mean	Winsorized mean is a truncated mean. This method replaces the extreme highs and lows values with a more central value. This mean is less sensitive to outliers.
TriMean	the trimean, or Tukey's trimean, is a measure of probability distribution location. This is equivalent to the the sum of (quartile 1, 2 times the quartile 2, and quartile 3) divided by four.
Variance
Standard Deviation	square root of the variance
Interquartile Range	separation distance between the 25%-tile and 75%-tile this shows the spread of the middle 50 percent of the data, similar to standard deviation, though this statistic is unaffected by the tails of the distribution
Range	separation between the minimum and maximum value Range = Maximum - Minimum
Mean Difference	the mean or average of the absolute difference of two random variables X and Y.
Median Abs. Deviation	Median Absolute Deviation is the median value of the sorted absolute deviations. It is calculated by 1. computing the data's median value 2. subtracting the median value from each data value 3. taking the absolute value of the difference 4. sorting the values 5. calculating the median of the values
Average Abs Deviation	Average Absolute Deviation is the average value of the sorted absolute deviations. It is calculated by 1. computing the data's average mean value 2. subtracting the mean value from each data value 3. taking the absolute value of the difference 4. calculating the average value
Quartile Dispersion	Measures dispersion of the data using: (Quartile 3 - Quartile 1)/(Quartile 3 + Quartile 1)
Relative Mean Difference	The mean difference of the entire data set divided by the sample mean of the data set
Standard Error	The standard error of the mean is the standard deviation of those sample means over all possible samples drawn from the population. This is calculated by dividing the standard deviation by the square root of the number of samples.
Coef. of Variation	The Coefficient of Variation is calculated by dividing the standard deviation by the mean. If a "-1" is reported, the coefficient of variation could not be computed. The coefficient of variation is computed only for the Z values.
Skewness	The Coefficient of Skewness is calculated by If a "-1" is reported, the coefficient of skewness could not be computed. The coefficient of skewness is computed only for the Z values.
Kurtosis	The Coefficient of Kurtosis is calculated by
Sum	the sum of all X, Y, or Z values
Sum Absolute	the absolute value of the sum of all X, Y, or Z values
Sum Squares	the sum of all squared X, Y, or Z values
Mean Square

Planar Regression

Planar regression is an ordinary least-squares fit where Z=AX+BY+C.

The Parameter Values are the A, B, and C values.
The Standard Error is the estimated standard deviation of the parameters.
The Inter-Parameter Correlations are the correlation between A, B, and C coefficients.
The ANOVA Table shows regression statistics on the planar fit where df are the degrees of freedom and F is the ratio of the mean squares.
The Coefficient of Multiple Determination (R2) is calculated with

For the Cross Validation Report, the planar regression is the residual regression at the validation points.

Nearest Neighbor Statistics

The nearest neighbor statistics represent aspects of the data values and of the data locations. The nearest neighbor to a data point uses a simple separation distance without taking anisotropy into account. If two or more points tie as the nearest neighbor, the tied data points are sorted on X, then Y, then Z, and then ID. The smallest value is selected as the nearest neighbor.

The Separation column shows the separation distances between the observation and its nearest neighbor. The |Delta Z| column shows the absolute values of the differences between the observation Z value and the nearest neighbor Z value.

The statistics are the same as the Univariate Statistics (see above).

The Nearest Neighbor Statistics also includes the Complete Spatial Randomness section. The Complete Spatial Randomness statistics measure how random locations are in space. Surfer does not correct for edge effects so the statistics may be biased.

Lamda

is the average spatial density

Clark and Evans

where

= average spatial density

Si= separation distance between the observation and the nearest neighbor

The distribution of this statistic is normal, with a mean equal to one and a variance of

See Clark and Evans (1954) and Cressie (1991) for more information.

Skellam

where

= average spatial density

Si= separation distance between the observation and the nearest neighbor

The distribution is Chi-Squared with 2N degrees of freedom. See Skellam (1952) and Cressie (1991) for more information.

Principal Component Analysis

Principal component analysis (PCA) is a mathematical procedure that uses orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. The number of principal components is less than or equal to the number of original variables. The principal components are calculated for the X, Y, and Z values. A value is also reported for each principal component.

Variogram Grid

Max Lag Distance	Max Lag Distance set on the General page in the New Variogram dialog
Angular Divisions	number of Angular Divisions set on the General page in the New Variogram dialog
Radial Divisions	number of Radial Divisions set on the General page in the New Variogram dialog

Output Grid

Grid File Name	name of the output grid file
Grid Size	number of rows and columns in the grid
Total Nodes	number of columns times the number of rows
Filled Nodes	number of grid nodes containing interpolated values
NoData Nodes	number of grid nodes containing the NoData value
NoData Value	reports the Z value associated with NoData nodes
X Minimum	minimum X grid line value specified in the Output Grid Geometry group in the Grid Data dialog
X Maximum	maximum X grid line value specified in the Output Grid Geometry group in the Grid Data dialog
X Spacing	X spacing set in the Grid Data dialog
Y Minimum	Minimum Y grid line value specified in the Output Grid Geometry group in the Grid Data dialog
Y Maximum	Maximum Y grid line value specified in the Output Grid Geometry group in the Grid Data dialog
Y Spacing	Y spacing set in the Grid Data dialog

Grid Information

Grid File Name	name of the output grid file
Grid Size	number of rows and columns in the grid
Total Nodes	number of columns times the number of rows
Filled Nodes	number of grid nodes containing interpolated values
NoData Nodes	number of grid nodes containing the NoData value
NoData Value	reports the Z value associated with NoData nodes

Grid Geometry

X Minimum	minimum X grid line value specified in the Output Grid Geometry group in the Grid Data dialog
X Maximum	maximum X grid line value specified in the Output Grid Geometry group in the Grid Data dialog
X Spacing	X spacing set in the Grid Data dialog
Y Minimum	Minimum Y grid line value specified in the Output Grid Geometry group in the Grid Data dialog
Y Maximum	Maximum Y grid line value specified in the Output Grid Geometry group in the Grid Data dialog
Y Spacing	Y spacing set in the Grid Data dialog

Polygon used for statistics

Side	Whether statistics were calculated for values Inside or Outside the polygon(s)
Polygons	Number of polygons used for calculating statistics
Number of points	Total number of vertices among the polygon(s)

Gridding Rules

This section displays the gridding method used, as well as the option settings for each gridding method.

Univariate Grid Statistics

The Univariate Grid Statistics are the same as those reported in the Univariate Statistics and Nearest Neighbor Statistics sections.

Univariate Cross-Validation Statistics

The Univariate Cross Validation Statistics section are the same as those reported in the Univariate Statistics. It also contains an additional column of data, called Data Used. This column shows the number of data points used in the calculation.

Volumes and Areas

Volume and area calculations are based on the Simple level method for contour line properties. Minimum and maximum contours along with the contour interval must be specified. Surface area and planar area calculations are made above, below, and between contours. Contour volume calculations are made above, below, and between contours.